Relationship between N100 amplitude and T1w/T2w-ratio in the auditory cortex in schizophrenia spectrum disorders

Relationship between N100 amplitude and T1w/T2w-ratio in the auditory cortex in schizophrenia spectrum disorders | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Relationship between N100 amplitude and T1w/T2w-ratio in the auditory cortex in schizophrenia spectrum disorders Nora Slapø, Kjetil Jørgensen, Stener Nerland, Lynn Egeland Mørch-Johnsen, and 19 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3906183/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 17 Jan, 2026 Read the published version in Schizophrenia → Version 1 posted You are reading this latest preprint version Abstract Schizophrenia spectrum disorders (SCZ spect ) are associated with altered function in the auditory cortex (AC), indicated by reduced N100 amplitude of the auditory evoked potential (AEP). While the neural substrate behind reduced N100 amplitude remains elusive, myelination in the AC may play a role. We compared N100 amplitude and magnetic resonance imaging (MRI) T1 weighted and T2 weighted ratio (T1w/T2w-ratio) as a proxy of myelination, in the primary AC (AC1) and secondary AC (AC2) between SCZ spect (n = 33, 48% women) and healthy controls (HC, n = 144, 49% women). Further, we examined associations between N100 amplitude and T1w/T2w-ratios in SCZ spect and HC. We finally explored N100 amplitude and T1w/T2w-ratios in the AC1/AC2 and association between N100 amplitude and T1w/T2w-ratios between male and female SCZ spect and HC. N100 amplitude did not differ between SCZ spect and HC or between female SCZ spect and female HC, but was significantly reduced in male SCZ spect compared to male HC (est = 4.3, se = 1.63, t = 2.63, p = 0.010). Further, T1w/T2w ratios in the AC1/AC2 did not differ between any groups. Finally, N100 amplitude was not associated with T1/T2-ratios in the AC1/AC2 in any groups. Reduced N100 amplitude in male SCZ spect compared to male HC, suggest that sex-specific effects should be considered in research on SCZ spect neurophysiology. Our findings did not support the hypothesis that reduced myelination in the AC1/AC2, as indexed by T1w/T2w-ratio, underlies N100 abnormalities in SCZ spect . However, more precise estimates of intracortical myelin are needed to confirm this. Biological sciences/Neuroscience Health sciences/Diseases/Psychiatric disorders/Schizophrenia Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Schizophrenia spectrum disorders (SCZ spect ) are severe mental disorders affecting approximately 1.0% of the general population 1 . Although the precise neural substrates of SCZ spect remain elusive, structural magnetic resonance imaging (MRI) studies suggest the involvement of the auditory cortex (AC) 2,3 . At the functional level, electroencephalography (EEG) studies have consistently demonstrated reduced amplitude 4–7 and delayed latency 8 of the N100 component of the auditory evoked potential (AEP) in SCZ spect . The N100 amplitude is believed to reflect how pyramidal cells in the AC respond to auditory stimuli 9,10 . While the structural and biological correlates for N100 amplitude reductions in SCZ spect remain unclear, altered myelination in the AC may play a role given that myelin is essential for fast and synchronized communication between neurons 11 . Thus, altered myelination in the AC in SCZ spect 12,13 may also partly explain the high prevalence of auditory hallucinations in these disorder 12,14–16 . Further, myelination directly impacts on key features of brain dynamics in the millisecond range as measured by EEG 17–19 and previous studies have shown associations between myelin indices and evoked response potentials (ERPs) 20,21 in healthy individuals. Further, individuals with multiple sclerosis (MS), a demyelination brain disorder, have reduced amplitude and delayed latency of the P100 component of the visual evoked potential 22,23 . While the relationship between the amplitude of the N100 component of the AEP and myelination in the AC in healthy individual remains elusive, here we examined the hypothesis that altered myelination in AC may be correlated with reduced N100 amplitude in SCZ spect . Altered cortical myelination is associated with a vulnerability towards SCZ spect 24–28 . MRI studies using gray matter/white matter contrast (GWC) or diffusion tensor imaging (DTI), suggest altered myelination in auditory regions in SCZ spect 28,29 . Further, connectivity in auditory fiber bundles is connected to auditory hallucinations in SCZ spect 30–33 . The ratio between T1- (T1w) and T2- (T2w) weighted MRI (i.e., the T1w/T2w-ratio) has been used as a proxy for cortical myelin microstructure 34–36 and has a close spatial correlation with myelin-based histology 37–39 . Further, patients with MS have reduced T1w/T2w-ratio 40,41 that is associated with tissue damage 42,43 . Together, these studies support the use of T1w/T2w-ratio as a proxy for myelin. While one study found globally reduced T1w/T2w-ratio in SCZ spect 44 , another study demonstrated reduced T1w/T2w-ratio in specific brain areas only 45 . However, none of these studies included intensity normalization, which has been shown to improve test-retest reliability of the T1w/T2w-ratio 34 . While several lines of evidence suggest altered myelination in the pathogenesis of SCZ spect 30,46 , whether there is a direct link between myelination and function in the AC in SCZ spect , remains unknown. To the best of our knowledge, no T1w/T2w-ratio abnormalities in the AC has been reported in SCZ spect . Understanding the influence of biological sex on AC function and structure in SCZ spect may provide insight into the neural substrate behind the well-established sex differences in the pathophysiology and treatment response in SCZ spect 47,48 . While previous studies report sex differences in the ERP- P300 component 49 and in the mismatch negativity 50 in SCZ spect , studies investigating sex difference in the N100 amplitude are sparse 51–53 . While previous studies have reported sex difference in brain structure in SCZ spect 48 to our knowledge, no study has investigated sex difference in T1w/T2w-ratio in the AC in SCZ spect . Here we aimed to provide new insight into the biological and structural correlates of N100 amplitude in SCZ spect and healthy controls (HC) by combining EEG and MRI, two non-invasive neuroimaging methods to study brain function and structure, respectively. To accomplish this, we examined the relationship between the N100 amplitude and the T1w/T2w-ratio in the primary auditory cortex (AC1) and in the secondary auditory cortex (AC2). These relationships are especially intriguing since reduced N100 amplitude is among one of the most consistently observed EEG changes in SCZ spect 4–7,10,54–56 . Given reports of important sex-differences in SCZ spect pathophysiology 48,57–60 , we also aimed to assess whether sex has an impact on these relationships. Methods Participants Participants with a DSM-IV diagnosis within the SCZ spect and HC were included from the ongoing Thematically Organized Psychosis (TOP) research study and partly overlap with the participants included in our previous study 61 . HC were randomly drawn from the national population register within the same catchment area and asked to participate in the study. The study was approved by the Regional Committees for Medical and Health Research Ethics of South-Eastern Norway and conducted in accordance with the Helsinki declaration. Participants provided written informed consent. Participants with a history of head trauma resulting in loss of consciousness, an IQ < 70, or somatic or neurological disorders believed to influence brain function, were excluded from the study. In addition, HC with a history of mental disorders and/or severe mental disorders in first degree relatives or a history of alcohol- and substance abuse or dependence were excluded. In total, MRI and EEG data was available for 442 participants (50 SCZ spect and 392 HC). We excluded participants (7 SCZ spect and 20 HC) with clinically relevant incidental findings on their MRI scan (cysts > 1x1cm, empty sella turcica, greater pituitary gland abnormalities, arterial-venous malformations, multiple sclerosis changes, tumors or infarctions), with poor AEP on visual inspection (10 SCZ spect and 61 HC) and with a time interval between MRI scanning and EEG recording of more than 12 months (1 HC). Since our healthy controls were significantly older than patients with SCZ spect , we selected controls that were similar in age with patients and excluded all participants that were older than 54 years. This resulted in the exclusion of 133 HC. The final sample consisted of 177 participants, including 33 individuals with SCZ spect (schizophrenia [n = 21], schizophreniform [n = 1] and psychosis not otherwise specified [n = 11]) and 144 HC. In this sample, MRI, EEG and clinical investigations were performed between 2015 and 2019 with a median time interval between MRI and EEG examinations of 12 days (0-337 days; interquartile range = 32 days). Clinical assessment Diagnosis, age of onset, duration of illness (DOI), psychosocial functioning, current symptoms and the use of antipsychotic medication(s) was assessed as described previously 61 . Trained clinical psychologists or physicians diagnosed the patients according to DSM-IV criteria using the Structural clinical interview for DSM-IV (SCID-I) 62 . We defined age of onset as age at first positive psychotic symptoms (verified by SCID-I) and the duration of illness (DOI) as years from age of onset to age at MRI. To assess psychosocial functioning we used the split version of the Global assessment of function (GAF-S and GAF-F) scale 63 . Current symptoms were evaluated using the Positive and negative syndrome scale (PANSS) interview 64 . For each patient, the current dosage of antipsychotic medication(s) was converted into Defined Daily Dose (DDD), where 1 DDD is the assumed average maintenance dose per day for a drug used for its main indication in adults ( www.whocc.no/atc_ddd_index/ ). In total, 21 patients were using antipsychotic medication, 7 patients were not using antipsychotic medication. Information about medication use was missing for 5 patients. MRI processing MRI were processed in the recon-all stream of FreeSurfer version 6.0.0 ( https://surfer.nmr.mgh.harvard.edu ) 65 . Briefly, this processing stream include removal of non-brain tissue, Talairach transformation, and intensity non-uniformity correction. Intensity information was used to reconstruct the inner (i.e., the gray/white matter boundary) and outer (i.e., the gray matter/cerebrospinal fluid boundary) surfaces of the cerebral cortex. Quality control and editing was conducted by trained research assistants following standard FreeSurfer procedures. At this stage, no participants were excluded. The T1w/T2w-ratio was computed using an approach previously found to have high test-retest reliability 34 . Briefly, this approach performs post hoc corrections for field inhomogeneities, partial voluming, and the presence of surface outliers, and intensity normalization using WhiteStripe 66 , which uses intensity values in normal-appearing white matter to harmonize T1w/T2w-ratio values. The mean T1w/T2w-ratios were extracted in three bilateral regions of interest in the Destrieux atlas 67 : The anterior transverse temporal gyrus of Heschl (HG), the transverse temporal sulcus (HS) and the temporal plane of the superior temporal gyrus (PT). Cortical labels were visually inspected to ensure correct placement. No subjects were excluded due to poor cortical labelling. For the main analyses, we defined two main regions of interest; the HG, referred to as the AC1 in the manuscript, and the combined HS and PT, referred to as AC2 in the manuscript. The T1w/T2w-ratio was calculated as an area-weighted mean across hemispheres and sub-regions. See Supplementary Note 1 for a discussion around parcellation of the AC and Supplementary Note 2 for details on how T1w/T2w-ratio was calculated. Supplementary Figs. 1 and 2 show the AC1 (HG) and AC2 (HS-PT) regions of interest. Figure 1 shows example T1- and T2-weighted volumes and the T1w/T2w-ratio volumes. Auditory evoked potentials obtained from the PPI paradigm AEPs were elicited during a prepulse-inhibition (PPI) task and EEG data was acquired and processed as described previously 61 . Supplementary Fig. 3 shows the timeline of the entire EEG session, where the PPI-paradigm was presented together with other tasks. During the PPI paradigm, the participants focused on a red dot in the middle of a computer-screen while exposed to a constant background noise at 70 dB for 3-minutes (to allow for habituation) followed by the main PPI experiment. This consisted of five main conditions, with 12 presentations each: 1) Startle-stimuli presented alone (40 ms white noise with near instantaneous rise/fall times presented at 115 dB); 2; startle stimuli preceded 30 ms earlier by weaker prepulse stimuli (20 ms white noise with near instantaneous rise/fall times presented at 85 dB); 3; startle stimuli preceded 60 ms earlier by the weaker prepulse stimuli; Startle stimuli preceded 120 ms earlier by the weaker prepulse; and 5) the weaker prepulse stimuli presented alone. The current paper focuses on AEPs elicited by the prepulse stimulus alone (presented at 85 dB), since this typically does not elicit a muscular startle response. While we thus compute ERPs from relatively few trials, the long average interstimulus interval (ISI: approximately 9 seconds), in combination with the relatively strong stimulus intensity (85 dB), nonetheless elicited robust AEPs 68 . Prior to the EEG examination, hearing was assessed at 20 dB and 40 dB. All participants that were included in the current study were able to hear the auditory stimuli at < 40 dB. Figure 2 illustrates individual AEP from 12 randomly selected individuals with SCZ spect . Figure 3 illustrates individual AEP from 24 randomly selected HC. Supplementary Fig. 4A-B illustrate mean AEPs from all SCZ spect and HC. EEG acquisition and processing We recorded EEG data at 2048 Hz from 64 Ag-AgCl scalp electrodes arranged according to the international 10–5 system using a BioSemi ActiveTwo amplifier. In addition, four external electrodes recorded lateral and vertical eye movements and two recorded the heart rhythm (electrocardiography). The Biosemi system uses a common mode sense with a driven right leg electrode in order to minimize common mode voltages. All offline EEG processing was conducted using the MATLAB-based EEGLAB toolbox 69 . After down-sampling to 512 Hz, we removed noisy channels using the PREP Pipeline algorithms with default setting 70 . We referenced remaining channels to the average of all good channels before we interpolated removed channels from surrounding channel potentials. Next, we re-referenced all channels to the new common average obtained after interpolation of bad channels. After average referencing, we removed the mean offset from all channels and applied a high pass filter of 1 Hz. The Trimoutlier eeglab plugin ( https://sccn.ucsd.edu/wiki/TrimOutlier ) identifies and remove sections of bad data (defined as +/- 500 ms around any datapoint exceeding 500 µV across the 64 scalp channels) in the continuous EEG files. Next, independent component analysis (ICA) and automated detection of eye-blink artifacts (ICLABEL) 71 were used to automatically identify EEG artifacts such as eye blinks, line noise, muscle movements, heart noise, and channel noise. All independent components were also visually inspected, before rejection of components with < 50% chance of originating from brain activity (assigned by ICLabel). Cleaned EEG data was next low pass filtered to 40 Hz and separate epochs were extracted for each stimulus event with the time window of -200 ms to 700 ms. Finally, epoched data was baseline-corrected from − 100-0 ms. Prior to extraction of ERP voltages, the ERPs were re-referenced to linked mastoids to capture both the negative (on centro-frontal electrodes) and positive (on inferior temporal and posterior electrodes) polarity of the auditory ERP (which inverts over the Sylvian fissure). Trials containing amplitudes exceeding +/- 100 µV were excluded prior to averaging. All 12 prepulse alone trials were included. Peak latency and amplitude for the N100 component was defined as the minimal amplitude within a time window from 50–200 ms after stimulus onset and extracted from channel Cz. In our main analyses we focused on the N100 amplitude from the Cz electrode. However, we also examined N100 latency (Supplementary analysis 2) . AEPs of individual participants were visually inspected in EEGLAB to ensure that the time windows used in the scripts were correct and that they accurately identified peaks and latencies (between 50–200 ms). After visual inspection of individual AEPs, we concluded that for the majority of subjects 12 prepulse alone trials were indeed sufficient for eliciting robust AEPs. Further, after visual inspection of individual AEPs, we excluded 74 participants where the peak N100 amplitude (the most negative peak) was outside of the latency range of 50-200ms. N100 amplitude that is generated at 85 db and a longer ISI will elicit a higher amplitude than N100 generated at lower db and shorter ISI 72 . Visual inspection revealed that N100 amplitudes were negative for all participants (from: -3.18µV to − 43.62µV). To ease interpretation on the direction of correlation, we multiplied all negative values with − 1, giving N100 amplitudes of 3.18µV − 43.62µV, so that a higher number reflects a more prominent N100. Statistical analyses Statistical analyses were conducted using R version 3.6 ( https://www.r-project.org ; R Core Team, 2014). Group differences in demographics and clinical variables, as provided in Table 1 , were calculated using the t-test for continuous variables and the chi-squared test for categorical variables. First, to calculate mean N100 amplitude, T1w/T2w-ratio in AC1 and in AC2 in SCZ spect (n = 33) and HC (n = 144), we performed separate analysis of covariance (ANCOVA), where N100 amplitude, T1w/T2w-ratio in AC1 or in AC2 was set as outcome variable, diagnostic group (SCZ spect or HC) and sex (female or male) as factors, and age as a covariate. To compare the N100 amplitude and the T1w/T2w-ratio in AC1 and AC2 between patients and controls, we used linear models where N100 amplitude or the T1w/T2w-ratio in AC1 or in AC2 were dependent variables and diagnostic group was the independent variable of interest. The models were adjusted for age and sex. Cohen’s d and Hedge´s g for group comparisons were calculated from differences in predicted means 73 . For the linear regression analyses a p-value < 0.017 was considered significant (Bonferroni correction for three comparisons, i.e., differences in N100 amplitude, in T1w/T2w in AC1 and in T1w/T2w in AC2). To test for associations between N100 amplitude and T1w/T2w-ratio in AC1 and in AC2, we ran separate linear models in SCZ spect and HC, where the N100 amplitude was the dependent variable and T1w/T2w-ratio in AC1 or in AC2 as well as age and sex were independent variables. Thereafter, to examine whether the associations between N100 and T1w/T2w-ratio in AC1 and in AC2 differed between diagnostic groups (SCZ spect and HC), we ran linear models in the combined sample (n = 177) of SCZ spect and HC with N100 amplitude as dependent variable and diagnosis, T1w/T2w-ratio in AC1 or in AC2 and the interaction term (diagnosis* T1w/T2w-ratio) as independent variables. For these analyses a p-value < 0.025 was considered significant (Bonferroni correction for two comparisons, i.e., associations between N100 amplitude and T1w/T2w-ratio in AC1/AC2). We performed sex stratified ANCOVA, where N100 amplitude, T1w/T2w-ratio in AC1 or in AC2 were set as outcome variables, diagnostic group as factor and age as a covariate. We ran this analysis in female and males separately. To compare the N100 amplitude and the T1w/T2w-ratio in AC1 and AC2 between female SCZ spect and female HC and between male SCZ spect and male HC, we used linear models where N100 amplitude, the T1w/T2w-ratio in AC1 or in AC2 were dependent variables and diagnostic group (SCZ spect or HC) was the independent variable of interest. The models were adjusted for age. We ran this model in females (n = 76) and males (n = 91) separately. Cohen’s d and Hedge´s g for group comparisons were calculated from differences in predicted means 73 . For the linear regression analyses a p-value < 0.017 was considered significant. To test for associations between N100 amplitude and T1w/T2-ratio in AC1 or in AC2 in female and male SCZ spect and HC, we ran models in the female SCZ spect , female HC, male SCZ spect and male HC samples separately. In these models, the N100 amplitude was the dependent variable and T1w/T2w-ratio in AC1 or in AC2, as well as age were independent variables. Thereafter, to examine whether the associations between N100 amplitude and T1w/T2w-ratio in AC1 and in AC2 differed between sex, we ran linear models with N100 amplitude as the dependent variable and sex, T1w/T2w-ratio in AC1/AC2 and the interaction term (sex*T1w/T2w-ratio in AC1/AC2) as well as age and diagnosis (SCZ spect or HC), as independent variables. We fitted this model in the combined sample (n = 177) of female and male patients and controls. For these analyses a p-value < 0.025 was considered significant. In addition to our main analyses, we ran supplementary analyses assessing T1w/T2w-ratio in AC1 and in AC2 in each hemisphere and its association with N100 amplitude in SCZ spect and HC. In addition, we examined N100 latency and its association with T1w/T2w-ratio in AC1 and in AC2 in SCZ spect and HC. Further, we examined how much of the variance in N100 amplitude was explained by age and sex and assessed differences in demographics and in our EEG and MRI data between female and male patients and controls. We also examined differences in N100 amplitude and T1w/T2w-ratios in AC1/AC2 in female SCZ spect compared to male SCZ spect , in female HC compared to male HC and between the combined sample of male SCZ spect and male HC and the combined sample of female SCZ spect and female HC. Further, we examined N100 amplitude and T1wT2w ratio in the AC1 and AC2 and the association between N100 amplitude and T1wT2w ratios in patients with auditory hallucinations (AH+) and without auditory hallucinations (AH-). As two sensitivity analyses, we also examined N100 amplitude and T1wT2w ratio in the AC1 and AC2 and the N100-T1w/T2w associations in a sample prior to excluding older controls and in a sample where we performed strict age matching between patients and controls. Lastly, we examined the effect of use of antipsychotics and PANSS scores on our EEG and MRI data. Results Demographics and clinical data There were no significant differences in age or sex distribution between SCZ spect and HC (Table 1). Table 1 . Participant characteristics SCZ spect [n=33 ] HC [n=144 ] SCZ spect vs. HC p-value Women , n (%) 16 (48) 70 (49) 0.99 Age, Mean (range, sd) 29.96 (18.46-54.06, 9.03) 32.94 (18.50-45.58, 7.42) 0.09 Time between EEG and MRI, Median (range, IQR) 6 (0-337, 37) 13 (0-278, 31) 0.51 Age of Onset, Mean (range, sd) 24.50 (17-37, 5.18) / / DOI, Mean (range, sd) 4.13 (0-20.47, 5.35) / / GAF-S, Mean (range, sd) 54.48 (38-85, 11.54) / / GAF-F, Mean (range, sd) 55.18 (35-85, 14.11) / / PANSS total, Mean (range, sd) 56.12 (33-91, 14.41) / / PANSS G, Mean (range, sd) 29.79 (18-47, 7.24) / / PANSS P, Mean (range, sd) 12.97 (7-24, 3.84) / / PANSS N, Mean (range, sd) 13.36 (7-25, 5.23) / / Antipsychotic drug use, DDD, Mean (range, sd) 1.01 (0.19-2.25, 0.58) / / Note: Table 1 shows the demographics of the final study sample. SCZ spect , patients with schizophrenia spectrum disorders and in HC, healthy controls; n, number; %, percentage; range (min-max); sd, standard deviation; EEG, electroencephalography; MRI, magnetic resonance imaging; IQR, interquartile range; Age of onset, age of onset of first positive psychotic symptom in years; DOI, duration of illness in years; GAF, Global assessment of function; GAF-S, GAF-symptoms, GAF-F, GAF- functioning; PANSS, positive and negative syndrome scale; G, general; P, positive; N, negative; DDD, defined daily dose of antipsychotics; 9 SCZ spect had missing information about age of onset and DOI. 5 had missing information about DDD. Mean N100 amplitude, T1w/T2w-ratio in AC1 and T1w/T2w-ratio in AC2 in SCZ spect and HC Estimated marginal means and differences in means between SCZ spect and HC are provided in Table 2. Table 2 Mean N100 amplitude, T1w/T2w-ratio in AC1 and AC2 in SCZ spect and HC N100 amplitude (microvolts) Mean (SE) [95% CI] AC1 T1w/T2w-ratio Mean (SE) [95% CI] AC2 T1w/T2w-ratio Mean (SE) [95% CI] SCZ spect [n=33] 12.19 (1.29) [9.65-14.74] 0.89 (0.002) [0.88-0.89] 0.88 (0.002) [0.87-0.88] HC [n=144 ] 15.30 (0.61) [14.09-16.51] 0.89 (0.001) [0.89-0.89] 0.88 (0.001) [0.88-0.88] SCZ spect vs. HC est=-3.11 se=1.43 p=0.03 Cohen’s d=0.42 Hedges´g=0.42 est=-1.87e-04 