Effect of antipsychotic on mismatch negativity amplitude and evoked theta power in drug- naïve patients with schizophrenia

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There is evidence suggesting a correlation between increased dopaminergic activity and reduced MMN amplitude, but there is no consensus on whether antipsychotic medications can improve MMN deficit in schizophrenia. Methods We conducted clinical assessments, cognitive function tests, and EEG data collection and analysis on 31 drug-naïve patients with schizophrenia. Comprehensive evaluation tools such as PANSS and MCCB. MMN amplitude was analyzed by event-related potential (ERP) approaches, evoked theta power was analyzed by event-related spectral perturbation (ERSP) approaches. Results Our findings indicate that antipsychotic treatment significantly improved clinical symptoms, as evidenced by reductions in PANSS positive, negative, general symptoms, and total scores (all p < 0.001). Cognitive function improvements were observed in language learning, working memory, and overall MCCB scores (p < 0.05), although other cognitive domains showed no significant changes. However, no significant improvements were noted in MMN amplitude and evoke theta power after four weeks of antipsychotic treatment (p > 0.05). Conclusion These results suggest that while antipsychotic medications effectively alleviate clinical symptoms, their impact on MMN amplitude and evoke theta power deficit is limited in the short term. Moreover, the amelioration of cognitive impairment in individuals with schizophrenia is not readily discernible, and it cannot be discounted that the enhancement observed in language acquisition and working memory may be attributed to a learning effect. These findings underscore the complexity of the neurobiological mechanisms involved and highlight the need for further research to optimize individualized treatment strategies for schizophrenia. Schizophrenia Mismatch negativity Time-frequency analysis Antipsychotic Figures Figure 1 1. Introduction Schizophrenia is a severe mental disorder that significantly impacts patients' cognitive functions, social capabilities, and overall quality of life. With a prevalence rate of approximately 1%, schizophrenia imposes substantial psychological and economic burdens on patients and society [ 1 ] . More than 50% of those observed experience intermittent yet persistent psychiatric problems, while approximately 20% suffer from lifelong chronic clinical symptoms and disability. This not only causes severe harm to the individuals but also imposes a significant burden on society, with the anticipated disease burden expected to more than double by 2030 [ 2 ] . Therefore, reducing the increasing disease burden of mental disorders such as schizophrenia has become a priority in mental health and is also important for improving the social functioning of patients. However, the current prevention, control, and diagnosis of schizophrenia are not ideal mainly due to difficulties in early identification and intervention in patients with schizophrenia, resulting in poor prognosis for these individuals and an inability to effectively restore their social functions [ 3 ] . Mismatch negativity (MMN) is an event-related potential (ERP) that occurs when a stimulus with different properties, such as duration (dMMN) or frequency (fMMN), is presented together with a standard stimulus that is more frequently presented [ 4 ]. MMN serves as an indicator of a memory-driven cerebral auditory sensory reaction to identifiable alterations in a sequence of stimuli, even when attention is not present [ 5 ] . The MMN component of the evoked potential has been discovered to offer valuable insights into the importance of regularity sensitivity in perception and cognition [ 6 ] . The MMN paradigm has gained considerable attention in recent years due to its capacity to provide insights into the underlying mechanisms of sensory information processing by detecting deviations [ 7 , 8 ] . The correlation between MMN and both neurocognitive abilities and functional outcomes among individuals diagnosed with schizophrenia has been well-established in prior research [ 9 , 10 ] . Cognitive impairment constitutes a fundamental