se=2.32e-03 p=0.94 Cohen’s d=0.02 Hedges´g=0.02 est=7.20e-04 se=2.34e-03 p=0.76 Cohen’s d=0.06 Hedges´g=0.06 Note: Table 2 shows mean N100 amplitude, T1w/T2w-ratio in AC1, primary auditory cortex and in AC2, secondary auditory cortex in SCZ spect , patients with schizophrenia spectrum disorder, in HC, healthy controls. Estimated marginal means were calculated using ANCOVA, where N100 amplitude, T1w/T2w-ratio in AC1 or T1w/T2w-ratio in AC2 were set as dependent variables with age, sex and diagnosis as independent variables . Estimated marginal means are provided with SE (standard error of the mean) and 95% CI, confidence interval. In addition, Table 2 shows differences in means between SCZ spect and HC. Est, estimate; p, p-value; *, significant p-value (p<0.017). N100 amplitude nominally smaller in SCZ spect compared to HC. Association between N100 amplitude and T1w/T2w-ratio in AC1/AC2 in SCZ spect and HC We found no significant association between N100 amplitude and T1w/T2w-ratio in AC1/AC2 in SCZ spect or in HC (Figure 4). Results from the regression models with interaction terms (diagnosis×T1w/T2w-ratio) indicate that the associations between N100 amplitude and T1w/T2w-ratio in AC1/AC2 did not differ between SCZ spect and HC (AC1: estimate (est)=132.26, standard error (se)=139.63, p-value (p)=0.34; AC2: est=144.76, se=124.74, p=0.25). Mean N100 amplitude, T1w/T2w-ratio in AC1 and T1w/T2w-ratio in AC2 in female/male SCZ spect and HC Estimated marginal means and differences in means between female SCZ spect and female HC and between male SCZ spect and male HC are provided in Table 3. Of interest, N100 amplitude was significantly smaller in male SCZ spect compared to male HC (est=4.30, se=1.63, p=0.01). Table 3 Mean N100 amplitude, T1w/T2w-ratio in AC1 and AC2 in female/male SCZ spect and HC N100 amplitude (microvolts) Mean (SE) [95% CI] AC1 T1w/T2w-ratio Mean (SE) [95% CI] AC2 T1w/T2w-ratio Mean (SE) [95% CI] SCZ spect F [n=16] 15.40 (2.11) [11.21-19.60] 0.89 (0.003) [0.88-0.89] 0.87 (0.003) [0.87-0.88] HC F [n=70] 16.53 (1.01) [14.53-18.54] 0.89 (0.001) [0.89-0.89] 0.88 (0.001) [0.88-0.88] SCZ spect M [n=17] 9.62 (1.46) [6.72-12.53] 0.89 (0.003) [0.88-0.90] 0.88 (0.003) [0.88-0.89] HC M [n=74] 13.92 (0.67) [12.56-15.29] 0.89 (0.001) [0.88-0.89] 0.88 (0.001) [0.87-0.88] SCZ spect F vs. HC F est=-1.13 se=2.34 p=0.63 Cohen’s d=0.13 Hedges´g=0.13 est=-0.01 se=0.003 p=0.10 Cohen’s d=0.47 Hedges´g=0.47 est=-5.31e-03 se=3.22e-03 p=0.10 Cohen’s d=0.47 Hedges´g=0.46 SCZ spect M vs. HC M est=-4.30 se=1.63 p=0.010* Cohen’s d=0.72 Hedges´g=0.73 est=0.004 se=0.003 p=0.21 Cohen’s d=0.65 Hedges´g=0.66 est=0.01 se=0.003 p=0.09 Cohen’s d=0.47 Hedges´g=0.48 Note: Table 3 shows mean N100 amplitude, mean T1w/T2w-ratio in AC1, primary auditory cortex and in AC2, secondary auditory cortex in SCZ spect F, female patients with schizophrenia spectrum disorder, in F HC, female healthy controls, in SCZ spect M, male SCZ spect and in M HC, male HC. Estimated marginal means were calculated using ANCOVA, where N100 amplitude, T1w/T2w-ratio in AC1 or T1w/T2w-ratio in AC2 were set as dependent variables with age and diagnosis as independent variables . Estimated marginal means are provided with SE (standard error of the mean) and 95% CI, confidence interval. In addition, Table 3 shows differences in means between female SCZ spect and female HC and between male SCZ spect and male HC. Est, estimate; p, p-value; *, significant p-value (p<0.017). N100 amplitude was significantly smaller in male SCZ spect compared to male HC. Association between N100 amplitude and T1w/T2w-ratio in AC1/AC2 in female/male SCZ spect and HC We found no significant association between N100 amplitude and T1w/T2w-ratio in AC1 or in AC2 in female or male SCZ spect (Figure 5.1.) or in female or male HC (Figure 5.2.) The associations between N100 amplitude and T1w/T2w-ratio in AC1/AC2 did not differ between sex (AC1: est=91.98, se=96.04, p=0.34; AC2: est=-59.05, se=95.87, p=0.92). In addition to our main results, of interest, we found no difference in T1w/T2w-ratios in the left or right AC1 or AC2 between SCZ spect and HC (Supplementary analyses 1). N100 amplitude was not associated with T1w/Tw2-ratios in the left or right AC1/AC2 in any groups (Supplementary analyses 2). Further, N100 latency did not differ between SCZ spect and HC and was not associated with T1w/T2w-ratio in AC1/AC2 in any groups (Supplementary analyses 3). In the combined sample of SCZ spect and HC, sex explained 4.5%, while age explained 2.7% of variance in N100 amplitude. In SCZ spect only, sex explained 13.67%, while age explained 9.91% of the variance in N100 amplitude. In HC only, sex explained 3.17 % and age explained 1.62% of variance in N100 amplitude (Supplementary analyses 4). Further, N100 amplitude was nominally reduced in male SCZ spect compared to female SCZ spect (p=0.03), in male HC compared to female HC (p=0.03) and significantly reduced in the combined sample of males (patients and controls) compared to females (patients and controls) (p=0.004) (Supplementary analyses 6). We found reduced T1w/T2w-ratio in the AC2 in female SCZ spect compared to male SCZ spect (p=0.01) and reduced N100 amplitude in the combined sample of male SCZ spect and HC compared to the combined sample of female SCZ spect and HC (p=0.004) (Supplementary analyses 6). We did not find any significant difference in N100 amplitude and T1w/T2w-ratio in AC1 or AC2 between AH+ or AH, and the associations did not differ between AH+ and AH- (Supplementary analyses 7). Further, when comparing means between SCZ spect and HC prior to excluding older HC from the sample, SCZ spect had significantly smaller N100 amplitude compared to HC (p=0.017) (Supplementary analyses 8.1.). When comparing means between SCZ spect and HC after stricter age-matching than in our main analysis, we found no significant difference in N100 amplitude or in T1w/T2w-ratio in AC1/AC2 between SCZ spect and HC (Supplementary analyses 8.2.). Further, antipsychotic use explained 2.25% of variance in N100 amplitude, 6.60% of variance in T1w/T2w-ratio in AC1 and 4.58% of variance in T1w/T2w-ratio in AC2 (Supplementary analyses 9.2.). Total PANSS score explained 2.7% of variance in N100 amplitude, 10.12% of variance in T1w/T2w-ratio in AC1 and 10.54% of variance in T1w/T2w-ratio in AC2 (Supplementary analyses 10.). Discussion The current study yielded three main findings. First, N100 amplitude was significantly reduced in male SCZ spect compared to male HC and nominally reduced in the combined sample of SCZ spect compared to the combined sample of HC. Second, T1w/T2w-ratio in AC1/AC2 did not differ between any groups. Finally, we did not find any significant association between N100 amplitude and T1w/T2w-ratio in the AC1 or in AC2. To our knowledge, this is the first published report showing reduced N100 amplitude in male SCZ spect compared to male HC 53 . While we at this point can only speculate why N100 amplitude was reduced in males with SCZ spect , but not in females with SCZ spect , the neuroprotective abilities of estrogen may play a role 74 . Of interest, our supplementary analyses revealed reduced N100 amplitude in the combined sample of male patients and controls compared to the combined sample of female patients and controls (Supplementary Table 6). These findings are in accordance with previous reports of sex differences in auditory functioning in healthy individuals. Females have larger auditory brainstem response 75–77 and larger P300 amplitude, indicating enhanced auditory function, compared to males 49 . Further, females are more sensitive to high frequency sounds 78 while males have a superior spatial auditory perception 79–81 . In females the AC1 is more sensitive to noise compared to males 82 . Together, these findings indicate sex differences in auditory function and estrogen may play a role. Estrogen is believed to protect the auditory system from noise and age-related damage and to optimize auditory processing 83 . Sex differences in auditory function are already present in infants 84,85 , indicating that exposure to sex steroids’ metabolites during prenatal development may lead to fundamental sex differences in auditory function 86 . Further, auditory function changes during the menstrual cycle 87–89 and during pregnancy, a period when estrogen (and progesterone) levels rise continuously until giving birth 90,91 . Peri- and postmenopausal women have diminished auditory function 92 and hormone-replacement therapy may reverse this decline 93,94 . Further females with Turner´s syndrome, a disorder characterized by estrogen deficiency, have increased rate of hearing decline 83 and auditory pathology 95 . Together, these findings indicate that estrogen has a neuroprotective role in auditory function 96 . The neuroprotective effect of estrogen is believed to be partly mediated through its interaction with brain-derived neurotrophic factor (BDNF), gamma-aminobutyric acid (GABA), norepinephrine 83,97 and through enhancing myelination 46,98,99 . Women with MS have fewer MS relapses during pregnancy, suggesting a neuroprotective effect of estrogen through promoting myelination 100 . More research is needed to fully understand the effect of sex steroids and myelination on auditory function in humans 83 . In addition, the relationship between sex steroids and N100 amplitude remains elusive. The effect of sex steroids on auditory function in SCZ spect remain unknown. However, animal models of SCZ spect show that estrogen plays a neuroprotective role in auditory function when interacting with BDNF, 101 . Further, sex differences in dopamine 102 and GABA 103 , neurotransmitters believed to have implications for generating post-synaptic potentials 104–106 which are important for auditory function, are reported in SCZ spect .. Thus, sex differences in these neurotransmitters may also be involved in the current findings of reduced N100 amplitude in males with SCZ spect . Understanding the relationship between sex steroids and N100 amplitude in SCZ spect may provide insight into new treatment targets. Animal models of SCZ spect show evidence suggesting that estrogen may be protective of the disorder through its interaction with BDNF and thus that estrogen–BDNF interactions may be new treatment targets 101 . The N100 amplitude may help us understand basic elemental mechanisms of brain function in SCZ spect . In a previous study, we found positive associations between AC thickness and N100 amplitude in SCZ spect , suggesting that a common neural substrate may underlie AC thickness and N100 amplitude alterations 61 . Based on these previous findings, as well as on a growing literature indicating myelination abnormalities in SCZ spect 107–114 , we here aimed to examine whether myelination in AC may play a role in this association. Myelination plays an important role in spike synchrony 115 . Thus, impaired myelination of pyramidal neurons in the AC could lead to abnormal neural synchrony and altered auditory processing, reflected by reduced N100 amplitude in SCZ spect 16,116 . Based on the assumption of altered myelination and altered synchronization of auditory pyramidal neurons in SCZ spect , we expected to find reduced N100 amplitude and decreased T1w/T2w-ratio in AC in SCZ spect and an association between reduced N100 amplitude and decreased T1w/T2w-ratio. However, in the current study N100 amplitude and T1w/T2w-ratio did not differ significantly between patients and controls and N100 amplitude was not associated with T1w/T2w-ratio in any groups. Thus, our findings did not support the hypothesis that altered myelination in the AC1/AC2, indexed by T1w/T2w-ratio, underlies N100 abnormalities in SCZ spect . However, it has been questioned to what degree T1w/T2w-ratio measures myelin. In one combined MRI and post-mortem study of patients with MS, the T1w/T2w-ratio correlated with dendritic density rather than myelin density 42 . Furthermore, while a high spatial correlation with cortical myelination was demonstrated by Glasser et al. (2014) 117 , recent studies have reported lower correlations with indices of myelin in white matter 118,119 , which shows that the T1w/T2w-ratio is a complex signal and not a quantitative marker of myelin content only. While the current findings point towards a lack of association between N100 amplitude and T1w/T2w-ratio in SCZ spect , we cannot exclude altered myelination in the AC as a neural substrate for N100 amplitude reduction as previously reported in these disorders. To fully understand how myelination in the AC may relate to N100 amplitude in SCZ spect , we need more precise measures of intracortical myelin. In theory, although speculative, another way to investigate the relationship between N100 amplitude and myelination in the AC may be combining intracortical EEG examinations with postmortem examination of myelin content in the AC. However, this method is hampered by ethical and technical challenges. Therefore, a combination of EEG and MRI measures acquired in vivo is more feasible. Other factors than altered myelination, indexed by T1w/T2w-ratio, may explain reduced N100 amplitude in SCZ spect . At this point we can only speculate what neural substrate may underly reduced N100 amplitude and thus altered function of AC pyramidal cells in SCZ spect . Altered synaptic pruning 120,121 resulting in reduced dendritic spine density on cortical pyramidal neurons 122,123 , is part of the pathogenesis of SCZ spect . Reduced dendritic spine density on AC pyramidal cells (and interneurons) may result in desynchronized firing, a decreased summation of postsynaptic potentials and thus in reduced N100 amplitude in SCZ spect 116,124 . Further, excessive synaptic pruning in the AC in SCZ spect may lead to impaired neural communication in cortical areas involved in auditory processing and may result in auditory hallucinations 125–127 . Of note, these two alternative potential mechanisms are consistent with our previous finding of an association between AC cortical thickness and N100 amplitude in SCZ spect 61 . While the current study focused on cortical structures, deeper subcortical white matter may be associated with N100 amplitude. Few studies have investigated the effect of APs on N100 amplitude and findings are inconclusive 128–130 . APs commonly used to treat SCZ spect have high affinity to the dopamine D2 receptor and to the 5-hydroxytryptamine 2 A receptor 131 . Thus, APs may influence N100 amplitude either directly by having effect on neural generators of the N100 or indirectly by decreasing symptoms in SCZ spect 128,132 . Studies investigating correlations between the dose of APs and N100 amplitude are inconclusive 133,134 . Further, one study has shown no effect of APs on the gray/white-matter contrast along the cortical surface 135 . To conclude, longitudinal studies investigating N100 amplitude and myelination in individuals with SCZ spect before and after starting on APs are needed to untangle the exact effect of APs on N100 amplitude and myelination. Some limitations should be considered when interpreting the current findings. As mentioned above, while the T1w/T2w-ratio is spatially correlated with myelination of the cortex, it is not a direct measure of myelin content. Second, the small sample of SCZ spect is an issue, although the study was hypothesis-driven and focusing on specific regions of interest, limiting the number of tests. Further, the way that we generated AEPs, using a small number of trials instead of what is typically recommended for AEPs is unusual. However, after visual inspection of AEPs, we found that the relatively strong stimulus intensity and the long ISI did elicit robust and large-amplitude AEPs as described by others 68 . Strengths of this study include the use of multimodal imaging (EEG and MRI), a sample of clinically well characterized participants, rigorous quality control and assessment of sex differences. In conclusion, our results are consistent with previous findings of reduced N100 amplitude in SCZ spect although the finding was restricted to males only. We did not find altered T1w-T2w-ratio within AC in SCZ spect compared to HC and found no associations between the N100 amplitude and T1w-T2w-ratio. More precise estimates of intracortical myelin in the AC and larger patient samples are needed to disentangle whether altered myelination explains N100 amplitude reduction in SCZ spect . Declarations Acknowledgments This work was supported by the Research Council of Norway (223273, 274359, 249795, 248238), the South – Eastern Norway Regional Health Authority (2014097, 2015044, 2015073, 2017097, 2018037, 2018076, 2019104), the Norwegian Extra Foundation for Health and Rehabilitation (2015/FO5146), the European Research Council under the European Union's Horizon 2020 research and Innovation program (ERC StG 802998), the Ebbe Frøland foundation, and a research grant from Mrs. Throne-Holst. Conflict of interest T.E. is a consultant to BrainWaveBank and Sunovion and received speaker’s honoraria from Lundbeck and Janssen Cilag. O.A.A. is a consultant to cortechs.ai and received speaker’s honoraria from Lundbeck, Janssen, Sunovion. I.A. has received speaker’s honoraria from Lundbeck. The other authors report no conflict of interest. Data and Code Availability Statement MRI and EEG data used in the following study was collected at our research center, NORMENT, Oslo, Norway, as part of the TOP study. The data was collected between 2015 and 2019. The MRI and EEG data is currently not openly available due to ethical and privacy issues of clinical data. The study was approved by the Regional Committees for Medical and Health Research Ethics of South – Eastern Norway, and all participants provided written informed consent. References Saha, S., Chant, D., Welham, J. & McGrath, J. A systematic review of the prevalence of schizophrenia. PLoS Med 2, e141, doi: 10.1371/journal.pmed.0020141 (2005). Kompus, K. et al. The role of the primary auditory cortex in the neural mechanism of auditory verbal hallucinations. Front Hum Neurosci 7, 144, doi: 10.3389/fnhum.2013.00144 (2013). Parker, E. M. & Sweet, R. A. Stereological Assessments of Neuronal Pathology in Auditory Cortex in Schizophrenia. Front Neuroanat 11, 131, doi: 10.3389/fnana.2017.00131 (2017). Rosburg, T., Boutros, N. N. & Ford, J. M. Reduced auditory evoked potential component N100 in schizophrenia–a critical review. Psychiatry Res 161, 259–274, doi: 10.1016/j.psychres.2008.03.017 (2008). Salisbury, D. F., Collins, K. C. & McCarley, R. W. Reductions in the N1 and P2 auditory event-related potentials in first-hospitalized and chronic schizophrenia. Schizophrenia bulletin 36, 991–1000, doi: 10.1093/schbul/sbp003 (2010). Foxe, J. J. et al. The N1 auditory evoked potential component as an endophenotype for schizophrenia: high-density electrical mapping in clinically unaffected first-degree relatives, first-episode, and chronic schizophrenia patients. European Archives of Psychiatry and Clinical Neuroscience 261, 331–339, doi: 10.1007/s00406-010-0176-0 (2011). Wang, B., Zartaloudi, E., Linden, J. F. & Bramon, E. Neurophysiology in psychosis: The quest for disease biomarkers. Transl Psychiatry 12, 100, doi: 10.1038/s41398-022-01860-x (2022). Shen, C. L. et al. P50, N100, and P200 Auditory Sensory Gating Deficits in Schizophrenia Patients. Front Psychiatry 11, 868, doi: 10.3389/fpsyt.2020.00868 (2020). Pantev, C. et al. Specific tonotopic organizations of different areas of the human auditory cortex revealed by simultaneous magnetic and electric recordings. Electroencephalogr Clin Neurophysiol 94, 26–40, doi: 10.1016/0013-4694(94)00209-4 (1995). Luck, S. J. An introduction to the event-related potential technique . Second edition. edn, (The MIT Press, 2014). Haroutunian, V. et al. Myelination, oligodendrocytes, and serious mental illness. Glia 62, 1856–1877, doi: https://doi.org/10.1002/glia.22716 (2014). Uhlhaas, P. J. & Singer, W. Abnormal neural oscillations and synchrony in schizophrenia. Nature Reviews Neuroscience 11, 100–113, doi: 10.1038/nrn2774 (2010). Bartzokis, G. Schizophrenia: Breakdown in the Well-regulated Lifelong Process of Brain Development and Maturation. Neuropsychopharmacology 27, 672–683, doi: 10.1016/S0893-133X(02)00364-0 (2002). Balz, J. et al. Beta/Gamma Oscillations and Event-Related Potentials Indicate Aberrant Multisensory Processing in Schizophrenia. Frontiers in Psychology 7, doi: 10.3389/fpsyg.2016.01896 (2016). Haenschel, C. et al. Cortical Oscillatory Activity Is Critical for Working Memory as Revealed by Deficits in Early-Onset Schizophrenia. The Journal of Neuroscience 29, 9481, doi: 10.1523/JNEUROSCI.1428-09.2009 (2009). Whitford, T. J., Ford, J. M., Mathalon, D. H., Kubicki, M. & Shenton, M. E. Schizophrenia, myelination, and delayed corollary discharges: a hypothesis. Schizophrenia bulletin 38, 486–494, doi: 10.1093/schbul/sbq105 (2012). Pajevic, S., Basser, P. J. & Fields, R. D. Role of myelin plasticity in oscillations and synchrony of neuronal activity. Neuroscience 276, 135–147, doi: 10.1016/j.neuroscience.2013.11.007 (2014). Fries, P. Rhythms for Cognition: Communication through Coherence. Neuron 88, 220–235, doi: 10.1016/j.neuron.2015.09.034 (2015). Mishra, R. K., Kim, S., Guzman, S. J. & Jonas, P. Symmetric spike timing-dependent plasticity at CA3–CA3 synapses optimizes storage and recall in autoassociative networks. Nature Communications 7, 11552, doi: 10.1038/ncomms11552 https://www.nature.com/articles/ncomms11552#supplementary-information (2016). Eggermont, J. J. On the rate of maturation of sensory evoked potentials. Electroencephalogr Clin Neurophysiol 70, 293–305, doi: 10.1016/0013-4694(88)90048-x (1988). Westlye, L. T., Walhovd, K. B., Bjørnerud, A., Due-Tønnessen, P. & Fjell, A. M. Error-related negativity is mediated by fractional anisotropy in the posterior cingulate gyrus–a study combining diffusion tensor imaging and electrophysiology in healthy adults. Cereb Cortex 19, 293–304, doi: 10.1093/cercor/bhn084 (2009). Alshuaib, W. B. Progression of visual evoked potential abnormalities in multiple sclerosis and optic neuritis. Electromyogr Clin Neurophysiol 40, 243–252 (2000). Kiiski, H. S. M. et al. Delayed P100-Like Latencies in Multiple Sclerosis: A Preliminary Investigation Using Visual Evoked Spread Spectrum Analysis. PloS one 11, e0146084-e0146084, doi: 10.1371/journal.pone.0146084 (2016). Agartz, I., Andersson, J. L. & Skare, S. Abnormal brain white matter in schizophrenia: a diffusion tensor imaging study. Neuroreport 12, 2251–2254, doi: 10.1097/00001756-200107200-00041 (2001). Szeszko, P. R. et al. White Matter Abnormalities in First-Episode Schizophrenia or Schizoaffective Disorder: A Diffusion Tensor Imaging Study. American Journal of Psychiatry 162, 602–605, doi: 10.1176/appi.ajp.162.3.602 (2005). Wei, W. et al. Structural Covariance of Depth-Dependent Intracortical Myelination in the Human Brain and Its Application to Drug-Naïve Schizophrenia: A T1w/T2w MRI Study. Cerebral Cortex 32, 2373–2384, doi: 10.1093/cercor/bhab337 (2022). Kelly, S. et al. Widespread white matter microstructural differences in schizophrenia across 4322 individuals: results from the ENIGMA Schizophrenia DTI Working Group. Mol Psychiatry 23, 1261–1269, doi: 10.1038/mp.2017.170 (2018). Jorgensen, K. N. et al. Increased MRI-based cortical grey/white-matter contrast in sensory and motor regions in schizophrenia and bipolar disorder. Psychol Med 46, 1971–1985, doi: 10.1017/s0033291716000593 (2016). Leitman, D. I. et al. The neural substrates of impaired prosodic detection in schizophrenia and its sensorial antecedents. Am J Psychiatry 164, 474–482, doi: 10.1176/ajp.2007.164.3.474 (2007). Hubl, D. et al. Pathways That Make Voices: White Matter Changes in Auditory Hallucinations. Archives of General Psychiatry 61, 658–668, doi: 10.1001/archpsyc.61.7.658 (2004). Knöchel, C. et al. Interhemispheric hypoconnectivity in schizophrenia: Fiber integrity and volume differences of the corpus callosum in patients and unaffected relatives. Neuroimage 59, 926–934, doi: https://doi.org/10.1016/j.neuroimage.2011.07.088 (2012). Mulert, C. et al. Hearing voices: A role of interhemispheric auditory connectivity? The World Journal of Biological Psychiatry 13, 153–158, doi: 10.3109/15622975.2011.570789 (2012). Wigand, M. et al. Auditory verbal hallucinations and the interhemispheric auditory pathway in chronic schizophrenia. The World Journal of Biological Psychiatry 16, 31–44, doi: 10.3109/15622975.2014.948063 (2015). Nerland, S. et al. Multisite reproducibility and test-retest reliability of the T1w/T2w-ratio: A comparison of processing methods. Neuroimage 245, 118709, doi: https://doi.org/10.1016/j.neuroimage.2021.118709 (2021). Uddin, M. N., Figley, T. D., Solar, K. G., Shatil, A. S. & Figley, C. R. Comparisons between multi-component myelin water fraction, T1w/T2w ratio, and diffusion tensor imaging measures in healthy human brain structures. Scientific Reports 9, 2500, doi: 10.1038/s41598-019-39199-x (2019). Shams, Z., Norris, D. G. & Marques, J. P. A comparison of in vivo MRI based cortical myelin mapping using T1w/T2w and R1 mapping at 3T. PLoS One 14, e0218089, doi: 10.1371/journal.pone.0218089 (2019). The Journal of Neuroscience 31, 11597, doi:10.1523/JNEUROSCI.2180-11.2011 (2011). Nieuwenhuys, R. & Broere, C. A map of the human neocortex showing the estimated overall myelin content of the individual architectonic areas based on the studies of Adolf Hopf. Brain Structure and Function 222, doi: 10.1007/s00429-016-1228-7 (2017). Eickhoff, S. et al. High-resolution MRI reflects myeloarchitecture and cytoarchitecture of human cerebral cortex. Hum Brain Mapp 24, 206–215, doi: 10.1002/hbm.20082 (2005). Beer, A. et al. Tissue damage within normal appearing white matter in early multiple sclerosis: assessment by the ratio of T1- and T2-weighted MR image intensity. J Neurol 263, 1495–1502, doi: 10.1007/s00415-016-8156-6 (2016). Cooper, G. et al. Standardization of T1w/T2w Ratio Improves Detection of Tissue Damage in Multiple Sclerosis. Front Neurol 10, 334, doi: 10.3389/fneur.2019.00334 (2019). Righart, R. et al. Cortical pathology in multiple sclerosis detected by the T1/T2-weighted ratio from routine magnetic resonance imaging. Ann Neurol 82, 519–529, doi: 10.1002/ana.25020 (2017). Nakamura, K., Chen, J. T., Ontaneda, D., Fox, R. J. & Trapp, B. D. T1-/T2-weighted ratio differs in demyelinated cortex in multiple sclerosis. Annals of Neurology 82, 635–639, doi: https://doi.org/10.1002/ana.25019 (2017). Iwatani, J. et al. Use of T1-weighted/T2-weighted magnetic resonance ratio images to elucidate changes in the schizophrenic brain. Brain and Behavior 5, e00399, doi: https://doi.org/10.1002/brb3.399 (2015). Wei, W. et al. Depth-dependent abnormal cortical myelination in first-episode treatment-naïve schizophrenia. Human brain mapping 41, 2782–2793, doi: 10.1002/hbm.24977 (2020). Long, P., Wan, G., Roberts, M. T. & Corfas, G. Myelin development, plasticity, and pathology in the auditory system. Dev Neurobiol 78, 80–92, doi: 10.1002/dneu.22538 (2018). Riecher-Rössler, A., Butler, S. & Kulkarni, J. Sex and gender differences in schizophrenic psychoses-a critical review. Arch Womens Ment Health 21, 627–648, doi: 10.1007/s00737-018-0847-9 (2018). Abel, K. M., Drake, R. & Goldstein, J. M. Sex differences in schizophrenia. Int Rev Psychiatry 22, 417–428, doi: 10.3109/09540261.2010.515205 (2010). Melynyte, S., Wang, G. Y. & Griskova-Bulanova, I. Gender effects on auditory P300: A systematic review. Int J Psychophysiol 133, 55–65, doi: 10.1016/j.ijpsycho.2018.08.009 (2018). Pentz, A. B. et al. Mismatch negativity in schizophrenia spectrum and bipolar disorders: Group and sex differences and associations with symptom severity. Schizophr Res 261, 80–93, doi: https://doi.org/10.1016/j.schres.2023.09.012 (2023). Higashima, M. et al. Neuropsychological correlates of an attention-related negative component elicited in an auditory oddball paradigm in schizophrenia. Neuropsychobiology 51, 177–182, doi: 10.1159/000085592 (2005). Sumich, A. et al. N100 and P300 amplitude to Go and No–Go variants of the auditory oddball in siblings discordant for schizophrenia. Schizophr Res 98, 265–277, doi: https://doi.org/10.1016/j.schres.2007.09.018 (2008). Riel, H., Lee, J. B., Fisher, D. J. & Tibbo, P. G. Sex differences in event-related potential (ERP) waveforms of primary psychotic disorders: A systematic review. Int J Psychophysiol 145, 119–124, doi: 10.1016/j.ijpsycho.2019.02.006 (2019). Brown, K. J., Gonsalvez, C. J., Harris, A. W. F., Williams, L. M. & Gordon, E. Target and non-target ERP disturbances in first episode vs. chronic schizophrenia. Clinical Neurophysiology 113, 1754–1763, doi: https://doi.org/10.1016/S1388-2457(02)00290-0 (2002). Force, R. B., Venables, N. C. & Sponheim, S. R. An auditory processing abnormality specific to liability for schizophrenia. Schizophr Res 103, 298–310, doi: 10.1016/j.schres.2008.04.038 (2008). Spencer, K. M. et al. Abnormal Neural Synchrony in Schizophrenia. The Journal of Neuroscience 23, 7407, doi: 10.1523/JNEUROSCI.23-19-07407.2003 (2003). Barendse, M. E. A. et al. Sex and pubertal influences on the neurodevelopmental underpinnings of schizophrenia: A case for longitudinal research on adolescents. Schizophr Res 252, 231–241, doi: 10.1016/j.schres.2022.12.011 (2023). Owens, S. J., Murphy, C. E., Purves-Tyson, T. D., Weickert, T. W. & Shannon Weickert, C. Considering the role of adolescent sex steroids in schizophrenia. Journal of Neuroendocrinology 30, e12538, doi: https://doi.org/10.1111/jne.12538 (2018). Hoekstra, S. et al. Sex differences in antipsychotic efficacy and side effects in schizophrenia spectrum disorder: results from the BeSt InTro study. NPJ Schizophr 7, 39, doi: 10.1038/s41537-021-00170-3 (2021). Sommer, I. E., Tiihonen, J., van Mourik, A., Tanskanen, A. & Taipale, H. The clinical course of schizophrenia in women and men—a nation-wide cohort study. npj Schizophrenia 6, 12, doi: 10.1038/s41537-020-0102-z (2020). Slapø, N. B. et al. Auditory Cortex Thickness Is Associated With N100 Amplitude in Schizophrenia Spectrum Disorders. Schizophrenia Bulletin Open 4, sgad015, doi: 10.1093/schizbullopen/sgad015 (2023). Spitzer, R. L., Williams, J. B., Gibbon, M. & First, M. B. The Structured Clinical Interview for DSM-III-R (SCID). I: History, rationale, and description. Arch Gen Psychiatry 49, 624–629, doi: 10.1001/archpsyc.1992.01820080032005 (1992). Pedersen, G., Hagtvet, K. & Karterud, S. Generalizability studies of the Global Assessment of Functioning-Split version. Comprehensive psychiatry 48, 88–94, doi: 10.1016/j.comppsych.2006.03.008 (2007). Kay, S. R., Fiszbein, A. & Opler, L. A. The Positive and Negative Syndrome Scale (PANSS) for Schizophrenia. Schizophrenia Bulletin 13, 261–276, doi: 10.1093/schbul/13.2.261 (1987). Fischl, B. FreeSurfer. Neuroimage 62, 774–781, doi: https://doi.org/10.1016/j.neuroimage.2012.01.021 (2012). Shinohara, R. T. et al. Statistical normalization techniques for magnetic resonance imaging. NeuroImage. Clinical 6, 9–19, doi: 10.1016/j.nicl.2014.08.008 (2014). Destrieux, C., Fischl, B., Dale, A. & Halgren, E. Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature. Neuroimage 53, 1–15, doi: https://doi.org/10.1016/j.neuroimage.2010.06.010 (2010). Pereira, D. R. et al. Effects of inter-stimulus interval (ISI) duration on the N1 and P2 components of the auditory event-related potential. Int J Psychophysiol 94, 311–318, doi: 10.1016/j.ijpsycho.2014.09.012 (2014). Delorme, A. & Makeig, S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Methods 134, 9–21, doi: 10.1016/j.jneumeth.2003.10.009 (2004). Bigdely-Shamlo, N., Mullen, T., Kothe, C., Su, K. M. & Robbins, K. A. The PREP pipeline: standardized preprocessing for large-scale EEG analysis. Front Neuroinform 9, 16, doi: 10.3389/fninf.2015.00016 (2015). Pion-Tonachini, L., Kreutz-Delgado, K. & Makeig, S. ICLabel: An automated electroencephalographic independent component classifier, dataset, and website. Neuroimage 198, 181–197, doi: https://doi.org/10.1016/j.neuroimage.2019.05.026 (2019). Graham, S. J., Langley, R. W., Bradshaw, C. M. & Szabadi, E. Effects of haloperidol and clozapine on prepulse inhibition of the acoustic startle response and the N1/P2 auditory evoked potential in man. Journal of Psychopharmacology 15, 243–250, doi: 10.1177/026988110101500411 (2001). Thalheimer, W. & Cook, S. How to calculate effect sizes from published research: A simplified methodology. (2009). Brand, B. A., de Boer, J. N. & Sommer, I. E. C. Estrogens in schizophrenia: progress, current challenges and opportunities. Curr Opin Psychiatry 34, 228–237, doi: 10.1097/YCO.0000000000000699 (2021). Dehan, C. P. & Jerger, J. Analysis of gender differences in the auditory brainstem response. Laryngoscope 100, 18–24, doi: 10.1288/00005537-199001000-00005 (1990). McFadden, D., Hsieh, M. D., Garcia-Sierra, A. & Champlin, C. A. Differences by sex, ear, and sexual orientation in the time intervals between successive peaks in auditory evoked potentials. Hearing Research 270, 56–64, doi: https://doi.org/10.1016/j.heares.2010.09.008 (2010). Hall, J. W. New Handbook of Auditory Evoked Responses . (Pearson, 2007). Snihur, A. W. K. & Hampson, E. Sex and ear differences in spontaneous and click-evoked otoacoustic emissions in young adults. Brain and Cognition 77, 40–47, doi: https://doi.org/10.1016/j.bandc.2011.06.004 (2011). Neuhoff, J. G., Planisek, R. & Seifritz, E. Adaptive sex differences in auditory motion perception: looming sounds are special. J Exp Psychol Hum Percept Perform 35, 225–234, doi: 10.1037/a0013159 (2009). Lewald, J. Gender-specific hemispheric asymmetry in auditory space perception. Cognitive Brain Research 19, 92–99, doi: https://doi.org/10.1016/j.cogbrainres.2003.11.005 (2004). Clint, E. K., Sober, E., Garland, T. & Rhodes, J. S. Male Superiority in Spatial Navigation: Adaptation or Side Effect? The Quarterly Review of Biology 87, 289–313, doi: 10.1086/668168 (2012). Ruytjens, L. et al. Functional sex differences in human primary auditory cortex. Eur J Nucl Med Mol Imaging 34, 2073–2081, doi: 10.1007/s00259-007-0517-z (2007). Caras, M. L. Estrogenic modulation of auditory processing: A vertebrate comparison. Frontiers in Neuroendocrinology 34, 285–299, doi: https://doi.org/10.1016/j.yfrne.2013.07.006 (2013). Eldredge, L. & Salamy, A. Functional auditory development in preterm and full term infants. Early Human Development 45, 215–228, doi: https://doi.org/10.1016/0378-3782(96)01732-X (1996). Maurizi, M. et al. Effects of sex on auditory brainstem responses in infancy and early childhood. Scand Audiol 17, 143–146, doi: 10.3109/01050398809042184 (1988). McFadden, D. Sexual orientation and the auditory system. Front Neuroendocrinol 32, 201–213, doi: 10.1016/j.yfrne.2011.02.001 (2011). Stenberg, A. E. et al. Estrogen receptors in the normal adult and developing human inner ear and in Turner’s syndrome. Hearing Research 157, 87–92, doi: https://doi.org/10.1016/S0378-5955(01)00280-5 (2001). Andreyko, J. L. & Jaffe, R. B. Use of a gonadotropin-releasing hormone agonist analogue for treatment of cyclic auditory dysfunction. Obstet Gynecol 74, 506–509 (1989). Souaid, J. P. & Rappaport, J. M. Fluctuating sensorineural hearing loss associated with the menstrual cycle. J Otolaryngol 30, 246–250, doi: 10.2310/7070.2001.20181 (2001). Sennaroglu, G. & Belgin, E. Audiological findings in pregnancy. J Laryngol Otol 115, 617–621, doi: 10.1258/0022215011908603 (2001). Schmidt, P. M., Flores Fda, T., Rossi, A. G. & Silveira, A. F. Hearing and vestibular complaints during pregnancy. Braz J Otorhinolaryngol 76, 29–33, doi: 10.1590/s1808-86942010000100006 (2010). Kim, S. H., Kang, B. M., Chae, H. D. & Kim, C. H. The association between serum estradiol level and hearing sensitivity in postmenopausal women. Obstetrics & Gynecology 99, 726–730, doi: https://doi.org/10.1016/S0029-7844(02)01963-4 (2002). Anderer, P. et al. Effects of hormone replacement therapy on perceptual and cognitive event-related potentials in menopausal insomnia. Psychoneuroendocrinology 28, 419–445, doi: https://doi.org/10.1016/S0306-4530(02)00032-X (2003). Khaliq, F., Tandon, O. P. & Goel, N. Auditory evoked responses in postmenopausal women on hormone replacement therapy. Indian J Physiol Pharmacol 47, 393–399 (2003). Hultcrantz, M. Ear and hearing problems in Turner's syndrome. Acta Otolaryngol 123, 253–257, doi: 10.1080/00016480310001097 (2003). Wharton, J. A. & Church, G. T. Influence of menopause on the auditory brainstem response. Audiology 29, 196–201, doi: 10.3109/00206099009072850 (1990). Maney, D. L., Goode, C. T., Lange, H. S., Sanford, S. E. & Solomon, B. L. Estradiol modulates neural responses to song in a seasonal songbird. Journal of Comparative Neurology 511, 173–186, doi: https://doi.org/10.1002/cne.21830 (2008). Long, K. L. P., Breton, J. M., Barraza, M. K., Perloff, O. S. & Kaufer, D. Hormonal Regulation of Oligodendrogenesis I: Effects across the Lifespan. Biomolecules 11, doi: 10.3390/biom11020283 (2021). Mitchell, T. W. et al. The prevalence of MS in the United States. Neurology 92, e1029, doi: 10.1212/WNL.0000000000007035 (2019). Confavreux, C., Hutchinson, M., Hours, M. M., Cortinovis-Tourniaire, P. & Moreau, T. Rate of Pregnancy-Related Relapse in Multiple Sclerosis. New England Journal of Medicine 339, 285–291, doi: 10.1056/NEJM199807303390501 (1998). Wu, Y. C., Hill, R. A., Gogos, A. & van den Buuse, M. Sex differences and the role of estrogen in animal models of schizophrenia: Interaction with BDNF. Neuroscience 239, 67–83, doi: https://doi.org/10.1016/j.neuroscience.2012.10.024 (2013). Godar, S. C. & Bortolato, M. Gene-sex interactions in schizophrenia: focus on dopamine neurotransmission. Front Behav Neurosci 8, 71, doi: 10.3389/fnbeh.2014.00071 (2014). Bristow, G. C., Bostrom, J. A., Haroutunian, V. & Sodhi, M. S. Sex differences in GABAergic gene expression occur in the anterior cingulate cortex in schizophrenia. Schizophr Res 167, 57–63, doi: 10.1016/j.schres.2015.01.025 (2015). Grothe, B. & Koch, U. Dynamics of binaural processing in the mammalian sound localization pathway–the role of GABA(B) receptors. Hear Res 279, 43–50, doi: 10.1016/j.heares.2011.03.013 (2011). Mayko, Z. M., Roberts, P. D. & Portfors, C. V. Inhibition shapes selectivity to vocalizations in the inferior colliculus of awake mice. Front Neural Circuits 6, 73, doi: 10.3389/fncir.2012.00073 (2012). Rudick, C. N. & Woolley, C. S. Estrogen regulates functional inhibition of hippocampal CA1 pyramidal cells in the adult female rat. J Neurosci 21, 6532–6543, doi: 10.1523/jneurosci.21-17-06532.2001 (2001). Hakak, Y. et al. Genome-wide expression analysis reveals dysregulation of myelination-related genes in chronic schizophrenia. Proc Natl Acad Sci U S A 98, 4746–4751, doi: 10.1073/pnas.081071198 (2001). Vikhreva, O. V., Rakhmanova, V. I., Orlovskaya, D. D. & Uranova, N. A. Ultrastructural alterations of oligodendrocytes in prefrontal white matter in schizophrenia: A post-mortem morphometric study. Schizophr Res 177, 28–36, doi: 10.1016/j.schres.2016.04.023 (2016). Kolomeets, N. S. & Uranova, N. A. Reduced oligodendrocyte density in layer 5 of the prefrontal cortex in schizophrenia. Eur Arch Psychiatry Clin Neurosci 269, 379–386, doi: 10.1007/s00406-018-0888-0 (2019). Kubicki, M. et al. A review of diffusion tensor imaging studies in schizophrenia. J Psychiatr Res 41, 15–30, doi: 10.1016/j.jpsychires.2005.05.005 (2007). Ellison-Wright, I. & Bullmore, E. Meta-analysis of diffusion tensor imaging studies in schizophrenia. Schizophr Res 108, 3–10, doi: 10.1016/j.schres.2008.11.021 (2009). Flynn, S. W. et al. Abnormalities of myelination in schizophrenia detected in vivo with MRI, and post-mortem with analysis of oligodendrocyte proteins. Molecular Psychiatry 8, 811–820, doi: 10.1038/sj.mp.4001337 (2003). Tkachev, D. et al. Oligodendrocyte dysfunction in schizophrenia and bipolar disorder. Lancet 362, 798–805, doi: 10.1016/S0140-6736(03)14289-4 (2003). Uranova, N. A., Vikhreva, O. V., Rachmanova, V. I. & Orlovskaya, D. D. Ultrastructural alterations of myelinated fibers and oligodendrocytes in the prefrontal cortex in schizophrenia: a postmortem morphometric study. Schizophr Res Treatment 2011, 325789–325789, doi: 10.1155/2011/325789 (2011). Lang, E. J. & Rosenbluth, J. Role of Myelination in the Development of a Uniform Olivocerebellar Conduction Time. J Neurophysiol 89, 2259–2270, doi: 10.1152/jn.00922.2002 (2003). Uhlhaas, P. J. & Singer, W. Abnormal neural oscillations and synchrony in schizophrenia. Nat Rev Neurosci 11, 100–113, doi: 10.1038/nrn2774 (2010). Glasser, M. F., Goyal, M. S., Preuss, T. M., Raichle, M. E. & Van Essen, D. C. Trends and properties of human cerebral cortex: correlations with cortical myelin content. Neuroimage 93 Pt 2, 165–175, doi: 10.1016/j.neuroimage.2013.03.060 (2014). Uddin, M. N., Figley, T. D., Solar, K. G., Shatil, A. S. & Figley, C. R. Comparisons between multi-component myelin water fraction, T1w/T2w ratio, and diffusion tensor imaging measures in healthy human brain structures. Sci Rep 9, 2500, doi: 10.1038/s41598-019-39199-x (2019). Sandrone, S. et al. Mapping myelin in white matter with T1-weighted/T2-weighted maps: discrepancy with histology and other myelin MRI measures. Brain Struct Funct 228, 525–535, doi: 10.1007/s00429-022-02600-z (2023). Sellgren, C. M. et al. Increased synapse elimination by microglia in schizophrenia patient-derived models of synaptic pruning. Nat Neurosci 22, 374–385, doi: 10.1038/s41593-018-0334-7 (2019). Paolicelli, R. C. et al. Synaptic pruning by microglia is necessary for normal brain development. Science 333, 1456–1458, doi: 10.1126/science.1202529 (2011). Glausier, J. R. & Lewis, D. A. Dendritic spine pathology in schizophrenia. Neuroscience 251, 90–107, doi: https://doi.org/10.1016/j.neuroscience.2012.04.044 (2013). Glantz, L. A. & Lewis, D. A. Decreased dendritic spine density on prefrontal cortical pyramidal neurons in schizophrenia. Arch Gen Psychiatry 57, 65–73, doi: 10.1001/archpsyc.57.1.65 (2000). Hirano, Y. et al. Auditory Cortex Volume and Gamma Oscillation Abnormalities in Schizophrenia. Clinical EEG and Neuroscience 51, 244–251, doi: 10.1177/1550059420914201 (2020). de la Iglesia-Vaya, M. et al. Abnormal synchrony and effective connectivity in patients with schizophrenia and auditory hallucinations. NeuroImage: Clinical 6, 171–179, doi: https://doi.org/10.1016/j.nicl.2014.08.027 (2014). Ford, J. M., Roach, B. J., Faustman, W. O. & Mathalon, D. H. Synch before you speak: auditory hallucinations in schizophrenia. Am J Psychiatry 164, 458–466, doi: 10.1176/ajp.2007.164.3.458 (2007). Mulert, C., Kirsch, V., Pascual-Marqui, R., McCarley, R. W. & Spencer, K. M. Long-range synchrony of gamma oscillations and auditory hallucination symptoms in schizophrenia. Int J Psychophysiol 79, 55–63, doi:10.1016/j.ijpsycho.2010.08.004 (2011). Rosburg, T. Auditory N100 gating in patients with schizophrenia: A systematic meta-analysis. Clinical Neurophysiology 129, 2099–2111, doi: https://doi.org/10.1016/j.clinph.2018.07.012 (2018). Brockhaus-Dumke, A., Mueller, R., Faigle, U. & Klosterkoetter, J. Sensory gating revisited: Relation between brain oscillations and auditory evoked potentials in schizophrenia. Schizophr Res 99, 238–249, doi: https://doi.org/10.1016/j.schres.2007.10.034 (2008). Mazhari, S., Price, G., Waters, F., Dragović, M. & Jablensky, A. Evidence of abnormalities in mid-latency auditory evoked responses (MLAER) in cognitive subtypes of patients with schizophrenia. Psychiatry Research 187, 317–323, doi: https://doi.org/10.1016/j.psychres.2011.01.003 (2011). Beasley, C. M. et al. Olanzapine versus placebo and haloperidol: Acute phase results of the North American double-blind olanzapine trial. Neuropsychopharmacology 14, 111–123, doi: https://doi.org/10.1016/0893-133X(95)00069-P (1996). Maxwell, C. R. et al. Effects of Chronic Olanzapine and Haloperidol Differ on the Mouse N1 Auditory Evoked Potential. Neuropsychopharmacology 29, 739–746, doi: 10.1038/sj.npp.1300376 (2004). Baribeau-Braun, J., Picton, T. W. & Gosselin, J.-Y. Schizophrenia: A Neurophysiological Evaluation of Abnormal Information Processing. Science 219, 874–876, doi: 10.1126/science.6823555 (1983). Barrett, K., McCallum, W. C. & Pocock, P. V. Brain indicators of altered attention and information processing in schizophrenic patients. Br J Psychiatry 148, 414–420, doi: 10.1192/bjp.148.4.414 (1986). Jørgensen, K. N. et al. Increased MRI-based cortical grey/white-matter contrast in sensory and motor regions in schizophrenia and bipolar disorder. Psychological Medicine 46, 1971–1985, doi: 10.1017/S0033291716000593 (2016). Additional Declarations The authors have declared there is NO conflict of interest to disclose Supplementary Files Suppl.Fig.1.tif Suppl.Fig.2.tif Suppl.Fig.3.tif Suppl.Fig.4.tif Supplements.docx Cite Share Download PDF Status: Published Journal Publication published 17 Jan, 2026 Read the published version in Schizophrenia → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Westlye","email":"","orcid":"https://orcid.org/0000-0001-8644-956X","institution":"University of Oslo","correspondingAuthor":false,"prefix":"","firstName":"Lars","middleName":"T.","lastName":"Westlye","suffix":""},{"id":271362205,"identity":"1ce91be3-039f-408a-a23d-afba52635304","order_by":17,"name":"Nils Eiel Steen","email":"","orcid":"https://orcid.org/0000-0001-6442-1179","institution":"Oslo University Hospital \u0026 University of Oslo","correspondingAuthor":false,"prefix":"","firstName":"Nils","middleName":"Eiel","lastName":"Steen","suffix":""},{"id":271362206,"identity":"32034c32-68e6-47b8-9cad-a63fcced923f","order_by":18,"name":"Linn Norbom","email":"","orcid":"https://orcid.org/0000-0001-7489-2724","institution":"Faculty of Social Sciences","correspondingAuthor":false,"prefix":"","firstName":"Linn","middleName":"","lastName":"Norbom","suffix":""},{"id":271362207,"identity":"1d004d92-5e27-4075-a18c-0f215af02ea4","order_by":19,"name":"Ole Andreassen","email":"","orcid":"https://orcid.org/0000-0002-4461-3568","institution":"Oslo University Hospital \u0026 Institute of Clinical Medicine, University of Oslo","correspondingAuthor":false,"prefix":"","firstName":"Ole","middleName":"","lastName":"Andreassen","suffix":""},{"id":271362208,"identity":"d74e1405-894e-4f57-8a13-fd88cade303e","order_by":20,"name":"Torgeir Moberget","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Torgeir","middleName":"","lastName":"Moberget","suffix":""},{"id":271362209,"identity":"2aefcbab-52bd-4022-adb4-30a1b44f07f5","order_by":21,"name":"Torbjorn Elvsashagen","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Torbjorn","middleName":"","lastName":"Elvsashagen","suffix":""},{"id":271362210,"identity":"ada83eec-d24f-453e-aedc-b637faddd07e","order_by":22,"name":"Erik Jönsson","email":"","orcid":"","institution":"University of Oslo","correspondingAuthor":false,"prefix":"","firstName":"Erik","middleName":"","lastName":"Jönsson","suffix":""}],"badges":[],"createdAt":"2024-01-28 15:30:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3906183/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3906183/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41537-025-00715-w","type":"published","date":"2026-01-17T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":50877217,"identity":"d43a447b-d6a2-4ace-b071-0a6db2420b3a","added_by":"auto","created_at":"2024-02-08 19:18:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":365666,"visible":true,"origin":"","legend":"\u003cp\u003eshows example MRI volumes. In the left column, T1-weighted volumes are shown (upper: coronal view, lower: sagittal view). In the middle column, T2-weighted volumes are shown. In the right column, T1w/T2w-ratio volumes are shown. The cortical surfaces based on FreeSurfer reconstruction are shown in red lines representing the outer cortical surface (i.e., the pial surface) and yellow lines represent the inner cortical surface (i.e., white matter surface)\u003c/p\u003e","description":"","filename":"Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-3906183/v1/5a43f3f1ab121f442c6b13b2.png"},{"id":50877218,"identity":"6a18da83-0db9-4394-bd2f-4e285d5df192","added_by":"auto","created_at":"2024-02-08 19:18:01","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":95989,"visible":true,"origin":"","legend":"\u003cp\u003eAuditory evoked potential (AEP) from 12 randomly drawn SCZ\u003csub\u003espect.\u003c/sub\u003e, patients with schizophrenia spectrum disorders\u003c/p\u003e","description":"","filename":"Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-3906183/v1/1da845144bdbce8da0b72bc6.png"},{"id":50877221,"identity":"6f899f21-a36f-47a6-97af-ba44d53321d7","added_by":"auto","created_at":"2024-02-08 19:18:01","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":147494,"visible":true,"origin":"","legend":"\u003cp\u003eAuditory evoked potential (AEP) from 24 randomly drawn HC, healthy controls.\u003c/p\u003e","description":"","filename":"Fig.3.png","url":"https://assets-eu.researchsquare.com/files/rs-3906183/v1/17d019579d74268fbea262eb.png"},{"id":50877219,"identity":"125ab9ed-063f-40b9-ad12-16b891ca6703","added_by":"auto","created_at":"2024-02-08 19:18:01","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":80101,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA-D\u003c/strong\u003e Association between N100 amplitude and T1w/Tw2-ratio in AC1, primary AC, auditory cortex and in AC2, secondary AC in SCZ\u003csub\u003espect.\u003c/sub\u003e, patients with schizophrenia spectrum disorder \u003cstrong\u003e(A-B)\u003c/strong\u003e and in HC, healthy controls \u003cstrong\u003e(C-D)\u003c/strong\u003e; est, estimate; se, standard error; p, p-value; *, significant p-value (p\u0026lt;0.025) association. N100 amplitude and T1w/Tw2-ratio in AC1/AC2 were set as dependent variables with age and sex as covariates. We found no significant associations between N100 amplitude and T1w/Tw2-ratio in AC1/AC2 in SCZ\u003csub\u003espect \u003c/sub\u003eor in HC.