manifestation of schizophrenia [ 11 ] . Revised sentence: Previous research has consistently demonstrated that individuals with schizophrenia exhibit cognitive deficits across multiple domains, consistently performing 0.5–1.75 standard deviations below the mean of healthy individuals on neuropsychological tasks assessing various cognitive functions [ 12 ] . The recovery of cognitive function plays a pivotal role in determining the reintegration of individuals with schizophrenia into society. Biomarkers are indispensable for achieving precision medicine in schizophrenia, and among various neurophysiological and neurocognitive measures, MMN reduction stands out as one of the most robust findings in patients with this disorder. Our previous study revealed a significant association between MMN amplitude impairment in individuals with schizophrenia and deficits in word learning and working memory within the cognitive domain [ 13 ] . Previous study has demonstrated the lack of efficacy of antipsychotic medication in ameliorating MMN deficits among individuals diagnosed with schizophrenia [ 14 ] . However, some studies have also found that antipsychotic medication improves MMN impairment in schizophrenia [ 15 ] . The cause of the variability in these results is unknown, and further follow-up studies are required. Furthermore, previous follow-up studies investigating antipsychotic therapy for MMN deficiency in patients with schizophrenia have primarily focused on assessing the amplitude of MMN. Relative to MMN amplitude, which can only provide local potential information on evoked potentials, event related spectral perturbation (ERSP) analysis can provide both potential-level and molecular-level information, in addition to more complex physiological information [ 16 ] . It has been shown that the ERSP evoked power of auditory MMN is mainly concentrated in the theta band (4–7 Hz), and the presence of impaired ERSP energy in the theta band evoked by MMN was found to be a biomarker of schizophrenia [ 17 ] . Our group also found that impaired evoked theta power deficits in schizophrenia was associated with working memory [ 13 ] . However, there are no current studies on follow-up studies of antipsychotic drugs inducing theta power deficits in patients with schizophrenia. In summary, both MMN amplitude and evoked theta power can serve as potential biomarkers for precise interventions targeting cognitive impairment in schizophrenia; however, the effect of antipsychotics on MMN wave amplitude remains inconclusive based on previous studies, and there is a lack of follow-up research investigating the impact of antipsychotic treatment on evoked theta power. In this study, we administered a 4-week course of antipsychotic treatment to drug-naïve patients with schizophrenia in order to investigate the impact of antipsychotics on both MMN amplitude and evoked theta power, aiming to elucidate whether antipsychotics can effectively ameliorate these deficits. The findings from this research have the potential to inform the development of more efficacious therapeutic strategies for managing cognitive deficits in schizophrenia, ultimately enhancing patient outcomes. 2. Method and material 2.1. Participants Thirty-one drug-naïve individuals diagnosed with schizophrenia were recruited as participants from Beijing Anding Hospital, Capital Medical University. The inclusion criteria for this study involved the validation of diagnoses using the Structured Clinical Interview for DSM-IV (SCID). Participants ranged in age from 18 to 45 years and all had IQ scores equal to or greater than 70. Exclusion criteria encompassed hearing impairments, learning difficulties, neurological disorders, a history of seizures or head injuries, prior electroconvulsive therapy, and substance abuse. This study obtained approval from the Ethics Committee of Beijing Anding Hospital and all subjects provided informed consent before participating. 