\u003c/p\u003e","description":"","filename":"Fig.4.png","url":"https://assets-eu.researchsquare.com/files/rs-3906183/v1/7f4502e56271923289dbf254.png"},{"id":50877236,"identity":"66f97ab0-513b-4c89-83c4-39fe3382cb0f","added_by":"auto","created_at":"2024-02-08 19:18:02","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":111096,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e5.1. A-D\u003c/strong\u003e\u003cem\u003e \u003c/em\u003eAssociation between N100 amplitude and T1w/Tw2-ratio in AC1, primary AC, auditory cortex and in AC2, secondary AC in female SCZ\u003csub\u003espect\u003c/sub\u003e, patients with schizophrenia spectrum disorder \u003cstrong\u003e(A-B)\u003c/strong\u003e and in male SCZ\u003csub\u003espect\u003c/sub\u003e \u003cstrong\u003e(C-D)\u003c/strong\u003e; est, estimate; se, standard error; p, p-value; *, significant p-value (p\u0026lt;0.025) association. N100 amplitude and T1w/Tw2-ratio in AC1/AC2 were set as dependent variables with age as covariates. We found no significant associations between N100 amplitude and T1w/Tw2-ratio in AC1/AC2 in female or male SCZ\u003csub\u003espect.\u003c/sub\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5.2 A-D\u003c/strong\u003e\u003cem\u003e \u003c/em\u003eAssociation between N100 amplitude and T1w/Tw2-ratio in AC1, primary AC, auditory cortex and in AC2, secondary AC in female HC, healthy controls \u003cstrong\u003e(A-B)\u003c/strong\u003e and in male HC\u003cstrong\u003e (C-D)\u003c/strong\u003e; est, estimate; se, standard error; p, p-value; *, significant p-value (p\u0026lt;0.025) association. N100 amplitude and T1w/Tw2-ratio in AC1/AC2 were set as dependent variables with age as covariates. We found no significant associations between N100 amplitude and T1w/Tw2-ratio in AC1/AC2 in female or male HC\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-3906183/v1/6d479ab30c4d9ceb01819434.png"},{"id":105886546,"identity":"a607845a-1d49-43ea-bce4-8d206db961e9","added_by":"auto","created_at":"2026-04-01 07:29:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2258185,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3906183/v1/2dcddcb7-31c7-4dc2-ba8b-98584a1e0dee.pdf"},{"id":50877238,"identity":"ab236f2a-cf7c-460d-878d-fee60af9903a","added_by":"auto","created_at":"2024-02-08 19:18:02","extension":"tif","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":16002458,"visible":true,"origin":"","legend":"","description":"","filename":"Suppl.Fig.1.tif","url":"https://assets-eu.researchsquare.com/files/rs-3906183/v1/d5336415b1f3f383e69b7d0c.tif"},{"id":50877237,"identity":"3253cb2d-0b72-4f62-b3ae-59f5c7d61f5e","added_by":"auto","created_at":"2024-02-08 19:18:02","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":16002458,"visible":true,"origin":"","legend":"","description":"","filename":"Suppl.Fig.2.tif","url":"https://assets-eu.researchsquare.com/files/rs-3906183/v1/af0705521c170636956a0527.tif"},{"id":50877239,"identity":"6caff4f4-e295-45fa-af57-58bf1a794478","added_by":"auto","created_at":"2024-02-08 19:18:02","extension":"tif","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":16002458,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"Suppl.Fig.3.tif","url":"https://assets-eu.researchsquare.com/files/rs-3906183/v1/36192093823bf1ab552c93fe.tif"},{"id":50877220,"identity":"0af4daf5-4eb1-4479-87d2-fc7d11d5924c","added_by":"auto","created_at":"2024-02-08 19:18:01","extension":"tif","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":2074510,"visible":true,"origin":"","legend":"","description":"","filename":"Suppl.Fig.4.tif","url":"https://assets-eu.researchsquare.com/files/rs-3906183/v1/79e775dbe73d9fb8e94ff64f.tif"},{"id":50877222,"identity":"654f4b08-2e19-48ee-8b5b-8464d6f40ece","added_by":"auto","created_at":"2024-02-08 19:18:01","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":84227,"visible":true,"origin":"","legend":"","description":"","filename":"Supplements.docx","url":"https://assets-eu.researchsquare.com/files/rs-3906183/v1/cd90f048dee9ee9684f9bc7e.docx"}],"financialInterests":"The authors have declared there is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose","formattedTitle":"Relationship between N100 amplitude and T1w/T2w-ratio in the auditory cortex in schizophrenia spectrum disorders","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSchizophrenia spectrum disorders (SCZ\u003csub\u003espect\u003c/sub\u003e) are severe mental disorders affecting approximately 1.0% of the general population \u003csup\u003e1\u003c/sup\u003e. Although the precise neural substrates of SCZ\u003csub\u003espect\u003c/sub\u003e remain elusive, structural magnetic resonance imaging (MRI) studies suggest the involvement of the auditory cortex (AC) \u003csup\u003e2,3\u003c/sup\u003e. At the functional level, electroencephalography (EEG) studies have consistently demonstrated reduced amplitude \u003csup\u003e4\u0026ndash;7\u003c/sup\u003e and delayed latency \u003csup\u003e8\u003c/sup\u003e of the N100 component of the auditory evoked potential (AEP) in SCZ\u003csub\u003espect\u003c/sub\u003e. The N100 amplitude is believed to reflect how pyramidal cells in the AC respond to auditory stimuli \u003csup\u003e9,10\u003c/sup\u003e. While the structural and biological correlates for N100 amplitude reductions in SCZ\u003csub\u003espect\u003c/sub\u003e remain unclear, altered myelination in the AC may play a role given that myelin is essential for fast and synchronized communication between neurons \u003csup\u003e11\u003c/sup\u003e. Thus, altered myelination in the AC in SCZ\u003csub\u003espect\u003c/sub\u003e \u003csup\u003e12,13\u003c/sup\u003e may also partly explain the high prevalence of auditory hallucinations in these disorder \u003csup\u003e12,14\u0026ndash;16\u003c/sup\u003e. Further, myelination directly impacts on key features of brain dynamics in the millisecond range as measured by EEG \u003csup\u003e17\u0026ndash;19\u003c/sup\u003e and previous studies have shown associations between myelin indices and evoked response potentials (ERPs) \u003csup\u003e20,21\u003c/sup\u003e in healthy individuals. Further, individuals with multiple sclerosis (MS), a demyelination brain disorder, have reduced amplitude and delayed latency of the P100 component of the visual evoked potential \u003csup\u003e22,23\u003c/sup\u003e. While the relationship between the amplitude of the N100 component of the AEP and myelination in the AC in healthy individual remains elusive, here we examined the hypothesis that altered myelination in AC may be correlated with reduced N100 amplitude in SCZ\u003csub\u003espect\u003c/sub\u003e.\u003c/p\u003e \u003cp\u003eAltered cortical myelination is associated with a vulnerability towards SCZ\u003csub\u003espect\u003c/sub\u003e \u003csup\u003e24\u0026ndash;28\u003c/sup\u003e. MRI studies using gray matter/white matter contrast (GWC) or diffusion tensor imaging (DTI), suggest altered myelination in auditory regions in SCZ\u003csub\u003espect\u003c/sub\u003e \u003csup\u003e28,29\u003c/sup\u003e. Further, connectivity in auditory fiber bundles is connected to auditory hallucinations in SCZ\u003csub\u003espect\u003c/sub\u003e \u003csup\u003e30\u0026ndash;33\u003c/sup\u003e. The ratio between T1- (T1w) and T2- (T2w) weighted MRI (i.e., the T1w/T2w-ratio) has been used as a proxy for cortical myelin microstructure \u003csup\u003e34\u0026ndash;36\u003c/sup\u003e and has a close spatial correlation with myelin-based histology \u003csup\u003e37\u0026ndash;39\u003c/sup\u003e. Further, patients with MS have reduced T1w/T2w-ratio \u003csup\u003e40,41\u003c/sup\u003e that is associated with tissue damage \u003csup\u003e42,43\u003c/sup\u003e. Together, these studies support the use of T1w/T2w-ratio as a proxy for myelin. While one study found globally reduced T1w/T2w-ratio in SCZ\u003csub\u003espect\u003c/sub\u003e \u003csup\u003e44\u003c/sup\u003e, another study demonstrated reduced T1w/T2w-ratio in specific brain areas only \u003csup\u003e45\u003c/sup\u003e. However, none of these studies included intensity normalization, which has been shown to improve test-retest reliability of the T1w/T2w-ratio \u003csup\u003e34\u003c/sup\u003e. While several lines of evidence suggest altered myelination in the pathogenesis of SCZ\u003csub\u003espect\u003c/sub\u003e \u003csup\u003e30,46\u003c/sup\u003e, whether there is a direct link between myelination and function in the AC in SCZ\u003csub\u003espect\u003c/sub\u003e, remains unknown. To the best of our knowledge, no T1w/T2w-ratio abnormalities in the AC has been reported in SCZ\u003csub\u003espect\u003c/sub\u003e.\u003c/p\u003e \u003cp\u003eUnderstanding the influence of biological sex on AC function and structure in SCZ\u003csub\u003espect\u003c/sub\u003e may provide insight into the neural substrate behind the well-established sex differences in the pathophysiology and treatment response in SCZ\u003csub\u003espect\u003c/sub\u003e \u003csup\u003e47,48\u003c/sup\u003e. While previous studies report sex differences in the ERP- P300 component \u003csup\u003e49\u003c/sup\u003e and in the mismatch negativity \u003csup\u003e50\u003c/sup\u003e in SCZ\u003csub\u003espect\u003c/sub\u003e, studies investigating sex difference in the N100 amplitude are sparse \u003csup\u003e51\u0026ndash;53\u003c/sup\u003e. While previous studies have reported sex difference in brain structure in SCZ\u003csub\u003espect\u003c/sub\u003e \u003csup\u003e48\u003c/sup\u003e to our knowledge, no study has investigated sex difference in T1w/T2w-ratio in the AC in SCZ\u003csub\u003espect\u003c/sub\u003e.\u003c/p\u003e \u003cp\u003eHere we aimed to provide new insight into the biological and structural correlates of N100 amplitude in SCZ\u003csub\u003espect\u003c/sub\u003e and healthy controls (HC) by combining EEG and MRI, two non-invasive neuroimaging methods to study brain function and structure, respectively. To accomplish this, we examined the relationship between the N100 amplitude and the T1w/T2w-ratio in the primary auditory cortex (AC1) and in the secondary auditory cortex (AC2). These relationships are especially intriguing since reduced N100 amplitude is among one of the most consistently observed EEG changes in SCZ\u003csub\u003espect\u003c/sub\u003e \u003csup\u003e4\u0026ndash;7,10,54\u0026ndash;56\u003c/sup\u003e. Given reports of important sex-differences in SCZ\u003csub\u003espect\u003c/sub\u003e pathophysiology \u003csup\u003e48,57\u0026ndash;60\u003c/sup\u003e, we also aimed to assess whether sex has an impact on these relationships.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eParticipants with a DSM-IV diagnosis within the SCZ\u003csub\u003espect\u003c/sub\u003e and HC were included from the ongoing Thematically Organized Psychosis (TOP) research study and partly overlap with the participants included in our previous study \u003csup\u003e61\u003c/sup\u003e. HC were randomly drawn from the national population register within the same catchment area and asked to participate in the study. The study was approved by the Regional Committees for Medical and Health Research Ethics of South-Eastern Norway and conducted in accordance with the Helsinki declaration. Participants provided written informed consent. Participants with a history of head trauma resulting in loss of consciousness, an IQ\u0026thinsp;\u0026lt;\u0026thinsp;70, or somatic or neurological disorders believed to influence brain function, were excluded from the study. In addition, HC with a history of mental disorders and/or severe mental disorders in first degree relatives or a history of alcohol- and substance abuse or dependence were excluded. In total, MRI and EEG data was available for 442 participants (50 SCZ\u003csub\u003espect\u003c/sub\u003e and 392 HC). We excluded participants (7 SCZ\u003csub\u003espect\u003c/sub\u003e and 20 HC) with clinically relevant incidental findings on their MRI scan (cysts\u0026thinsp;\u0026gt;\u0026thinsp;1x1cm, empty sella turcica, greater pituitary gland abnormalities, arterial-venous malformations, multiple sclerosis changes, tumors or infarctions), with poor AEP on visual inspection (10 SCZ\u003csub\u003espect\u003c/sub\u003e and 61 HC) and with a time interval between MRI scanning and EEG recording of more than 12 months (1 HC). Since our healthy controls were significantly older than patients with SCZ\u003csub\u003espect\u003c/sub\u003e, we selected controls that were similar in age with patients and excluded all participants that were older than 54 years. This resulted in the exclusion of 133 HC. The final sample consisted of 177 participants, including 33 individuals with SCZ\u003csub\u003espect\u003c/sub\u003e (schizophrenia [n\u0026thinsp;=\u0026thinsp;21], schizophreniform [n\u0026thinsp;=\u0026thinsp;1] and psychosis not otherwise specified [n\u0026thinsp;=\u0026thinsp;11]) and 144 HC. In this sample, MRI, EEG and clinical investigations were performed between 2015 and 2019 with a median time interval between MRI and EEG examinations of 12 days (0-337 days; interquartile range\u0026thinsp;=\u0026thinsp;32 days).\u003c/p\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003eClinical assessment\u003c/h2\u003e \u003cp\u003eDiagnosis, age of onset, duration of illness (DOI), psychosocial functioning, current symptoms and the use of antipsychotic medication(s) was assessed as described previously \u003csup\u003e61\u003c/sup\u003e. Trained clinical psychologists or physicians diagnosed the patients according to DSM-IV criteria using the Structural clinical interview for DSM-IV (SCID-I) \u003csup\u003e62\u003c/sup\u003e. We defined age of onset as age at first positive psychotic symptoms (verified by SCID-I) and the duration of illness (DOI) as years from age of onset to age at MRI. To assess psychosocial functioning we used the split version of the Global assessment of function (GAF-S and GAF-F) scale \u003csup\u003e63\u003c/sup\u003e. Current symptoms were evaluated using the Positive and negative syndrome scale (PANSS) interview \u003csup\u003e64\u003c/sup\u003e. For each patient, the current dosage of antipsychotic medication(s) was converted into Defined Daily Dose (DDD), where 1 DDD is the assumed average maintenance dose per day for a drug used for its main indication in adults (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.whocc.no/atc_ddd_index/\" target=\"_blank\"\u003ewww.whocc.no/atc_ddd_index/\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.whocc.no/atc_ddd_index/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). In total, 21 patients were using antipsychotic medication, 7 patients were not using antipsychotic medication. Information about medication use was missing for 5 patients.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eMRI processing\u003c/h2\u003e \u003cp\u003eMRI were processed in the recon-all stream of FreeSurfer version 6.0.0 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://surfer.nmr.mgh.harvard.edu\u003c/span\u003e\u003cspan address=\"https://surfer.nmr.mgh.harvard.edu\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e \u003csup\u003e65\u003c/sup\u003e. Briefly, this processing stream include removal of non-brain tissue, Talairach transformation, and intensity non-uniformity correction. Intensity information was used to reconstruct the inner (i.e., the gray/white matter boundary) and outer (i.e., the gray matter/cerebrospinal fluid boundary) surfaces of the cerebral cortex. Quality control and editing was conducted by trained research assistants following standard FreeSurfer procedures. At this stage, no participants were excluded. The T1w/T2w-ratio was computed using an approach previously found to have high test-retest reliability \u003csup\u003e34\u003c/sup\u003e. Briefly, this approach performs post hoc corrections for field inhomogeneities, partial voluming, and the presence of surface outliers, and intensity normalization using WhiteStripe \u003csup\u003e66\u003c/sup\u003e, which uses intensity values in normal-appearing white matter to harmonize T1w/T2w-ratio values. The mean T1w/T2w-ratios were extracted in three bilateral regions of interest in the Destrieux atlas \u003csup\u003e67\u003c/sup\u003e: The anterior transverse temporal gyrus of Heschl (HG), the transverse temporal sulcus (HS) and the temporal plane of the superior temporal gyrus (PT). Cortical labels were visually inspected to ensure correct placement. No subjects were excluded due to poor cortical labelling. For the main analyses, we defined two main regions of interest; the HG, referred to as the AC1 in the manuscript, and the combined HS and PT, referred to as AC2 in the manuscript. The T1w/T2w-ratio was calculated as an area-weighted mean across hemispheres and sub-regions. See \u003cem\u003eSupplementary Note 1\u003c/em\u003e for a discussion around parcellation of the AC and \u003cem\u003eSupplementary Note 2\u003c/em\u003e for details on how T1w/T2w-ratio was calculated. \u003cem\u003eSupplementary Figs.\u0026nbsp;1 and 2\u003c/em\u003e show the AC1 (HG) and AC2\u003c/p\u003e \u003cp\u003e(HS-PT) regions of interest. Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows example T1- and T2-weighted volumes and the T1w/T2w-ratio volumes.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eAuditory evoked potentials obtained from the PPI paradigm\u003c/h2\u003e \u003cp\u003eAEPs were elicited during a prepulse-inhibition (PPI) task and EEG data was acquired and processed as described previously \u003csup\u003e61\u003c/sup\u003e. \u003cem\u003eSupplementary Fig.\u0026nbsp;3\u003c/em\u003e shows the timeline of the entire EEG session, where the PPI-paradigm was presented together with other tasks. During the PPI paradigm, the participants focused on a red dot in the middle of a computer-screen while exposed to a constant background noise at 70 dB for 3-minutes (to allow for habituation) followed by the main PPI experiment. This consisted of five main conditions, with 12 presentations each: 1) Startle-stimuli presented alone (40 ms white noise with near instantaneous rise/fall times presented at 115 dB); 2; startle stimuli preceded 30 ms earlier by weaker prepulse stimuli (20 ms white noise with near instantaneous rise/fall times presented at 85 dB); 3; startle stimuli preceded 60 ms earlier by the weaker prepulse stimuli; Startle stimuli preceded 120 ms earlier by the weaker prepulse; and 5) the weaker prepulse stimuli presented alone. The current paper focuses on AEPs elicited by the prepulse stimulus alone (presented at 85 dB), since this typically does not elicit a muscular startle response. While we thus compute ERPs from relatively few trials, the long average interstimulus interval (ISI: approximately 9 seconds), in combination with the relatively strong stimulus intensity (85 dB), nonetheless elicited robust AEPs \u003csup\u003e68\u003c/sup\u003e. Prior to the EEG examination, hearing was assessed at 20 dB and 40 dB. All participants that were included in the current study were able to hear the auditory stimuli at \u0026lt;\u0026thinsp;40 dB. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e2\u003c/span\u003e illustrates individual AEP from 12 randomly selected individuals with SCZ\u003csub\u003espect\u003c/sub\u003e. Figure\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrates individual AEP from 24 randomly selected HC. \u003cem\u003eSupplementary Fig.\u0026nbsp;4A-B\u003c/em\u003e illustrate mean AEPs from all SCZ\u003csub\u003espect\u003c/sub\u003e and HC.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eEEG acquisition and processing\u003c/h2\u003e \u003cp\u003eWe recorded EEG data at 2048 Hz from 64 Ag-AgCl scalp electrodes arranged according to the international 10\u0026ndash;5 system using a BioSemi ActiveTwo amplifier. In addition, four external electrodes recorded lateral and vertical eye movements and two recorded the heart rhythm (electrocardiography). The Biosemi system uses a common mode sense with a driven right leg electrode in order to minimize common mode voltages. All offline EEG processing was conducted using the MATLAB-based EEGLAB toolbox \u003csup\u003e69\u003c/sup\u003e. After down-sampling to 512 Hz, we removed noisy channels using the PREP Pipeline algorithms with default setting \u003csup\u003e70\u003c/sup\u003e. We referenced remaining channels to the average of all good channels before we interpolated removed channels from surrounding channel potentials. Next, we re-referenced all channels to the new common average obtained after interpolation of bad channels. After average referencing, we removed the mean offset from all channels and applied a high pass filter of 1 Hz. The Trimoutlier eeglab plugin (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://sccn.ucsd.edu/wiki/TrimOutlier\u003c/span\u003e\u003cspan address=\"https://sccn.ucsd.edu/wiki/TrimOutlier\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) identifies and remove sections of bad data (defined as +/- 500 ms around any datapoint exceeding 500 \u0026micro;V across the 64 scalp channels) in the continuous EEG files. Next, independent component analysis (ICA) and automated detection of eye-blink artifacts (ICLABEL) \u003csup\u003e71\u003c/sup\u003e were used to automatically identify EEG artifacts such as eye blinks, line noise, muscle movements, heart noise, and channel noise. All independent components were also visually inspected, before rejection of components with \u0026lt;\u0026thinsp;50% chance of originating from brain activity (assigned by ICLabel). Cleaned EEG data was next low pass filtered to 40 Hz and separate epochs were extracted for each stimulus event with the time window of -200 ms to 700 ms. Finally, epoched data was baseline-corrected from \u0026minus;\u0026thinsp;100-0 ms. Prior to extraction of ERP voltages, the ERPs were re-referenced to linked mastoids to capture both the negative (on centro-frontal electrodes) and positive (on inferior temporal and posterior electrodes) polarity of the auditory ERP (which inverts over the Sylvian fissure). Trials containing amplitudes exceeding +/- 100 \u0026micro;V were excluded prior to averaging. All 12 prepulse alone trials were included. Peak latency and amplitude for the N100 component was defined as the minimal amplitude within a time window from 50\u0026ndash;200 ms after stimulus onset and extracted from channel Cz. In our main analyses we focused on the N100 amplitude from the Cz electrode. However, we also examined N100 latency \u003cem\u003e(Supplementary analysis 2)\u003c/em\u003e. AEPs of individual participants were visually inspected in EEGLAB to ensure that the time windows used in the scripts were correct and that they accurately identified peaks and latencies (between 50\u0026ndash;200 ms). After visual inspection of individual AEPs, we concluded that for the majority of subjects 12 prepulse alone trials were indeed sufficient for eliciting robust AEPs. Further, after visual inspection of individual AEPs, we excluded 74 participants where the peak N100 amplitude (the most negative peak) was outside of the latency range of 50-200ms. N100 amplitude that is generated at 85 db and a longer ISI will elicit a higher amplitude than N100 generated at lower db and shorter ISI \u003csup\u003e72\u003c/sup\u003e. Visual inspection revealed that N100 amplitudes were negative for all participants (from: -3.18\u0026micro;V to \u0026minus;\u0026thinsp;43.62\u0026micro;V). To ease interpretation on the direction of correlation, we multiplied all negative values with \u0026minus;\u0026thinsp;1, giving N100 amplitudes of 3.18\u0026micro;V \u0026minus;\u0026thinsp;43.62\u0026micro;V, so that a higher number reflects a more prominent N100.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eStatistical analyses were conducted using R version 3.6 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.r-project.org\u003c/span\u003e\u003cspan address=\"https://www.r-project.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e; R Core Team, 2014). Group differences in demographics and clinical variables, as provided in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, were calculated using the t-test for continuous variables and the chi-squared test for categorical variables.\u003c/p\u003e \u003cp\u003eFirst, to calculate mean N100 amplitude, T1w/T2w-ratio in AC1 and in AC2 in SCZ\u003csub\u003espect\u003c/sub\u003e (n\u0026thinsp;=\u0026thinsp;33) and HC (n\u0026thinsp;=\u0026thinsp;144), we performed separate analysis of covariance (ANCOVA), where N100 amplitude, T1w/T2w-ratio in AC1 or in AC2 was set as outcome variable, diagnostic group (SCZ\u003csub\u003espect\u003c/sub\u003e or HC) and sex (female or male) as factors, and age as a covariate. To compare the N100 amplitude and the T1w/T2w-ratio in AC1 and AC2 between patients and controls, we used linear models where N100 amplitude or the T1w/T2w-ratio in AC1 or in AC2 were dependent variables and diagnostic group was the independent variable of interest. The models were adjusted for age and sex. Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e and Hedge\u0026acute;s \u003cem\u003eg\u003c/em\u003e for group comparisons were calculated from differences in predicted means \u003csup\u003e73\u003c/sup\u003e. For the linear regression analyses a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.017 was considered significant (Bonferroni correction for three comparisons, i.e., differences in N100 amplitude, in T1w/T2w in AC1 and in T1w/T2w in AC2).