2.2. Procedures The auditory stimuli comprised a series of binaural tones (825 trials) presented in a random sequence with a stimulus onset asynchrony ranging from 500 to 550 ms. The majority of the trials (675, accounting for 82%) featured standard tones characterized by a frequency of 1000 Hz, sound intensity level of 75 dB, and duration of 50 ms. In contrast, deviant tones included variations in both frequency and duration. Frequency deviants (75 trials, representing 9% of the total) had a frequency of 1500 Hz, sound intensity level of 75 dB, and duration of 50 ms. Duration deviants (another set comprising approximately 9% or 75 trials overall) maintained the same frequency as the standard tones but had an extended duration lasting for 100 ms instead. To establish baseline standards at the experiment's outset, we employed the initial set consisting of fifteen stimuli as our reference. 2.3. Electroencephalogram (EEG) data acquisition and processing Electroencephalogram (EEG) data were recorded from all participants using a 128-channel electrode system (Electrical Geodesics, Inc., Oregon, USA) with standard reference and grounding procedures. The signal impedance was adjusted to be ≥ 50 KΩ while maintaining a sampling rate of 1000 Hz. During the experiment, subjects were seated comfortably in a specially designed room that minimized potential external factors that could affect the study. The test consisted of three sections separated by breaks lasting for 60 seconds each. For the ERP analyses, we employed EEGLAB 14.1.1b ( http://sccn.ucsd.edu/eeglab/ ), a MATLAB-based tool for neural electrophysiological analysis. The EEG data were processed using a finite impulse response filter with a bandpass range of 0.1–40 Hz to ensure optimal signal quality. To eliminate power frequency noise at 50 Hz, notch processing was applied as an additional step in the preprocessing pipeline. We adopted a global brain average reference as the new electrode configuration to enhance spatial comparability across subjects and minimize potential bias introduced by individual differences in scalp topography. Independent component analysis (ICA) was utilized to effectively remove artifacts caused by eye movement, ensuring accurate interpretation of the underlying neural activity patterns. Segmentation of the EEG data encompassed a time window from 100 ms before stimulus onset to 500 ms after stimulus initiation, allowing us to capture both pre-stimulus baseline activity and post-stimulus responses within an appropriate temporal context for further analysis purposes. MMN waveforms were derived by subtracting the deviant stimulus from the standard stimulus specifically at the frontal midline (Fz) electrode location. For the analysis of evoked (average) power, we employed the short-time Fourier transformation (STFT) method in MATLAB (MathWorks, Natick, MA, USA) to convert ERP waves. The segmented EEG signal underwent continuous wavelet transformation over time. The EEG data spanned from 100 ms prior to stimulus initiation to 500 ms after stimulus onset relative to presentation time. A frequency range of 1–20 Hz was applied for the wavelet transformation. Furthermore, temporal power values corresponding to each frequency point were averaged across trials to obtain an EEG power time-frequency distribution on a channel-by-channel basis. For statistical analysis purposes, maximum power values within each subject's theta frequency band of 4–7 Hz and between 100–250 ms were extracted. This range represents the primary active frequency band of neural oscillation in response to the standard stimulus. 2.4. Clinical, intelligence quotient and neuropsychological assessment The clinical symptoms of each patient were evaluated with the Positive and Negative Symptom Scale (PANSS, Chinese version), which was previously described. The Chinese intelligence quotient (IQ) test tool was revised short form the Wechsler adult intelligence scale-revised, and the four included subsets for this evaluation were information, similarities, picture completion, and block design [ 18 ] .The MATRICS consensus cognitive battery (MCCB, Chinese version) was used to evaluated cognitive deficits in patients with schizophrenia and healthy controls [ 19 ] . 2.5. Statistical analysis The statistical analysis was performed using SPSS 20.0 (IBM, Chicago, IL, USA). To compare PANSS scores, MCCB scores, amplitudes of MMN and evoke power between the baseline and 4-week treatment sessions, we utilized paired-samples T tests. A significance level of p < 0.05 was employed for the statistical analysis. 