\u003c/p\u003e \u003cp\u003eTo test for associations between N100 amplitude and T1w/T2w-ratio in AC1 and in AC2, we ran separate linear models in SCZ\u003csub\u003espect\u003c/sub\u003e and HC, where the N100 amplitude was the dependent variable and T1w/T2w-ratio in AC1 or in AC2 as well as age and sex were independent variables. Thereafter, to examine whether the associations between N100 and T1w/T2w-ratio in AC1 and in AC2 differed between diagnostic groups (SCZ\u003csub\u003espect\u003c/sub\u003e and HC), we ran linear models in the combined sample (n\u0026thinsp;=\u0026thinsp;177) of SCZ\u003csub\u003espect\u003c/sub\u003e and HC with N100 amplitude as dependent variable and diagnosis, T1w/T2w-ratio in AC1 or in AC2 and the interaction term (diagnosis* T1w/T2w-ratio) as independent variables. For these analyses a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.025 was considered significant (Bonferroni correction for two comparisons, i.e., associations between N100 amplitude and T1w/T2w-ratio in AC1/AC2).\u003c/p\u003e \u003cp\u003eWe performed sex stratified ANCOVA, where N100 amplitude, T1w/T2w-ratio in AC1 or in AC2 were set as outcome variables, diagnostic group as factor and age as a covariate. We ran this analysis in female and males separately. To compare the N100 amplitude and the T1w/T2w-ratio in AC1 and AC2 between female SCZ\u003csub\u003espect\u003c/sub\u003e and female HC and between male SCZ\u003csub\u003espect\u003c/sub\u003e and male HC, we used linear models where N100 amplitude, the T1w/T2w-ratio in AC1 or in AC2 were dependent variables and diagnostic group (SCZ\u003csub\u003espect\u003c/sub\u003e or HC) was the independent variable of interest. The models were adjusted for age. We ran this model in females (n\u0026thinsp;=\u0026thinsp;76) and males (n\u0026thinsp;=\u0026thinsp;91) separately. Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e and Hedge\u0026acute;s \u003cem\u003eg\u003c/em\u003e for group comparisons were calculated from differences in predicted means \u003csup\u003e73\u003c/sup\u003e. For the linear regression analyses a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.017 was considered significant.\u003c/p\u003e \u003cp\u003eTo test for associations between N100 amplitude and T1w/T2-ratio in AC1 or in AC2 in female and male SCZ\u003csub\u003espect\u003c/sub\u003e and HC, we ran models in the female SCZ\u003csub\u003espect\u003c/sub\u003e, female HC, male SCZ\u003csub\u003espect\u003c/sub\u003e and male HC samples separately. In these models, the N100 amplitude was the dependent variable and T1w/T2w-ratio in AC1 or in AC2, as well as age were independent variables. Thereafter, to examine whether the associations between N100 amplitude and T1w/T2w-ratio in AC1 and in AC2 differed between sex, we ran linear models with N100 amplitude as the dependent variable and sex, T1w/T2w-ratio in AC1/AC2 and the interaction term (sex*T1w/T2w-ratio in AC1/AC2) as well as age and diagnosis (SCZ\u003csub\u003espect\u003c/sub\u003e or HC), as independent variables. We fitted this model in the combined sample (n\u0026thinsp;=\u0026thinsp;177) of female and male patients and controls. For these analyses a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.025 was considered significant.\u003c/p\u003e \u003cp\u003eIn addition to our main analyses, we ran supplementary analyses assessing T1w/T2w-ratio in AC1 and in AC2 in each hemisphere and its association with N100 amplitude in SCZ\u003csub\u003espect\u003c/sub\u003e and HC. In addition, we examined N100 latency and its association with T1w/T2w-ratio in AC1 and in AC2 in SCZ\u003csub\u003espect\u003c/sub\u003e and HC. Further, we examined how much of the variance in N100 amplitude was explained by age and sex and assessed differences in demographics and in our EEG and MRI data between female and male patients and controls. We also examined differences in N100 amplitude and T1w/T2w-ratios in AC1/AC2 in female SCZ\u003csub\u003espect\u003c/sub\u003e compared to male SCZ\u003csub\u003espect\u003c/sub\u003e, in female HC compared to male HC and between the combined sample of male SCZ\u003csub\u003espect\u003c/sub\u003e and male HC and the combined sample of female SCZ\u003csub\u003espect\u003c/sub\u003e and female HC. Further, we examined N100 amplitude and T1wT2w ratio in the AC1 and AC2 and the association between N100 amplitude and T1wT2w ratios in patients with auditory hallucinations (AH+) and without auditory hallucinations (AH-). As two sensitivity analyses, we also examined N100 amplitude and T1wT2w ratio in the AC1 and AC2 and the N100-T1w/T2w associations in a sample prior to excluding older controls and in a sample where we performed strict age matching between patients and controls. Lastly, we examined the effect of use of antipsychotics and PANSS scores on our EEG and MRI data.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003ch2\u003eDemographics and clinical data\u003c/h2\u003e\n\u003cp\u003eThere were no significant differences in age or sex distribution between\u0026nbsp;SCZ\u003csub\u003espect\u003c/sub\u003e and HC (Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e. Participant characteristics\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"558\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.93177737881508%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.6983842010772%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSCZ\u003csub\u003espect\u003c/sub\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e[n=33\u003c/strong\u003e\u003cstrong\u003e]\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.6983842010772%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHC [n=144\u003c/strong\u003e\u003cstrong\u003e]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.671454219030522%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSCZ\u003csub\u003espect\u003c/sub\u003e vs. HC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.93177737881508%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.6983842010772%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.6983842010772%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.671454219030522%\" valign=\"top\"\u003e\n \u003cp\u003ep-value\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.93177737881508%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWomen\u003c/strong\u003e, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.6983842010772%\" valign=\"top\"\u003e\n \u003cp\u003e16 (48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.6983842010772%\" valign=\"top\"\u003e\n \u003cp\u003e70 (49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.671454219030522%\" valign=\"top\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.93177737881508%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge,\u0026nbsp;\u003c/strong\u003eMean (range, sd)\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.6983842010772%\" valign=\"top\"\u003e\n \u003cp\u003e29.96 (18.46-54.06, 9.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.6983842010772%\" valign=\"top\"\u003e\n \u003cp\u003e32.94 (18.50-45.58, 7.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.671454219030522%\" valign=\"top\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.93177737881508%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime between EEG and MRI,\u0026nbsp;\u003c/strong\u003eMedian (range, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.6983842010772%\" valign=\"top\"\u003e\n \u003cp\u003e6 (0-337, 37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.6983842010772%\" valign=\"top\"\u003e\n \u003cp\u003e13 (0-278, 31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.671454219030522%\" valign=\"top\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.93177737881508%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge of Onset,\u0026nbsp;\u003c/strong\u003eMean (range, sd)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.6983842010772%\" valign=\"top\"\u003e\n \u003cp\u003e24.50 (17-37, 5.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.6983842010772%\" valign=\"top\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.671454219030522%\" valign=\"top\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.93177737881508%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDOI,\u0026nbsp;\u003c/strong\u003eMean (range, sd)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.6983842010772%\" valign=\"top\"\u003e\n \u003cp\u003e4.13 (0-20.47, 5.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.6983842010772%\" valign=\"top\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.671454219030522%\" valign=\"top\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.93177737881508%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGAF-S,\u0026nbsp;\u003c/strong\u003eMean\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e(range, sd)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.6983842010772%\" valign=\"top\"\u003e\n \u003cp\u003e54.48 (38-85, 11.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.6983842010772%\" valign=\"top\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.671454219030522%\" valign=\"top\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.93177737881508%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGAF-F,\u0026nbsp;\u003c/strong\u003eMean\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e(range, sd)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.6983842010772%\" valign=\"top\"\u003e\n \u003cp\u003e55.18 (35-85, 14.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.6983842010772%\" valign=\"top\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.671454219030522%\" valign=\"top\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.93177737881508%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePANSS total,\u0026nbsp;\u003c/strong\u003eMean\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e(range, sd)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.6983842010772%\" valign=\"top\"\u003e\n \u003cp\u003e56.12 (33-91, 14.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.6983842010772%\" valign=\"top\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.671454219030522%\" valign=\"top\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.93177737881508%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePANSS G,\u0026nbsp;\u003c/strong\u003eMean\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e(range, sd)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.6983842010772%\" valign=\"top\"\u003e\n \u003cp\u003e29.79 (18-47, 7.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.6983842010772%\" valign=\"top\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.671454219030522%\" valign=\"top\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.93177737881508%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePANSS P,\u0026nbsp;\u003c/strong\u003eMean\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e(range, sd)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.6983842010772%\" valign=\"top\"\u003e\n \u003cp\u003e12.97 (7-24, 3.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.6983842010772%\" valign=\"top\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.671454219030522%\" valign=\"top\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.93177737881508%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePANSS N,\u0026nbsp;\u003c/strong\u003eMean\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e(range, sd)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.6983842010772%\" valign=\"top\"\u003e\n \u003cp\u003e13.36 (7-25, 5.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.6983842010772%\" valign=\"top\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.671454219030522%\" valign=\"top\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.93177737881508%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAntipsychotic drug use, DDD,\u0026nbsp;\u003c/strong\u003eMean\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e(range, sd)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.6983842010772%\" valign=\"top\"\u003e\n \u003cp\u003e1.01 (0.19-2.25, 0.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.6983842010772%\" valign=\"top\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.671454219030522%\" valign=\"top\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote:\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eTable 1 shows the demographics of the final study sample.\u0026nbsp;SCZ\u003csub\u003espect\u003c/sub\u003e, patients with schizophrenia spectrum disorders and in HC, healthy controls; n, number; %, percentage; range (min-max); sd, standard deviation; EEG, electroencephalography; MRI, magnetic resonance imaging; IQR, interquartile range; Age of onset, age of onset of first positive psychotic symptom in years; DOI, duration of illness in years; GAF, Global assessment of function; GAF-S, GAF-symptoms, GAF-F, GAF- functioning; PANSS, positive and negative syndrome scale;\u0026nbsp;G, general; P, positive; N, negative; DDD, defined daily dose of antipsychotics;\u0026nbsp;9 SCZ\u003csub\u003espect\u003c/sub\u003e had missing information about age of onset and DOI. 5 had missing information about DDD.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eMean N100 amplitude, T1w/T2w-ratio in AC1 and T1w/T2w-ratio in AC2 in SCZ\u003csub\u003espect\u003c/sub\u003e and HC\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eEstimated marginal means and differences in means between SCZ\u003csub\u003espect\u003c/sub\u003e and HC\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eare provided in Table 2.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u0026nbsp;\u003c/strong\u003eMean N100 amplitude, T1w/T2w-ratio in AC1 and AC2 in\u0026nbsp;SCZ\u003csub\u003espect\u003c/sub\u003e and HC \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"595\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.991596638655462%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.3781512605042%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eN100 amplitude (microvolts)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMean (SE) [95% CI]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.3781512605042%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAC1 T1w/T2w-ratio\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMean (SE) [95% CI]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.252100840336134%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAC2 T1w/T2w-ratio\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMean (SE) [95% CI]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.991596638655462%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSCZ\u003csub\u003espect\u003c/sub\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;[n=33]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.3781512605042%\" valign=\"top\"\u003e\n \u003cp\u003e12.19 (1.29) [9.65-14.74]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.3781512605042%\" valign=\"top\"\u003e\n \u003cp\u003e0.89 (0.002) [0.88-0.89]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.252100840336134%\" valign=\"top\"\u003e\n \u003cp\u003e0.88 (0.002) [0.87-0.88]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.991596638655462%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHC [n=144\u003c/strong\u003e\u003cstrong\u003e]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.3781512605042%\" valign=\"top\"\u003e\n \u003cp\u003e15.30 (0.61) [14.09-16.51]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.3781512605042%\" valign=\"top\"\u003e\n \u003cp\u003e0.89 (0.001) [0.89-0.89]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.252100840336134%\" valign=\"top\"\u003e\n \u003cp\u003e0.88 (0.001) [0.88-0.88]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.991596638655462%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSCZ\u003csub\u003espect\u003c/sub\u003e vs. HC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.3781512605042%\" valign=\"top\"\u003e\n \u003cp\u003eest=-3.11\u003c/p\u003e\n \u003cp\u003ese=1.43\u003c/p\u003e\n \u003cp\u003ep=0.03\u003c/p\u003e\n \u003cp\u003eCohen\u0026rsquo;s d=0.42\u003c/p\u003e\n \u003cp\u003eHedges\u0026acute;g=0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.3781512605042%\" valign=\"top\"\u003e\n \u003cp\u003eest=-1.87e-04\u003c/p\u003e\n \u003cp\u003ese=2.32e-03\u003c/p\u003e\n \u003cp\u003ep=0.94\u003c/p\u003e\n \u003cp\u003eCohen\u0026rsquo;s d=0.02\u003c/p\u003e\n \u003cp\u003eHedges\u0026acute;g=0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.252100840336134%\" valign=\"top\"\u003e\n \u003cp\u003eest=7.20e-04\u003c/p\u003e\n \u003cp\u003ese=2.34e-03\u003c/p\u003e\n \u003cp\u003ep=0.76\u003c/p\u003e\n \u003cp\u003eCohen\u0026rsquo;s d=0.06\u003c/p\u003e\n \u003cp\u003eHedges\u0026acute;g=0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote:\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eTable 2 shows\u0026nbsp;mean N100 amplitude, T1w/T2w-ratio in\u0026nbsp;AC1, primary auditory cortex and in AC2, secondary auditory cortex\u0026nbsp;in\u0026nbsp;SCZ\u003csub\u003espect\u003c/sub\u003e, patients with schizophrenia\u0026nbsp;spectrum disorder, in HC,\u0026nbsp;healthy controls. Estimated marginal means were calculated using ANCOVA, where\u0026nbsp;N100 amplitude, T1w/T2w-ratio in AC1 or T1w/T2w-ratio in AC2 were set as dependent variables with age, sex and diagnosis as independent variables\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eEstimated marginal means are provided with SE (standard error of the mean) and 95% CI, confidence interval.\u0026nbsp;In addition, Table 2 shows differences in means between\u0026nbsp;SCZ\u003csub\u003espect\u003c/sub\u003e and HC. Est, estimate; p, p-value; *, significant p-value (p\u0026lt;0.017). N100 amplitude nominally smaller in SCZ\u003csub\u003espect\u003c/sub\u003e compared to HC. \u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eAssociation between N100 amplitude and T1w/T2w-ratio in AC1/AC2 in SCZ\u003csub\u003espect\u003c/sub\u003e and HC\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eWe found no significant association between N100 amplitude and T1w/T2w-ratio in AC1/AC2 in SCZ\u003csub\u003espect\u003c/sub\u003e or in HC (Figure 4). Results from the regression models with interaction terms (diagnosis\u0026times;T1w/T2w-ratio) indicate that the associations between N100 amplitude and T1w/T2w-ratio in AC1/AC2 did not differ between SCZ\u003csub\u003espect\u003c/sub\u003e and HC (AC1: estimate (est)=132.26, standard error (se)=139.63, p-value (p)=0.34; AC2: est=144.76, se=124.74, p=0.25).\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eMean N100 amplitude, T1w/T2w-ratio in AC1 and T1w/T2w-ratio in AC2 in female/male SCZ\u003csub\u003espect\u003c/sub\u003e and HC\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eEstimated marginal means and differences in means between female SCZ\u003csub\u003espect\u003c/sub\u003e and female HC and between male SCZ\u003csub\u003espect\u003c/sub\u003e and male HC are provided in Table 3. Of interest, N100 amplitude was significantly smaller in male SCZ\u003csub\u003espect\u003c/sub\u003e compared to male HC (est=4.30, se=1.63, p=0.01).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u0026nbsp;\u003c/strong\u003eMean N100 amplitude, T1w/T2w-ratio in AC1 and AC2 in female/male\u0026nbsp;SCZ\u003csub\u003espect\u003c/sub\u003e and HC \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"576\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.618055555555557%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.07638888888889%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eN100 amplitude (microvolts)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMean (SE) [95% CI]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.95138888888889%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAC1 T1w/T2w-ratio\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMean (SE) [95% CI]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.354166666666668%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAC2 T1w/T2w-ratio\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMean (SE) [95% CI]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.618055555555557%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSCZ\u003csub\u003espect\u003c/sub\u003e F [n=16]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.07638888888889%\" valign=\"top\"\u003e\n \u003cp\u003e15.40 (2.11) [11.21-19.60]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.95138888888889%\" valign=\"top\"\u003e\n \u003cp\u003e0.89 (0.003) [0.88-0.89]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.354166666666668%\" valign=\"top\"\u003e\n \u003cp\u003e0.87 (0.003) [0.87-0.88]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.618055555555557%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHC F [n=70]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.07638888888889%\" valign=\"top\"\u003e\n \u003cp\u003e16.53 (1.01) [14.53-18.54]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.95138888888889%\" valign=\"top\"\u003e\n \u003cp\u003e0.89 (0.001) [0.89-0.89]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.354166666666668%\" valign=\"top\"\u003e\n \u003cp\u003e0.88 (0.001) [0.88-0.88]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.618055555555557%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSCZ\u003csub\u003espect\u003c/sub\u003e M [n=17]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.07638888888889%\" valign=\"top\"\u003e\n \u003cp\u003e9.62 (1.46) [6.72-12.53]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.95138888888889%\" valign=\"top\"\u003e\n \u003cp\u003e0.89 (0.003) [0.88-0.90]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.354166666666668%\" valign=\"top\"\u003e\n \u003cp\u003e0.88 (0.003) [0.88-0.89]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.618055555555557%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHC M [n=74]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.07638888888889%\" valign=\"top\"\u003e\n \u003cp\u003e13.92\u0026nbsp;(0.67) [12.56-15.29]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.95138888888889%\" valign=\"top\"\u003e\n \u003cp\u003e0.89 (0.001) [0.88-0.89]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.354166666666668%\" valign=\"top\"\u003e\n \u003cp\u003e0.88 (0.001) [0.87-0.88]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.618055555555557%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSCZ\u003csub\u003espect\u003c/sub\u003e F vs. HC F\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.07638888888889%\" valign=\"top\"\u003e\n \u003cp\u003eest=-1.13\u003c/p\u003e\n \u003cp\u003ese=2.34\u003c/p\u003e\n \u003cp\u003ep=0.63\u003c/p\u003e\n \u003cp\u003eCohen\u0026rsquo;s d=0.13\u003c/p\u003e\n \u003cp\u003eHedges\u0026acute;g=0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.95138888888889%\" valign=\"top\"\u003e\n \u003cp\u003eest=-0.01\u003c/p\u003e\n \u003cp\u003ese=0.003\u003c/p\u003e\n \u003cp\u003ep=0.10\u003c/p\u003e\n \u003cp\u003eCohen\u0026rsquo;s d=0.47\u003c/p\u003e\n \u003cp\u003eHedges\u0026acute;g=0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.354166666666668%\" valign=\"top\"\u003e\n \u003cp\u003eest=-5.31e-03\u003c/p\u003e\n \u003cp\u003ese=3.22e-03\u003c/p\u003e\n \u003cp\u003ep=0.10\u003c/p\u003e\n \u003cp\u003eCohen\u0026rsquo;s d=0.47\u003c/p\u003e\n \u003cp\u003eHedges\u0026acute;g=0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.618055555555557%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSCZ\u003csub\u003espect\u003c/sub\u003e M vs. HC M\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.07638888888889%\" valign=\"top\"\u003e\n \u003cp\u003eest=-4.30\u003c/p\u003e\n \u003cp\u003ese=1.63\u003c/p\u003e\n \u003cp\u003ep=0.010*\u003c/p\u003e\n \u003cp\u003eCohen\u0026rsquo;s d=0.72\u003c/p\u003e\n \u003cp\u003eHedges\u0026acute;g=0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.95138888888889%\" valign=\"top\"\u003e\n \u003cp\u003eest=0.004\u003c/p\u003e\n \u003cp\u003ese=0.003\u003c/p\u003e\n \u003cp\u003ep=0.21\u003c/p\u003e\n \u003cp\u003eCohen\u0026rsquo;s d=0.65\u003c/p\u003e\n \u003cp\u003eHedges\u0026acute;g=0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.354166666666668%\" valign=\"top\"\u003e\n \u003cp\u003eest=0.01\u003c/p\u003e\n \u003cp\u003ese=0.003\u003c/p\u003e\n \u003cp\u003ep=0.09\u003c/p\u003e\n \u003cp\u003eCohen\u0026rsquo;s d=0.47\u003c/p\u003e\n \u003cp\u003eHedges\u0026acute;g=0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote:\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eTable 3\u0026nbsp;shows mean N100 amplitude, mean T1w/T2w-ratio in\u0026nbsp;AC1, primary auditory cortex and in AC2, secondary auditory cortex\u0026nbsp;in\u0026nbsp;SCZ\u003csub\u003espect\u003c/sub\u003e F, female patients with schizophrenia spectrum disorder, in F HC, female healthy controls, in SCZ\u003csub\u003espect\u003c/sub\u003e M, male SCZ\u003csub\u003espect\u003c/sub\u003e and in M HC, male HC. Estimated marginal means were calculated using ANCOVA, where N100 amplitude, T1w/T2w-ratio in AC1 or T1w/T2w-ratio in AC2 were set as dependent variables with age and diagnosis as independent variables\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eEstimated marginal means are provided with SE (standard error of the mean) and 95% CI, confidence interval.\u0026nbsp;In addition, Table 3 shows differences in means between\u0026nbsp;female SCZ\u003csub\u003espect\u003c/sub\u003e and female HC and between male SCZ\u003csub\u003espect\u003c/sub\u003e and male HC. Est, estimate; p, p-value; *, significant p-value (p\u0026lt;0.017). N100 amplitude was significantly smaller in male SCZ\u003csub\u003espect\u003c/sub\u003e compared to male HC. \u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eAssociation between N100 amplitude and T1w/T2w-ratio in AC1/AC2 in female/male SCZ\u003csub\u003espect\u003c/sub\u003e and HC\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eWe\u0026nbsp;found no significant association between N100 amplitude and T1w/T2w-ratio in AC1 or in AC2 in female or male\u0026nbsp;SCZ\u003csub\u003espect\u003c/sub\u003e (Figure 5.1.)\u0026nbsp;or in female or male HC (Figure 5.2.)\u0026nbsp;The associations between N100 amplitude and T1w/T2w-ratio in AC1/AC2 did not differ between sex (AC1: est=91.98, se=96.04, p=0.34; AC2: est=-59.05, se=95.87, p=0.92).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn addition to our main results, of interest,\u0026nbsp;we found no difference in\u0026nbsp;T1w/T2w-ratios in the left or right AC1 or AC2 between SCZ\u003csub\u003espect\u003c/sub\u003e and HC (Supplementary analyses 1). N100 amplitude was not associated with T1w/Tw2-ratios in the left or right AC1/AC2 in any groups (Supplementary analyses 2). Further,\u0026nbsp;N100 latency did not differ between SCZ\u003csub\u003espect\u003c/sub\u003e and HC and was not associated with T1w/T2w-ratio in AC1/AC2 in any groups (Supplementary analyses 3). In\u0026nbsp;the combined sample of SCZ\u003csub\u003espect \u0026nbsp;\u0026nbsp;\u003c/sub\u003eand HC, sex explained 4.5%, while age explained 2.7% of variance in N100 amplitude. In SCZ\u003csub\u003espect\u0026nbsp;\u003c/sub\u003eonly, sex explained 13.67%, while age explained 9.91% of the variance in N100 amplitude. In HC only, sex explained 3.17 % and age explained 1.62% of variance in N100 amplitude (Supplementary analyses 4). Further, N100 amplitude was nominally reduced in male SCZ\u003csub\u003espect\u003c/sub\u003e compared to female SCZ\u003csub\u003espect\u003c/sub\u003e (p=0.03), in male HC compared to female HC (p=0.03) and significantly reduced in the combined sample of males (patients and controls) compared to females (patients and controls) (p=0.004) (Supplementary analyses 6). We found reduced T1w/T2w-ratio in the AC2 in female SCZ\u003csub\u003espect\u0026nbsp;\u003c/sub\u003ecompared to male SCZ\u003csub\u003espect\u003c/sub\u003e (p=0.01) and reduced N100 amplitude in the combined sample of male SCZ\u003csub\u003espect\u003c/sub\u003e and HC compared to the combined sample of female SCZ\u003csub\u003espect\u003c/sub\u003e and HC (p=0.004) (Supplementary analyses 6). We did not find any significant difference in N100 amplitude and T1w/T2w-ratio in AC1 or AC2 between AH+ or AH, and the associations did not differ between AH+ and AH- (Supplementary analyses 7). Further, when comparing means between SCZ\u003csub\u003espect\u003c/sub\u003e and HC prior to excluding older HC from the sample, SCZ\u003csub\u003espect\u003c/sub\u003e had significantly smaller N100 amplitude compared to HC (p=0.017) (Supplementary analyses 8.1.). When comparing means between SCZ\u003csub\u003espect\u003c/sub\u003e and HC after stricter age-matching than in our main analysis, we found no significant difference in N100 amplitude or in T1w/T2w-ratio in AC1/AC2 between SCZ\u003csub\u003espect\u003c/sub\u003e and HC (Supplementary analyses 8.2.). Further, antipsychotic use explained 2.25% of variance in N100 amplitude, 6.60% of variance in T1w/T2w-ratio in AC1 and 4.58% of variance in T1w/T2w-ratio in AC2 (Supplementary analyses 9.2.). Total PANSS score explained 2.7% of variance in N100 amplitude, 10.12% of variance in T1w/T2w-ratio in AC1 and 10.54% of variance in T1w/T2w-ratio in AC2 (Supplementary analyses 10.).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe current study yielded three main findings. First, N100 amplitude was significantly reduced in male SCZ\u003csub\u003espect\u003c/sub\u003e compared to male HC and nominally reduced in the combined sample of SCZ\u003csub\u003espect\u003c/sub\u003e compared to the combined sample of HC. Second, T1w/T2w-ratio in AC1/AC2 did not differ between any groups. Finally, we did not find any significant association between N100 amplitude and T1w/T2w-ratio in the AC1 or in AC2.\u003c/p\u003e \u003cp\u003eTo our knowledge, this is the first published report showing reduced N100 amplitude in male SCZ\u003csub\u003espect\u003c/sub\u003e compared to male HC \u003csup\u003e53\u003c/sup\u003e. While we at this point can only speculate why N100 amplitude was reduced in males with SCZ\u003csub\u003espect\u003c/sub\u003e, but not in females with SCZ\u003csub\u003espect\u003c/sub\u003e, the neuroprotective abilities of estrogen may play a role \u003csup\u003e74\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOf interest, our supplementary analyses revealed reduced N100 amplitude in the combined sample of male patients and controls compared to the combined sample of female patients and controls \u003cem\u003e(Supplementary Table\u0026nbsp;6).\u003c/em\u003e These findings are in accordance with previous reports of sex differences in auditory functioning in healthy individuals. Females have larger auditory brainstem response \u003csup\u003e75\u0026ndash;77\u003c/sup\u003e and larger P300 amplitude, indicating enhanced auditory function, compared to males \u003csup\u003e49\u003c/sup\u003e. Further, females are more sensitive to high frequency sounds \u003csup\u003e78\u003c/sup\u003e while males have a superior spatial auditory perception \u003csup\u003e79\u0026ndash;81\u003c/sup\u003e. In females the AC1 is more sensitive to noise compared to males \u003csup\u003e82\u003c/sup\u003e. Together, these findings indicate sex differences in auditory function and estrogen may play a role. Estrogen is believed to protect the auditory system from noise and age-related damage and to optimize auditory processing \u003csup\u003e83\u003c/sup\u003e. Sex differences in auditory function are already present in infants \u003csup\u003e84,85\u003c/sup\u003e, indicating that exposure to sex steroids\u0026rsquo; metabolites during prenatal development may lead to fundamental sex differences in auditory function \u003csup\u003e86\u003c/sup\u003e. Further, auditory function changes during the menstrual cycle \u003csup\u003e87\u0026ndash;89\u003c/sup\u003e and during pregnancy, a period when estrogen (and progesterone) levels rise continuously until giving birth \u003csup\u003e90,91\u003c/sup\u003e. Peri- and postmenopausal women have diminished auditory function \u003csup\u003e92\u003c/sup\u003e and hormone-replacement therapy may reverse this decline \u003csup\u003e93,94\u003c/sup\u003e. Further females with Turner\u0026acute;s syndrome, a disorder characterized by estrogen deficiency, have increased rate of hearing decline \u003csup\u003e83\u003c/sup\u003e and auditory pathology \u003csup\u003e95\u003c/sup\u003e. Together, these findings indicate that estrogen has a neuroprotective role in auditory function \u003csup\u003e96\u003c/sup\u003e. The neuroprotective effect of estrogen is believed to be partly mediated through its interaction with brain-derived neurotrophic factor (BDNF), gamma-aminobutyric acid (GABA), norepinephrine \u003csup\u003e83,97\u003c/sup\u003e and through enhancing myelination \u003csup\u003e46,98,99\u003c/sup\u003e. Women with MS have fewer MS relapses during pregnancy, suggesting a neuroprotective effect of estrogen through promoting myelination \u003csup\u003e100\u003c/sup\u003e. More research is needed to fully understand the effect of sex steroids and myelination on auditory function in humans \u003csup\u003e83\u003c/sup\u003e. In addition, the relationship between sex steroids and N100 amplitude remains elusive.\u003c/p\u003e \u003cp\u003eThe effect of sex steroids on auditory function in SCZ\u003csub\u003espect\u003c/sub\u003e remain unknown. However, animal models of SCZ\u003csub\u003espect\u003c/sub\u003e show that estrogen plays a neuroprotective role in auditory function when interacting with BDNF, \u003csup\u003e101\u003c/sup\u003e. Further, sex differences in dopamine \u003csup\u003e102\u003c/sup\u003e and GABA \u003csup\u003e103\u003c/sup\u003e, neurotransmitters believed to have implications for generating post-synaptic potentials \u003csup\u003e104\u0026ndash;106\u003c/sup\u003e which are important for auditory function, are reported in SCZ\u003csub\u003espect\u003c/sub\u003e.. Thus, sex differences in these neurotransmitters may also be involved in the current findings of reduced N100 amplitude in males with SCZ\u003csub\u003espect\u003c/sub\u003e. Understanding the relationship between sex steroids and N100 amplitude in SCZ\u003csub\u003espect\u003c/sub\u003e may provide insight into new treatment targets. Animal models of SCZ\u003csub\u003espect\u003c/sub\u003e show evidence suggesting that estrogen may be protective of the disorder through its interaction with BDNF and thus that estrogen\u0026ndash;BDNF interactions may be new treatment targets \u003csup\u003e101\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe N100 amplitude may help us understand basic elemental mechanisms of brain function in SCZ\u003csub\u003espect\u003c/sub\u003e. In a previous study, we found positive associations between AC thickness and N100 amplitude in SCZ\u003csub\u003espect\u003c/sub\u003e, suggesting that a common neural substrate may underlie AC thickness and N100 amplitude alterations \u003csup\u003e61\u003c/sup\u003e. Based on these previous findings, as well as on a growing literature indicating myelination abnormalities in SCZ\u003csub\u003espect\u003c/sub\u003e \u003csup\u003e107\u0026ndash;114\u003c/sup\u003e, we here aimed to examine whether myelination in AC may play a role in this association. Myelination plays an important role in spike synchrony \u003csup\u003e115\u003c/sup\u003e. Thus, impaired myelination of pyramidal neurons in the AC could lead to abnormal neural synchrony and altered auditory processing, reflected by reduced N100 amplitude in SCZ\u003csub\u003espect\u003c/sub\u003e \u003csup\u003e16,116\u003c/sup\u003e. Based on the assumption of altered myelination and altered synchronization of auditory pyramidal neurons in SCZ\u003csub\u003espect\u003c/sub\u003e, we expected to find reduced N100 amplitude and decreased T1w/T2w-ratio in AC in SCZ\u003csub\u003espect\u003c/sub\u003e and an association between reduced N100 amplitude and decreased T1w/T2w-ratio. However, in the current study N100 amplitude and T1w/T2w-ratio did not differ significantly between patients and controls and N100 amplitude was not associated with T1w/T2w-ratio in any groups. Thus, our findings did not support the hypothesis that altered myelination in the AC1/AC2, indexed by T1w/T2w-ratio, underlies N100 abnormalities in SCZ\u003csub\u003espect\u003c/sub\u003e. However, it has been questioned to what degree T1w/T2w-ratio measures myelin. In one combined MRI and post-mortem study of patients with MS, the T1w/T2w-ratio correlated with dendritic density rather than myelin density \u003csup\u003e42\u003c/sup\u003e. Furthermore, while a high spatial correlation with cortical myelination was demonstrated by Glasser et al. (2014) \u003csup\u003e117\u003c/sup\u003e, recent studies have reported lower correlations with indices of myelin in white matter \u003csup\u003e118,119\u003c/sup\u003e, which shows that the T1w/T2w-ratio is a complex signal and not a quantitative marker of myelin content only. While the current findings point towards a lack of association between N100 amplitude and T1w/T2w-ratio in SCZ\u003csub\u003espect\u003c/sub\u003e, we cannot exclude altered myelination in the AC as a neural substrate for N100 amplitude reduction as previously reported in these disorders. To fully understand how myelination in the AC may relate to N100 amplitude in SCZ\u003csub\u003espect\u003c/sub\u003e, we need more precise measures of intracortical myelin. In theory, although speculative, another way to investigate the relationship between N100 amplitude and myelination in the AC may be combining intracortical EEG examinations with postmortem examination of myelin content in the AC. However, this method is hampered by ethical and technical challenges. Therefore, a combination of EEG and MRI measures acquired in vivo is more feasible.\u003c/p\u003e \u003cp\u003eOther factors than altered myelination, indexed by T1w/T2w-ratio, may explain reduced N100 amplitude in SCZ\u003csub\u003espect\u003c/sub\u003e. At this point we can only speculate what neural substrate may underly reduced N100 amplitude and thus altered function of AC pyramidal cells in SCZ\u003csub\u003espect\u003c/sub\u003e. Altered synaptic pruning \u003csup\u003e120,121\u003c/sup\u003e resulting in reduced dendritic spine density on cortical pyramidal neurons \u003csup\u003e122,123\u003c/sup\u003e, is part of the pathogenesis of SCZ\u003csub\u003espect\u003c/sub\u003e. Reduced dendritic spine density on AC pyramidal cells (and interneurons) may result in desynchronized firing, a decreased summation of postsynaptic potentials and thus in reduced N100 amplitude in SCZ\u003csub\u003espect\u003c/sub\u003e \u003csup\u003e116,124\u003c/sup\u003e. Further, excessive synaptic pruning in the AC in SCZ\u003csub\u003espect\u003c/sub\u003e may lead to impaired neural communication in cortical areas involved in auditory processing and may result in auditory hallucinations \u003csup\u003e125\u0026ndash;127\u003c/sup\u003e. Of note, these two alternative potential mechanisms are consistent with our previous finding of an association between AC cortical thickness and N100 amplitude in SCZ\u003csub\u003espect\u003c/sub\u003e \u003csup\u003e61\u003c/sup\u003e. While the current study focused on cortical structures, deeper subcortical white matter may be associated with N100 amplitude.\u003c/p\u003e \u003cp\u003eFew studies have investigated the effect of APs on N100 amplitude and findings are inconclusive \u003csup\u003e128\u0026ndash;130\u003c/sup\u003e. APs commonly used to treat SCZ\u003csub\u003espect\u003c/sub\u003e have high affinity to the dopamine D2 receptor and to the 5-hydroxytryptamine 2 A receptor \u003csup\u003e131\u003c/sup\u003e. Thus, APs may influence N100 amplitude either directly by having effect on neural generators of the N100 or indirectly by decreasing symptoms in SCZ\u003csub\u003espect\u003c/sub\u003e \u003csup\u003e128,132\u003c/sup\u003e. Studies investigating correlations between the dose of APs and N100 amplitude are inconclusive \u003csup\u003e133,134\u003c/sup\u003e. Further, one study has shown no effect of APs on the gray/white-matter contrast along the cortical surface \u003csup\u003e135\u003c/sup\u003e. To conclude, longitudinal studies investigating N100 amplitude and myelination in individuals with SCZ\u003csub\u003espect\u003c/sub\u003e before and after starting on APs are needed to untangle the exact effect of APs on N100 amplitude and myelination.\u003c/p\u003e \u003cp\u003eSome limitations should be considered when interpreting the current findings. As mentioned above, while the T1w/T2w-ratio is spatially correlated with myelination of the cortex, it is not a direct measure of myelin content. Second, the small sample of SCZ\u003csub\u003espect\u003c/sub\u003e is an issue, although the study was hypothesis-driven and focusing on specific regions of interest, limiting the number of tests. Further, the way that we generated AEPs, using a small number of trials instead of what is typically recommended for AEPs is unusual. However, after visual inspection of AEPs, we found that the relatively strong stimulus intensity and the long ISI did elicit robust and large-amplitude AEPs as described by others \u003csup\u003e68\u003c/sup\u003e. Strengths of this study include the use of multimodal imaging (EEG and MRI), a sample of clinically well characterized participants, rigorous quality control and assessment of sex differences.\u003c/p\u003e \u003cp\u003eIn conclusion, our results are consistent with previous findings of reduced N100 amplitude in SCZ\u003csub\u003espect\u003c/sub\u003e although the finding was restricted to males only. We did not find altered T1w-T2w-ratio within AC in SCZ\u003csub\u003espect\u003c/sub\u003e compared to HC and found no associations between the N100 amplitude and T1w-T2w-ratio. More precise estimates of intracortical myelin in the AC and larger patient samples are needed to disentangle whether altered myelination explains N100 amplitude reduction in SCZ\u003csub\u003espect\u003c/sub\u003e.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Research Council of Norway (223273, 274359, 249795, 248238), the South \u0026ndash; Eastern Norway Regional Health Authority (2014097, 2015044, 2015073, 2017097, 2018037, 2018076, 2019104), the Norwegian Extra Foundation for Health and Rehabilitation (2015/FO5146), the European Research Council under the European Union\u0026apos;s Horizon 2020 research and Innovation program (ERC StG 802998), the Ebbe Fr\u0026oslash;land foundation, and a research grant from Mrs. Throne-Holst. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eT.E. is a consultant to BrainWaveBank and Sunovion and received speaker\u0026rsquo;s honoraria from Lundbeck and Janssen Cilag. O.A.A. is a consultant to cortechs.ai and received speaker\u0026rsquo;s honoraria from Lundbeck, Janssen, Sunovion. I.A. has received speaker\u0026rsquo;s honoraria from Lundbeck. The other authors report no conflict of interest.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData and Code Availability Statement\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMRI and EEG data used in the following study was collected at our research center, NORMENT, Oslo, Norway, as part of the TOP study. The data was collected between 2015 and 2019. The MRI and EEG data is currently not openly available due to ethical and privacy issues of clinical data. The study was approved by the Regional Committees for Medical and Health Research Ethics of South \u0026ndash; Eastern Norway, and all participants provided written informed consent.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSaha, S., Chant, D., Welham, J. \u0026amp; McGrath, J. A systematic review of the prevalence of schizophrenia. PLoS Med 2, e141, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pmed.0020141\u003c/span\u003e\u003cspan address=\"10.1371/journal.pmed.0020141\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2005).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKompus, K. \u003cem\u003eet al.\u003c/em\u003e The role of the primary auditory cortex in the neural mechanism of auditory verbal hallucinations. Front Hum Neurosci 7, 144, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fnhum.2013.00144\u003c/span\u003e\u003cspan address=\"10.3389/fnhum.2013.00144\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eParker, E. M. \u0026amp; Sweet, R. A. Stereological Assessments of Neuronal Pathology in Auditory Cortex in Schizophrenia. Front Neuroanat 11, 131, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fnana.2017.00131\u003c/span\u003e\u003cspan address=\"10.3389/fnana.2017.00131\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRosburg, T., Boutros, N. N. \u0026amp; Ford, J. M. Reduced auditory evoked potential component N100 in schizophrenia\u0026ndash;a critical review. Psychiatry Res 161, 259\u0026ndash;274, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.psychres.2008.03.017\u003c/span\u003e\u003cspan address=\"10.1016/j.psychres.2008.03.017\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2008).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSalisbury, D. F., Collins, K. C. \u0026amp; McCarley, R. W. Reductions in the N1 and P2 auditory event-related potentials in first-hospitalized and chronic schizophrenia. Schizophrenia bulletin 36, 991\u0026ndash;1000, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/schbul/sbp003\u003c/span\u003e\u003cspan address=\"10.1093/schbul/sbp003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2010).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFoxe, J. J. \u003cem\u003eet al.\u003c/em\u003e The N1 auditory evoked potential component as an endophenotype for schizophrenia: high-density electrical mapping in clinically unaffected first-degree relatives, first-episode, and chronic schizophrenia patients. European Archives of Psychiatry and Clinical Neuroscience 261, 331\u0026ndash;339, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00406-010-0176-0\u003c/span\u003e\u003cspan address=\"10.1007/s00406-010-0176-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2011).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang, B., Zartaloudi, E., Linden, J. F. \u0026amp; Bramon, E. Neurophysiology in psychosis: The quest for disease biomarkers. Transl Psychiatry 12, 100, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41398-022-01860-x\u003c/span\u003e\u003cspan address=\"10.1038/s41398-022-01860-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShen, C. L. \u003cem\u003eet al.\u003c/em\u003e P50, N100, and P200 Auditory Sensory Gating Deficits in Schizophrenia Patients. Front Psychiatry 11, 868, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fpsyt.2020.00868\u003c/span\u003e\u003cspan address=\"10.3389/fpsyt.2020.00868\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePantev, C. \u003cem\u003eet al.\u003c/em\u003e Specific tonotopic organizations of different areas of the human auditory cortex revealed by simultaneous magnetic and electric recordings. Electroencephalogr Clin Neurophysiol 94, 26\u0026ndash;40, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/0013-4694(94)00209-4\u003c/span\u003e\u003cspan address=\"10.1016/0013-4694(94)00209-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1995).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLuck, S. J. \u003cem\u003eAn introduction to the event-related potential technique\u003c/em\u003e. Second edition. edn, (The MIT Press, 2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHaroutunian, V. \u003cem\u003eet al.\u003c/em\u003e Myelination, oligodendrocytes, and serious mental illness. Glia 62, 1856\u0026ndash;1877, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/glia.22716\u003c/span\u003e\u003cspan address=\"10.1002/glia.22716\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUhlhaas, P. J. \u0026amp; Singer, W. Abnormal neural oscillations and synchrony in schizophrenia. Nature Reviews Neuroscience 11, 100\u0026ndash;113, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/nrn2774\u003c/span\u003e\u003cspan address=\"10.1038/nrn2774\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2010).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBartzokis, G. Schizophrenia: Breakdown in the Well-regulated Lifelong Process of Brain Development and Maturation. Neuropsychopharmacology 27, 672\u0026ndash;683, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0893-133X(02)00364-0\u003c/span\u003e\u003cspan address=\"10.1016/S0893-133X(02)00364-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2002).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBalz, J. \u003cem\u003eet al.\u003c/em\u003e Beta/Gamma Oscillations and Event-Related Potentials Indicate Aberrant Multisensory Processing in Schizophrenia. Frontiers in Psychology 7, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fpsyg.2016.01896\u003c/span\u003e\u003cspan address=\"10.3389/fpsyg.2016.01896\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHaenschel, C. \u003cem\u003eet al.\u003c/em\u003e Cortical Oscillatory Activity Is Critical for Working Memory as Revealed by Deficits in Early-Onset Schizophrenia. The Journal of Neuroscience 29, 9481, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1523/JNEUROSCI.1428-09.2009\u003c/span\u003e\u003cspan address=\"10.1523/JNEUROSCI.1428-09.2009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2009).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWhitford, T. J., Ford, J. M., Mathalon, D. H., Kubicki, M. \u0026amp; Shenton, M. E. Schizophrenia, myelination, and delayed corollary discharges: a hypothesis. Schizophrenia bulletin 38, 486\u0026ndash;494, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/schbul/sbq105\u003c/span\u003e\u003cspan address=\"10.1093/schbul/sbq105\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2012).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePajevic, S., Basser, P. J. \u0026amp; Fields, R. D. Role of myelin plasticity in oscillations and synchrony of neuronal activity. Neuroscience 276, 135\u0026ndash;147, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.neuroscience.2013.11.007\u003c/span\u003e\u003cspan address=\"10.1016/j.neuroscience.2013.11.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFries, P. Rhythms for Cognition: Communication through Coherence. Neuron 88, 220\u0026ndash;235, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.neuron.2015.09.034\u003c/span\u003e\u003cspan address=\"10.1016/j.neuron.2015.09.034\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMishra, R. K., Kim, S., Guzman, S. J. \u0026amp; Jonas, P. Symmetric spike timing-dependent plasticity at CA3\u0026ndash;CA3 synapses optimizes storage and recall in autoassociative networks. Nature Communications 7, 11552, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/ncomms11552\u003c/span\u003e\u003cspan address=\"10.1038/ncomms11552\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.nature.com/articles/ncomms11552#supplementary-information\u003c/span\u003e\u003cspan address=\"https://www.nature.com/articles/ncomms11552#supplementary-information\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEggermont, J. J. On the rate of maturation of sensory evoked potentials. Electroencephalogr Clin Neurophysiol 70, 293\u0026ndash;305, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/0013-4694(88)90048-x\u003c/span\u003e\u003cspan address=\"10.1016/0013-4694(88)90048-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1988).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWestlye, L. T., Walhovd, K. B., Bj\u0026oslash;rnerud, A., Due-T\u0026oslash;nnessen, P. \u0026amp; Fjell, A. M. Error-related negativity is mediated by fractional anisotropy in the posterior cingulate gyrus\u0026ndash;a study combining diffusion tensor imaging and electrophysiology in healthy adults. Cereb Cortex 19, 293\u0026ndash;304, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/cercor/bhn084\u003c/span\u003e\u003cspan address=\"10.1093/cercor/bhn084\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2009).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlshuaib, W. B. Progression of visual evoked potential abnormalities in multiple sclerosis and optic neuritis. Electromyogr Clin Neurophysiol 40, 243\u0026ndash;252 (2000).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKiiski, H. S. M. \u003cem\u003eet al.\u003c/em\u003e Delayed P100-Like Latencies in Multiple Sclerosis: A Preliminary Investigation Using Visual Evoked Spread Spectrum Analysis. \u003cem\u003ePloS one\u003c/em\u003e 11, e0146084-e0146084, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0146084\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0146084\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAgartz, I., Andersson, J. L. \u0026amp; Skare, S. Abnormal brain white matter in schizophrenia: a diffusion tensor imaging study. Neuroreport 12, 2251\u0026ndash;2254, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/00001756-200107200-00041\u003c/span\u003e\u003cspan address=\"10.1097/00001756-200107200-00041\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2001).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSzeszko, P. R. \u003cem\u003eet al.\u003c/em\u003e White Matter Abnormalities in First-Episode Schizophrenia or Schizoaffective Disorder: A Diffusion Tensor Imaging Study. American Journal of Psychiatry 162, 602\u0026ndash;605, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1176/appi.ajp.162.3.602\u003c/span\u003e\u003cspan address=\"10.1176/appi.ajp.162.3.602\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2005).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWei, W. \u003cem\u003eet al.\u003c/em\u003e Structural Covariance of Depth-Dependent Intracortical Myelination in the Human Brain and Its Application to Drug-Na\u0026iuml;ve Schizophrenia: A T1w/T2w MRI Study. Cerebral Cortex 32, 2373\u0026ndash;2384, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/cercor/bhab337\u003c/span\u003e\u003cspan address=\"10.1093/cercor/bhab337\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKelly, S. \u003cem\u003eet al.\u003c/em\u003e Widespread white matter microstructural differences in schizophrenia across 4322 individuals: results from the ENIGMA Schizophrenia DTI Working Group. Mol Psychiatry 23, 1261\u0026ndash;1269, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/mp.2017.170\u003c/span\u003e\u003cspan address=\"10.1038/mp.2017.170\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJorgensen, K. N. \u003cem\u003eet al.\u003c/em\u003e Increased MRI-based cortical grey/white-matter contrast in sensory and motor regions in schizophrenia and bipolar disorder. Psychol Med 46, 1971\u0026ndash;1985, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1017/s0033291716000593\u003c/span\u003e\u003cspan address=\"10.1017/s0033291716000593\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeitman, D. I. \u003cem\u003eet al.\u003c/em\u003e The neural substrates of impaired prosodic detection in schizophrenia and its sensorial antecedents. Am J Psychiatry 164, 474\u0026ndash;482, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1176/ajp.2007.164.3.474\u003c/span\u003e\u003cspan address=\"10.1176/ajp.2007.164.3.474\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2007).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHubl, D. \u003cem\u003eet al.\u003c/em\u003e Pathways That Make Voices: White Matter Changes in Auditory Hallucinations. Archives of General Psychiatry 61, 658\u0026ndash;668, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/archpsyc.61.7.658\u003c/span\u003e\u003cspan address=\"10.1001/archpsyc.61.7.658\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2004).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKn\u0026ouml;chel, C. \u003cem\u003eet al.\u003c/em\u003e Interhemispheric hypoconnectivity in schizophrenia: Fiber integrity and volume differences of the corpus callosum in patients and unaffected relatives. Neuroimage 59, 926\u0026ndash;934, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.neuroimage.2011.07.088\u003c/span\u003e\u003cspan address=\"10.1016/j.neuroimage.2011.07.088\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2012).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMulert, C. \u003cem\u003eet al.\u003c/em\u003e Hearing voices: A role of interhemispheric auditory connectivity? The World Journal of Biological Psychiatry 13, 153\u0026ndash;158, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3109/15622975.2011.570789\u003c/span\u003e\u003cspan address=\"10.3109/15622975.2011.570789\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2012).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWigand, M. \u003cem\u003eet al.\u003c/em\u003e Auditory verbal hallucinations and the interhemispheric auditory pathway in chronic schizophrenia. The World Journal of Biological Psychiatry 16, 31\u0026ndash;44, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3109/15622975.2014.948063\u003c/span\u003e\u003cspan address=\"10.3109/15622975.2014.948063\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNerland, S. \u003cem\u003eet al.\u003c/em\u003e Multisite reproducibility and test-retest reliability of the T1w/T2w-ratio: A comparison of processing methods. Neuroimage 245, 118709, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.neuroimage.2021.118709\u003c/span\u003e\u003cspan address=\"10.1016/j.neuroimage.2021.118709\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUddin, M. N., Figley, T. D., Solar, K. G., Shatil, A. S. \u0026amp; Figley, C. R. Comparisons between multi-component myelin water fraction, T1w/T2w ratio, and diffusion tensor imaging measures in healthy human brain structures. Scientific Reports 9, 2500, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41598-019-39199-x\u003c/span\u003e\u003cspan address=\"10.1038/s41598-019-39199-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShams, Z., Norris, D. G. \u0026amp; Marques, J. P. A comparison of in vivo MRI based cortical myelin mapping using T1w/T2w and R1 mapping at 3T. PLoS One 14, e0218089, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0218089\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0218089\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u003cem\u003eThe Journal of Neuroscience\u003c/em\u003e 31, 11597, doi:10.1523/JNEUROSCI.2180-11.2011 (2011).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNieuwenhuys, R. \u0026amp; Broere, C. A map of the human neocortex showing the estimated overall myelin content of the individual architectonic areas based on the studies of Adolf Hopf. Brain Structure and Function 222, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00429-016-1228-7\u003c/span\u003e\u003cspan address=\"10.1007/s00429-016-1228-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEickhoff, S. \u003cem\u003eet al.\u003c/em\u003e High-resolution MRI reflects myeloarchitecture and cytoarchitecture of human cerebral cortex. Hum Brain Mapp 24, 206\u0026ndash;215, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/hbm.20082\u003c/span\u003e\u003cspan address=\"10.1002/hbm.20082\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2005).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBeer, A. \u003cem\u003eet al.\u003c/em\u003e Tissue damage within normal appearing white matter in early multiple sclerosis: assessment by the ratio of T1- and T2-weighted MR image intensity. J Neurol 263, 1495\u0026ndash;1502, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00415-016-8156-6\u003c/span\u003e\u003cspan address=\"10.1007/s00415-016-8156-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCooper, G. \u003cem\u003eet al.\u003c/em\u003e Standardization of T1w/T2w Ratio Improves Detection of Tissue Damage in Multiple Sclerosis. Front Neurol 10, 334, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fneur.2019.00334\u003c/span\u003e\u003cspan address=\"10.3389/fneur.2019.00334\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRighart, R. \u003cem\u003eet al.\u003c/em\u003e Cortical pathology in multiple sclerosis detected by the T1/T2-weighted ratio from routine magnetic resonance imaging. Ann Neurol 82, 519\u0026ndash;529, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/ana.25020\u003c/span\u003e\u003cspan address=\"10.1002/ana.25020\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNakamura, K., Chen, J. T., Ontaneda, D., Fox, R. J. \u0026amp; Trapp, B. D. T1-/T2-weighted ratio differs in demyelinated cortex in multiple sclerosis. Annals of Neurology 82, 635\u0026ndash;639, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/ana.25019\u003c/span\u003e\u003cspan address=\"10.1002/ana.25019\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIwatani, J. \u003cem\u003eet al.\u003c/em\u003e Use of T1-weighted/T2-weighted magnetic resonance ratio images to elucidate changes in the schizophrenic brain. Brain and Behavior 5, e00399, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/brb3.399\u003c/span\u003e\u003cspan address=\"10.1002/brb3.399\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWei, W. \u003cem\u003eet al.\u003c/em\u003e Depth-dependent abnormal cortical myelination in first-episode treatment-na\u0026iuml;ve schizophrenia. Human brain mapping 41, 2782\u0026ndash;2793, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/hbm.24977\u003c/span\u003e\u003cspan address=\"10.1002/hbm.24977\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLong, P., Wan, G., Roberts, M. T. \u0026amp; Corfas, G. Myelin development, plasticity, and pathology in the auditory system. Dev Neurobiol 78, 80\u0026ndash;92, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/dneu.22538\u003c/span\u003e\u003cspan address=\"10.1002/dneu.22538\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRiecher-R\u0026ouml;ssler, A., Butler, S. \u0026amp; Kulkarni, J. Sex and gender differences in schizophrenic psychoses-a critical review. Arch Womens Ment Health 21, 627\u0026ndash;648, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00737-018-0847-9\u003c/span\u003e\u003cspan address=\"10.1007/s00737-018-0847-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbel, K. M., Drake, R. \u0026amp; Goldstein, J. M. Sex differences in schizophrenia. Int Rev Psychiatry 22, 417\u0026ndash;428, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3109/09540261.2010.515205\u003c/span\u003e\u003cspan address=\"10.3109/09540261.2010.515205\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2010).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMelynyte, S., Wang, G. Y. \u0026amp; Griskova-Bulanova, I. Gender effects on auditory P300: A systematic review. Int J Psychophysiol 133, 55\u0026ndash;65, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ijpsycho.2018.08.009\u003c/span\u003e\u003cspan address=\"10.1016/j.ijpsycho.2018.08.009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePentz, A. B. \u003cem\u003eet al.\u003c/em\u003e Mismatch negativity in schizophrenia spectrum and bipolar disorders: Group and sex differences and associations with symptom severity. Schizophr Res 261, 80\u0026ndash;93, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.schres.2023.09.012\u003c/span\u003e\u003cspan address=\"10.1016/j.schres.2023.09.012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHigashima, M. \u003cem\u003eet al.\u003c/em\u003e Neuropsychological correlates of an attention-related negative component elicited in an auditory oddball paradigm in schizophrenia. Neuropsychobiology 51, 177\u0026ndash;182, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1159/000085592\u003c/span\u003e\u003cspan address=\"10.1159/000085592\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2005).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSumich, A. \u003cem\u003eet al.\u003c/em\u003e N100 and P300 amplitude to Go and No\u0026ndash;Go variants of the auditory oddball in siblings discordant for schizophrenia. Schizophr Res 98, 265\u0026ndash;277, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.schres.2007.09.018\u003c/span\u003e\u003cspan address=\"10.1016/j.schres.2007.09.018\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2008).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRiel, H., Lee, J. B., Fisher, D. J. \u0026amp; Tibbo, P. G. Sex differences in event-related potential (ERP) waveforms of primary psychotic disorders: A systematic review. Int J Psychophysiol 145, 119\u0026ndash;124, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ijpsycho.2019.02.006\u003c/span\u003e\u003cspan address=\"10.1016/j.ijpsycho.2019.02.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrown, K. J., Gonsalvez, C. J., Harris, A. W. F., Williams, L. M. \u0026amp; Gordon, E. Target and non-target ERP disturbances in first episode vs. chronic schizophrenia. Clinical Neurophysiology 113, 1754\u0026ndash;1763, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S1388-2457(02)00290-0\u003c/span\u003e\u003cspan address=\"10.1016/S1388-2457(02)00290-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2002).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eForce, R. B., Venables, N. C. \u0026amp; Sponheim, S. R. An auditory processing abnormality specific to liability for schizophrenia. Schizophr Res 103, 298\u0026ndash;310, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.schres.2008.04.038\u003c/span\u003e\u003cspan address=\"10.1016/j.schres.2008.04.038\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2008).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSpencer, K. M. \u003cem\u003eet al.\u003c/em\u003e Abnormal Neural Synchrony in Schizophrenia. The Journal of Neuroscience 23, 7407, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1523/JNEUROSCI.23-19-07407.2003\u003c/span\u003e\u003cspan address=\"10.1523/JNEUROSCI.23-19-07407.2003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2003).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarendse, M. E. A. \u003cem\u003eet al.\u003c/em\u003e Sex and pubertal influences on the neurodevelopmental underpinnings of schizophrenia: A case for longitudinal research on adolescents. Schizophr Res 252, 231\u0026ndash;241, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.schres.2022.12.011\u003c/span\u003e\u003cspan address=\"10.1016/j.schres.2022.12.011\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOwens, S. J., Murphy, C. E., Purves-Tyson, T. D., Weickert, T. W. \u0026amp; Shannon Weickert, C. Considering the role of adolescent sex steroids in schizophrenia. Journal of Neuroendocrinology 30, e12538, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/jne.12538\u003c/span\u003e\u003cspan address=\"10.1111/jne.12538\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHoekstra, S. \u003cem\u003eet al.\u003c/em\u003e Sex differences in antipsychotic efficacy and side effects in schizophrenia spectrum disorder: results from the BeSt InTro study. NPJ Schizophr 7, 39, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41537-021-00170-3\u003c/span\u003e\u003cspan address=\"10.1038/s41537-021-00170-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSommer, I. E., Tiihonen, J., van Mourik, A., Tanskanen, A. \u0026amp; Taipale, H. The clinical course of schizophrenia in women and men\u0026mdash;a nation-wide cohort study. npj Schizophrenia 6, 12, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41537-020-0102-z\u003c/span\u003e\u003cspan address=\"10.1038/s41537-020-0102-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSlap\u0026oslash;, N. B. \u003cem\u003eet al.\u003c/em\u003e Auditory Cortex Thickness Is Associated With N100 Amplitude in Schizophrenia Spectrum Disorders. Schizophrenia Bulletin Open 4, sgad015, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/schizbullopen/sgad015\u003c/span\u003e\u003cspan address=\"10.1093/schizbullopen/sgad015\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSpitzer, R. L., Williams, J. B., Gibbon, M. \u0026amp; First, M. B. The Structured Clinical Interview for DSM-III-R (SCID). I: History, rationale, and description. Arch Gen Psychiatry 49, 624\u0026ndash;629, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/archpsyc.1992.01820080032005\u003c/span\u003e\u003cspan address=\"10.1001/archpsyc.1992.01820080032005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1992).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePedersen, G., Hagtvet, K. \u0026amp; Karterud, S. Generalizability studies of the Global Assessment of Functioning-Split version. Comprehensive psychiatry 48, 88\u0026ndash;94, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.comppsych.2006.03.008\u003c/span\u003e\u003cspan address=\"10.1016/j.comppsych.2006.03.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2007).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKay, S. R., Fiszbein, A. \u0026amp; Opler, L. A. The Positive and Negative Syndrome Scale (PANSS) for Schizophrenia. Schizophrenia Bulletin 13, 261\u0026ndash;276, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/schbul/13.2.261\u003c/span\u003e\u003cspan address=\"10.1093/schbul/13.2.261\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1987).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFischl, B. FreeSurfer. Neuroimage 62, 774\u0026ndash;781, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.neuroimage.2012.01.021\u003c/span\u003e\u003cspan address=\"10.1016/j.neuroimage.2012.01.021\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2012).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShinohara, R. T. \u003cem\u003eet al.\u003c/em\u003e Statistical normalization techniques for magnetic resonance imaging. NeuroImage. Clinical 6, 9\u0026ndash;19, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.nicl.2014.08.008\u003c/span\u003e\u003cspan address=\"10.1016/j.nicl.2014.08.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDestrieux, C., Fischl, B., Dale, A. \u0026amp; Halgren, E. Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature. Neuroimage 53, 1\u0026ndash;15, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.neuroimage.2010.06.010\u003c/span\u003e\u003cspan address=\"10.1016/j.neuroimage.2010.06.010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2010).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePereira, D. R. \u003cem\u003eet al.\u003c/em\u003e Effects of inter-stimulus interval (ISI) duration on the N1 and P2 components of the auditory event-related potential. Int J Psychophysiol 94, 311\u0026ndash;318, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ijpsycho.2014.09.012\u003c/span\u003e\u003cspan address=\"10.1016/j.ijpsycho.2014.09.012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDelorme, A. \u0026amp; Makeig, S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Methods 134, 9\u0026ndash;21, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jneumeth.2003.10.009\u003c/span\u003e\u003cspan address=\"10.1016/j.jneumeth.2003.10.009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2004).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBigdely-Shamlo, N., Mullen, T., Kothe, C., Su, K. M. \u0026amp; Robbins, K. A. The PREP pipeline: standardized preprocessing for large-scale EEG analysis. Front Neuroinform 9, 16, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fninf.2015.00016\u003c/span\u003e\u003cspan address=\"10.3389/fninf.2015.00016\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePion-Tonachini, L., Kreutz-Delgado, K. \u0026amp; Makeig, S. ICLabel: An automated electroencephalographic independent component classifier, dataset, and website. Neuroimage 198, 181\u0026ndash;197, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.neuroimage.2019.05.026\u003c/span\u003e\u003cspan address=\"10.1016/j.neuroimage.2019.05.026\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGraham, S. J., Langley, R. W., Bradshaw, C. M. \u0026amp; Szabadi, E. Effects of haloperidol and clozapine on prepulse inhibition of the acoustic startle response and the N1/P2 auditory evoked potential in man. Journal of Psychopharmacology 15, 243\u0026ndash;250, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/026988110101500411\u003c/span\u003e\u003cspan address=\"10.1177/026988110101500411\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2001).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThalheimer, W. \u0026amp; Cook, S. How to calculate effect sizes from published research: A simplified methodology. (2009).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrand, B. A., de Boer, J. N. \u0026amp; Sommer, I. E. C. Estrogens in schizophrenia: progress, current challenges and opportunities. Curr Opin Psychiatry 34, 228\u0026ndash;237, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/YCO.0000000000000699\u003c/span\u003e\u003cspan address=\"10.1097/YCO.0000000000000699\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDehan, C. P. \u0026amp; Jerger, J. Analysis of gender differences in the auditory brainstem response. Laryngoscope 100, 18\u0026ndash;24, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1288/00005537-199001000-00005\u003c/span\u003e\u003cspan address=\"10.1288/00005537-199001000-00005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1990).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcFadden, D., Hsieh, M. D., Garcia-Sierra, A. \u0026amp; Champlin, C. A. Differences by sex, ear, and sexual orientation in the time intervals between successive peaks in auditory evoked potentials. Hearing Research 270, 56\u0026ndash;64, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.heares.2010.09.008\u003c/span\u003e\u003cspan address=\"10.1016/j.heares.2010.09.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2010).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHall, J. W. \u003cem\u003eNew Handbook of Auditory Evoked Responses\u003c/em\u003e. (Pearson, 2007).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSnihur, A. W. K. \u0026amp; Hampson, E. Sex and ear differences in spontaneous and click-evoked otoacoustic emissions in young adults. Brain and Cognition 77, 40\u0026ndash;47, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.bandc.2011.06.004\u003c/span\u003e\u003cspan address=\"10.1016/j.bandc.2011.06.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2011).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNeuhoff, J. G., Planisek, R. \u0026amp; Seifritz, E. Adaptive sex differences in auditory motion perception: looming sounds are special. J Exp Psychol Hum Percept Perform 35, 225\u0026ndash;234, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1037/a0013159\u003c/span\u003e\u003cspan address=\"10.1037/a0013159\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2009).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLewald, J. Gender-specific hemispheric asymmetry in auditory space perception. Cognitive Brain Research 19, 92\u0026ndash;99, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.cogbrainres.2003.11.005\u003c/span\u003e\u003cspan address=\"10.1016/j.cogbrainres.2003.11.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2004).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eClint, E. K., Sober, E., Garland, T. \u0026amp; Rhodes, J. S. Male Superiority in Spatial Navigation: Adaptation or Side Effect? The Quarterly Review of Biology 87, 289\u0026ndash;313, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1086/668168\u003c/span\u003e\u003cspan address=\"10.1086/668168\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2012).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRuytjens, L. \u003cem\u003eet al.\u003c/em\u003e Functional sex differences in human primary auditory cortex. Eur J Nucl Med Mol Imaging 34, 2073\u0026ndash;2081, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00259-007-0517-z\u003c/span\u003e\u003cspan address=\"10.1007/s00259-007-0517-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2007).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCaras, M. L. Estrogenic modulation of auditory processing: A vertebrate comparison. Frontiers in Neuroendocrinology 34, 285\u0026ndash;299, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.yfrne.2013.07.006\u003c/span\u003e\u003cspan address=\"10.1016/j.yfrne.2013.07.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEldredge, L. \u0026amp; Salamy, A. Functional auditory development in preterm and full term infants. Early Human Development 45, 215\u0026ndash;228, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/0378-3782(96)01732-X\u003c/span\u003e\u003cspan address=\"10.1016/0378-3782(96)01732-X\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1996).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaurizi, M. \u003cem\u003eet al.\u003c/em\u003e Effects of sex on auditory brainstem responses in infancy and early childhood. Scand Audiol 17, 143\u0026ndash;146, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3109/01050398809042184\u003c/span\u003e\u003cspan address=\"10.3109/01050398809042184\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1988).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcFadden, D. Sexual orientation and the auditory system. Front Neuroendocrinol 32, 201\u0026ndash;213, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.yfrne.2011.02.001\u003c/span\u003e\u003cspan address=\"10.1016/j.yfrne.2011.02.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2011).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStenberg, A. E. \u003cem\u003eet al.\u003c/em\u003e Estrogen receptors in the normal adult and developing human inner ear and in Turner\u0026rsquo;s syndrome. Hearing Research 157, 87\u0026ndash;92, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0378-5955(01)00280-5\u003c/span\u003e\u003cspan address=\"10.1016/S0378-5955(01)00280-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2001).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAndreyko, J. L. \u0026amp; Jaffe, R. B. Use of a gonadotropin-releasing hormone agonist analogue for treatment of cyclic auditory dysfunction. Obstet Gynecol 74, 506\u0026ndash;509 (1989).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSouaid, J. P. \u0026amp; Rappaport, J. M. Fluctuating sensorineural hearing loss associated with the menstrual cycle. J Otolaryngol 30, 246\u0026ndash;250, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2310/7070.2001.20181\u003c/span\u003e\u003cspan address=\"10.2310/7070.2001.20181\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2001).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSennaroglu, G. \u0026amp; Belgin, E. Audiological findings in pregnancy. J Laryngol Otol 115, 617\u0026ndash;621, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1258/0022215011908603\u003c/span\u003e\u003cspan address=\"10.1258/0022215011908603\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2001).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchmidt, P. M., Flores Fda, T., Rossi, A. G. \u0026amp; Silveira, A. F. Hearing and vestibular complaints during pregnancy. Braz J Otorhinolaryngol 76, 29\u0026ndash;33, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1590/s1808-86942010000100006\u003c/span\u003e\u003cspan address=\"10.1590/s1808-86942010000100006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2010).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim, S. H., Kang, B. M., Chae, H. D. \u0026amp; Kim, C. H. The association between serum estradiol level and hearing sensitivity in postmenopausal women. Obstetrics \u0026amp; Gynecology 99, 726\u0026ndash;730, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0029-7844(02)01963-4\u003c/span\u003e\u003cspan address=\"10.1016/S0029-7844(02)01963-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2002).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnderer, P. \u003cem\u003eet al.\u003c/em\u003e Effects of hormone replacement therapy on perceptual and cognitive event-related potentials in menopausal insomnia. Psychoneuroendocrinology 28, 419\u0026ndash;445, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0306-4530(02)00032-X\u003c/span\u003e\u003cspan address=\"10.1016/S0306-4530(02)00032-X\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2003).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhaliq, F., Tandon, O. P. \u0026amp; Goel, N. Auditory evoked responses in postmenopausal women on hormone replacement therapy. Indian J Physiol Pharmacol 47, 393\u0026ndash;399 (2003).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHultcrantz, M. Ear and hearing problems in Turner's syndrome. Acta Otolaryngol 123, 253\u0026ndash;257, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/00016480310001097\u003c/span\u003e\u003cspan address=\"10.1080/00016480310001097\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2003).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWharton, J. A. \u0026amp; Church, G. T. Influence of menopause on the auditory brainstem response. Audiology 29, 196\u0026ndash;201, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3109/00206099009072850\u003c/span\u003e\u003cspan address=\"10.3109/00206099009072850\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1990).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eManey, D. L., Goode, C. T., Lange, H. S., Sanford, S. E. \u0026amp; Solomon, B. L. Estradiol modulates neural responses to song in a seasonal songbird. Journal of Comparative Neurology 511, 173\u0026ndash;186, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/cne.21830\u003c/span\u003e\u003cspan address=\"10.1002/cne.21830\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2008).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLong, K. L. P., Breton, J. M., Barraza, M. K., Perloff, O. S. \u0026amp; Kaufer, D. Hormonal Regulation of Oligodendrogenesis I: Effects across the Lifespan. Biomolecules 11, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/biom11020283\u003c/span\u003e\u003cspan address=\"10.3390/biom11020283\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMitchell, T. W. \u003cem\u003eet al.\u003c/em\u003e The prevalence of MS in the United States. Neurology 92, e1029, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1212/WNL.0000000000007035\u003c/span\u003e\u003cspan address=\"10.1212/WNL.0000000000007035\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eConfavreux, C., Hutchinson, M., Hours, M. M., Cortinovis-Tourniaire, P. \u0026amp; Moreau, T. Rate of Pregnancy-Related Relapse in Multiple Sclerosis. New England Journal of Medicine 339, 285\u0026ndash;291, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1056/NEJM199807303390501\u003c/span\u003e\u003cspan address=\"10.1056/NEJM199807303390501\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1998).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu, Y. C., Hill, R. A., Gogos, A. \u0026amp; van den Buuse, M. Sex differences and the role of estrogen in animal models of schizophrenia: Interaction with BDNF. Neuroscience 239, 67\u0026ndash;83, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.neuroscience.2012.10.024\u003c/span\u003e\u003cspan address=\"10.1016/j.neuroscience.2012.10.024\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGodar, S. C. \u0026amp; Bortolato, M. Gene-sex interactions in schizophrenia: focus on dopamine neurotransmission. Front Behav Neurosci 8, 71, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fnbeh.2014.00071\u003c/span\u003e\u003cspan address=\"10.3389/fnbeh.2014.00071\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBristow, G. C., Bostrom, J. A., Haroutunian, V. \u0026amp; Sodhi, M. S. Sex differences in GABAergic gene expression occur in the anterior cingulate cortex in schizophrenia. Schizophr Res 167, 57\u0026ndash;63, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.schres.2015.01.025\u003c/span\u003e\u003cspan address=\"10.1016/j.schres.2015.01.025\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrothe, B. \u0026amp; Koch, U. Dynamics of binaural processing in the mammalian sound localization pathway\u0026ndash;the role of GABA(B) receptors. Hear Res 279, 43\u0026ndash;50, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.heares.2011.03.013\u003c/span\u003e\u003cspan address=\"10.1016/j.heares.2011.03.013\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2011).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMayko, Z. M., Roberts, P. D. \u0026amp; Portfors, C. V. Inhibition shapes selectivity to vocalizations in the inferior colliculus of awake mice. Front Neural Circuits 6, 73, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fncir.2012.00073\u003c/span\u003e\u003cspan address=\"10.3389/fncir.2012.00073\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2012).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRudick, C. N. \u0026amp; Woolley, C. S. Estrogen regulates functional inhibition of hippocampal CA1 pyramidal cells in the adult female rat. J Neurosci 21, 6532\u0026ndash;6543, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1523/jneurosci.21-17-06532.2001\u003c/span\u003e\u003cspan address=\"10.1523/jneurosci.21-17-06532.2001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2001).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHakak, Y. \u003cem\u003eet al.\u003c/em\u003e Genome-wide expression analysis reveals dysregulation of myelination-related genes in chronic schizophrenia. Proc Natl Acad Sci U S A 98, 4746\u0026ndash;4751, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1073/pnas.081071198\u003c/span\u003e\u003cspan address=\"10.1073/pnas.081071198\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2001).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVikhreva, O. V., Rakhmanova, V. I., Orlovskaya, D. D. \u0026amp; Uranova, N. A. Ultrastructural alterations of oligodendrocytes in prefrontal white matter in schizophrenia: A post-mortem morphometric study. Schizophr Res 177, 28\u0026ndash;36, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.schres.2016.04.023\u003c/span\u003e\u003cspan address=\"10.1016/j.schres.2016.04.023\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKolomeets, N. S. \u0026amp; Uranova, N. A. Reduced oligodendrocyte density in layer 5 of the prefrontal cortex in schizophrenia. Eur Arch Psychiatry Clin Neurosci 269, 379\u0026ndash;386, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00406-018-0888-0\u003c/span\u003e\u003cspan address=\"10.1007/s00406-018-0888-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKubicki, M. \u003cem\u003eet al.\u003c/em\u003e A review of diffusion tensor imaging studies in schizophrenia. J Psychiatr Res 41, 15\u0026ndash;30, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jpsychires.2005.05.005\u003c/span\u003e\u003cspan address=\"10.1016/j.jpsychires.2005.05.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2007).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEllison-Wright, I. \u0026amp; Bullmore, E. Meta-analysis of diffusion tensor imaging studies in schizophrenia. Schizophr Res 108, 3\u0026ndash;10, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.schres.2008.11.021\u003c/span\u003e\u003cspan address=\"10.1016/j.schres.2008.11.021\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2009).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFlynn, S. W. \u003cem\u003eet al.\u003c/em\u003e Abnormalities of myelination in schizophrenia detected in vivo with MRI, and post-mortem with analysis of oligodendrocyte proteins. Molecular Psychiatry 8, 811\u0026ndash;820, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/sj.mp.4001337\u003c/span\u003e\u003cspan address=\"10.1038/sj.mp.4001337\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2003).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTkachev, D. \u003cem\u003eet al.\u003c/em\u003e Oligodendrocyte dysfunction in schizophrenia and bipolar disorder. Lancet 362, 798\u0026ndash;805, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0140-6736(03)14289-4\u003c/span\u003e\u003cspan address=\"10.1016/S0140-6736(03)14289-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2003).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUranova, N. A., Vikhreva, O. V., Rachmanova, V. I. \u0026amp; Orlovskaya, D. D. Ultrastructural alterations of myelinated fibers and oligodendrocytes in the prefrontal cortex in schizophrenia: a postmortem morphometric study. \u003cem\u003eSchizophr Res Treatment\u003c/em\u003e 2011, 325789\u0026ndash;325789, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1155/2011/325789\u003c/span\u003e\u003cspan address=\"10.1155/2011/325789\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2011).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLang, E. J. \u0026amp; Rosenbluth, J. Role of Myelination in the Development of a Uniform Olivocerebellar Conduction Time. J Neurophysiol 89, 2259\u0026ndash;2270, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1152/jn.00922.2002\u003c/span\u003e\u003cspan address=\"10.1152/jn.00922.2002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2003).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUhlhaas, P. J. \u0026amp; Singer, W. Abnormal neural oscillations and synchrony in schizophrenia. Nat Rev Neurosci 11, 100\u0026ndash;113, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/nrn2774\u003c/span\u003e\u003cspan address=\"10.1038/nrn2774\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2010).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGlasser, M. F., Goyal, M. S., Preuss, T. M., Raichle, M. E. \u0026amp; Van Essen, D. C. Trends and properties of human cerebral cortex: correlations with cortical myelin content. Neuroimage 93 Pt 2, 165\u0026ndash;175, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.neuroimage.2013.03.060\u003c/span\u003e\u003cspan address=\"10.1016/j.neuroimage.2013.03.060\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUddin, M. N., Figley, T. D., Solar, K. G., Shatil, A. S. \u0026amp; Figley, C. R. Comparisons between multi-component myelin water fraction, T1w/T2w ratio, and diffusion tensor imaging measures in healthy human brain structures. Sci Rep 9, 2500, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41598-019-39199-x\u003c/span\u003e\u003cspan address=\"10.1038/s41598-019-39199-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSandrone, S. \u003cem\u003eet al.\u003c/em\u003e Mapping myelin in white matter with T1-weighted/T2-weighted maps: discrepancy with histology and other myelin MRI measures. Brain Struct Funct 228, 525\u0026ndash;535, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00429-022-02600-z\u003c/span\u003e\u003cspan address=\"10.1007/s00429-022-02600-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSellgren, C. M. \u003cem\u003eet al.\u003c/em\u003e Increased synapse elimination by microglia in schizophrenia patient-derived models of synaptic pruning. Nat Neurosci 22, 374\u0026ndash;385, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41593-018-0334-7\u003c/span\u003e\u003cspan address=\"10.1038/s41593-018-0334-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePaolicelli, R. C. \u003cem\u003eet al.\u003c/em\u003e Synaptic pruning by microglia is necessary for normal brain development. Science 333, 1456\u0026ndash;1458, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1126/science.1202529\u003c/span\u003e\u003cspan address=\"10.1126/science.1202529\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2011).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGlausier, J. R. \u0026amp; Lewis, D. A. Dendritic spine pathology in schizophrenia. Neuroscience 251, 90\u0026ndash;107, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.neuroscience.2012.04.044\u003c/span\u003e\u003cspan address=\"10.1016/j.neuroscience.2012.04.044\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGlantz, L. A. \u0026amp; Lewis, D. A. Decreased dendritic spine density on prefrontal cortical pyramidal neurons in schizophrenia. Arch Gen Psychiatry 57, 65\u0026ndash;73, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/archpsyc.57.1.65\u003c/span\u003e\u003cspan address=\"10.1001/archpsyc.57.1.65\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2000).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHirano, Y. \u003cem\u003eet al.\u003c/em\u003e Auditory Cortex Volume and Gamma Oscillation Abnormalities in Schizophrenia. Clinical EEG and Neuroscience 51, 244\u0026ndash;251, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/1550059420914201\u003c/span\u003e\u003cspan address=\"10.1177/1550059420914201\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede la Iglesia-Vaya, M. \u003cem\u003eet al.\u003c/em\u003e Abnormal synchrony and effective connectivity in patients with schizophrenia and auditory hallucinations. NeuroImage: Clinical 6, 171\u0026ndash;179, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.nicl.2014.08.027\u003c/span\u003e\u003cspan address=\"10.1016/j.nicl.2014.08.027\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFord, J. M., Roach, B. J., Faustman, W. O. \u0026amp; Mathalon, D. H. Synch before you speak: auditory hallucinations in schizophrenia. Am J Psychiatry 164, 458\u0026ndash;466, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1176/ajp.2007.164.3.458\u003c/span\u003e\u003cspan address=\"10.1176/ajp.2007.164.3.458\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2007).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMulert, C., Kirsch, V., Pascual-Marqui, R., McCarley, R. W. \u0026amp; Spencer, K. M. Long-range synchrony of gamma oscillations and auditory hallucination symptoms in schizophrenia. Int J Psychophysiol 79, 55\u0026ndash;63, doi:10.1016/j.ijpsycho.2010.08.004 (2011).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRosburg, T. Auditory N100 gating in patients with schizophrenia: A systematic meta-analysis. Clinical Neurophysiology 129, 2099\u0026ndash;2111, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.clinph.2018.07.012\u003c/span\u003e\u003cspan address=\"10.1016/j.clinph.2018.07.012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrockhaus-Dumke, A., Mueller, R., Faigle, U. \u0026amp; Klosterkoetter, J. Sensory gating revisited: Relation between brain oscillations and auditory evoked potentials in schizophrenia. Schizophr Res 99, 238\u0026ndash;249, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.schres.2007.10.034\u003c/span\u003e\u003cspan address=\"10.1016/j.schres.2007.10.034\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2008).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMazhari, S., Price, G., Waters, F., Dragović, M. \u0026amp; Jablensky, A. Evidence of abnormalities in mid-latency auditory evoked responses (MLAER) in cognitive subtypes of patients with schizophrenia. Psychiatry Research 187, 317\u0026ndash;323, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.psychres.2011.01.003\u003c/span\u003e\u003cspan address=\"10.1016/j.psychres.2011.01.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2011).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBeasley, C. M. \u003cem\u003eet al.\u003c/em\u003e Olanzapine versus placebo and haloperidol: Acute phase results of the North American double-blind olanzapine trial. Neuropsychopharmacology 14, 111\u0026ndash;123, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/0893-133X(95)00069-P\u003c/span\u003e\u003cspan address=\"10.1016/0893-133X(95)00069-P\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1996).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaxwell, C. R. \u003cem\u003eet al.\u003c/em\u003e Effects of Chronic Olanzapine and Haloperidol Differ on the Mouse N1 Auditory Evoked Potential. Neuropsychopharmacology 29, 739\u0026ndash;746, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/sj.npp.1300376\u003c/span\u003e\u003cspan address=\"10.1038/sj.npp.1300376\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2004).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaribeau-Braun, J., Picton, T. W. \u0026amp; Gosselin, J.-Y. Schizophrenia: A Neurophysiological Evaluation of Abnormal Information Processing. Science 219, 874\u0026ndash;876, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1126/science.6823555\u003c/span\u003e\u003cspan address=\"10.1126/science.6823555\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1983).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarrett, K., McCallum, W. C. \u0026amp; Pocock, P. V. Brain indicators of altered attention and information processing in schizophrenic patients. Br J Psychiatry 148, 414\u0026ndash;420, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1192/bjp.148.4.414\u003c/span\u003e\u003cspan address=\"10.1192/bjp.148.4.414\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1986).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJ\u0026oslash;rgensen, K. N. \u003cem\u003eet al.\u003c/em\u003e Increased MRI-based cortical grey/white-matter contrast in sensory and motor regions in schizophrenia and bipolar disorder. Psychological Medicine 46, 1971\u0026ndash;1985, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1017/S0033291716000593\u003c/span\u003e\u003cspan address=\"10.1017/S0033291716000593\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2016).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-3906183/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3906183/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSchizophrenia spectrum disorders (SCZ\u003csub\u003espect\u003c/sub\u003e) are associated with altered function in the auditory cortex (AC), indicated by reduced N100 amplitude of the auditory evoked potential (AEP). While the neural substrate behind reduced N100 amplitude remains elusive, myelination in the AC may play a role. We compared N100 amplitude and magnetic resonance imaging (MRI) T1 weighted and T2 weighted ratio (T1w/T2w-ratio) as a proxy of myelination, in the primary AC (AC1) and secondary AC (AC2) between SCZ\u003csub\u003espect\u003c/sub\u003e (n\u0026thinsp;=\u0026thinsp;33, 48% women) and healthy controls (HC, n\u0026thinsp;=\u0026thinsp;144, 49% women). Further, we examined associations between N100 amplitude and T1w/T2w-ratios in SCZ\u003csub\u003espect\u003c/sub\u003e and HC. We finally explored N100 amplitude and T1w/T2w-ratios in the AC1/AC2 and association between N100 amplitude and T1w/T2w-ratios between male and female SCZ\u003csub\u003espect\u003c/sub\u003e and HC. N100 amplitude did not differ between SCZ\u003csub\u003espect\u003c/sub\u003e and HC or between female SCZ\u003csub\u003espect\u003c/sub\u003e and female HC, but was significantly reduced in male SCZ\u003csub\u003espect\u003c/sub\u003e compared to male HC (est\u0026thinsp;=\u0026thinsp;4.3, se\u0026thinsp;=\u0026thinsp;1.63, t\u0026thinsp;=\u0026thinsp;2.63, p\u0026thinsp;=\u0026thinsp;0.010). Further, T1w/T2w ratios in the AC1/AC2 did not differ between any groups. Finally, N100 amplitude was not associated with T1/T2-ratios in the AC1/AC2 in any groups. Reduced N100 amplitude in male SCZ\u003csub\u003espect\u003c/sub\u003e compared to male HC, suggest that sex-specific effects should be considered in research on SCZ\u003csub\u003espect\u003c/sub\u003e neurophysiology. Our findings did not support the hypothesis that reduced myelination in the AC1/AC2, as indexed by T1w/T2w-ratio, underlies N100 abnormalities in SCZ\u003csub\u003espect\u003c/sub\u003e. However, more precise estimates of intracortical myelin are needed to confirm this.\u003c/p\u003e","manuscriptTitle":"Relationship between N100 amplitude and T1w/T2w-ratio in the auditory cortex in schizophrenia spectrum disorders","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-08 19:17:56","doi":"10.21203/rs.3.rs-3906183/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"00aea01c-d813-4221-831b-b3edaf70e163","owner":[],"postedDate":"February 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":28606383,"name":"Biological sciences/Neuroscience"},{"id":28606384,"name":"Health sciences/Diseases/Psychiatric disorders/Schizophrenia"}],"tags":[],"updatedAt":"2026-04-01T07:29:30+00:00","versionOfRecord":{"articleIdentity":"rs-3906183","link":"https://doi.org/10.1038/s41537-025-00715-w","journal":{"identity":"schizophrenia","isVorOnly":true,"title":"Schizophrenia"},"publishedOn":"2026-01-17 05:00:00","publishedOnDateReadable":"January 17th, 2026"},"versionCreatedAt":"2024-02-08 19:17:56","video":"","vorDoi":"10.1038/s41537-025-00715-w","vorDoiUrl":"https://doi.org/10.1038/s41537-025-00715-w","workflowStages":[]},"version":"v1","identity":"rs-3906183","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3906183","identity":"rs-3906183","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}