3. Results 3.1 Demographics and Clinical Characteristics The mean age of individuals diagnosed with schizophrenia was 27.5 ± 5.7 years, with a majority (77%) being male. The average duration of education for these individuals was 13.9 ± 3.5 years, while the mean age at onset of symptoms was recorded as 25.6 ± 5.3 years, and the average illness duration stood at 26.4 ± 30.7 months. Furthermore, the conversion to olanzapine-equivalent dosage resulted in an average daily intake of 15.9 ± 6.3 mg/dose per patient's requirement. The detailed results are shown in Table 1 . Table 1 General demographic and clinical data characteristics Variables Patients (N = 31) Age (mean ± SD, year) 27.5 ± 5.7 Sex (male / %) 24 / 77% Education years (mean ± SD, year) 13.9 ± 3.5 Onset age (mean ± SD, year) 25.6 ± 5.3 Course (mean ± SD, month) 26.4 ± 30.7 olanzapine-equivalent dosage (mean ± SD, mg/d) 15.9 ± 6.3 3.2 Comparisons of PANSS before and after antipsychotics treatment After a 4-week treatment regimen with a single antipsychotic medication, there was a significant improvement in the symptoms of patients diagnosed with schizophrenia. Specifically, statistically significant differences were observed in PANSS positive symptom scores (df = 30, t = 11.991, p < 0.001), negative symptom scores (df = 30, t = 8.650, p < 0.001), general symptom scores (df = 30, t = 14.086, p < 0.001), and the overall PANSS score (df = 30, t = 16.898 p < 0.001). The detailed results are shown in Table 2 . Table 2 PANSS scores before and after antipsychotic treatment Variables Baseline After 4-week treatments Paired-samples T tests Mean SD Mean SD df t p (2-tailed) Positive symptom scale 21.2 4.1 10.7 2.4 30 11.991 < 0.001 Negative symptom scale 17.9 5.3 11.7 3.1 30 8.650 < 0.001 Total psychopathology scale 38.7 4.3 25.4 3.1 30 14.086 < 0.001 PANSS (total scores) 77.8 9.5 47.5 6.6 30 16.898 < 0.001 3.3 Comparisons of MCCB before and after antipsychotics treatment The neurocognitive treatment using MCCB demonstrated significant improvements in word learning (df = 30, t = -3.393, p = 0.002), working memory (df = 30, t = -3.766, p = 0.001), and total MCCB cognitive score (df = 30, t = -3.042, p = 0.005). However, no significant improvements were observed in other cognitive domains. Specific detailed results are shown in Table 3 . Table 3 MCCB scores before and after antipsychotic treatment Variables Baseline After 4-week treatments Paired-samples T tests Mean SD Mean SD df t p (2-tailed) Speed of processing 36.9 6.7 38.6 7.3 30 -1.349 0.188 Attention/Vigilance 34.1 8.7 34.5 11.5 30 -0.238 0.814 Working memory 39.7 8.9 45.2 7.1 30 -3.766 0.001 Verbal learning 37.5 9.3 42.1 9.6 30 -3.393 0.002 Visual learning 44.3 11.2 48.2 11.8 30 -1.829 0.077 Reasoning and problem solving 39.4 12.1 42.7 10.9 30 -1.864 0.072 Social cognition 32.9 7.9 33.6 10.0 30 -0.389 0.700 MCCB combine 37.7 5.7 40.7 6.1 30 -3.042 0.005 3.4 Comparisons of MMN index and after antipsychotics treatment After 4 weeks of monotherapy with antipsychotic medication, there was no statistically significant improvement observed in the amplitude of MMN wave frequency (df = 30, t = -1.043, p = 0.305), duration wave amplitude (df = 30, t = -0.403, p = 0.690), and evoke theta power (df = 30, t = -1.242, p = 0.224). Detailed results are shown in Table 4 and Fig. 1 . Table 4 Mismatch negativity amplitudes and evoke power before and after antipsychotic treatment Variables Baseline After 4-week treatments Paired-samples T tests Mean SD Mean SD df t p (2-tail) Frequency MMN (µV) -0.7911 0.2884 -0.7443 0.2951 30 -1.043 0.305 Duration MMN (µV) -1.6588 0.5394 -1.6212 0.5370 30 -0.403 0.690 Evoke theta power 0.0381 0.0338 0.0427 0.0364 30 -1.242 0.224 4. Discussion This study focuses on the neurocognitive performance and auditory evoked potentials, specifically MMN amplitude and its related frequency band analysis, in drug-naïve patients with schizophrenia before and after antipsychotic treatment. Previous studies investigating the effects of antipsychotic drugs on MMN indexes in schizophrenia have predominantly focused on amplitude, whereas this study represents the first attempt to examine the influence of antipsychotic drugs on MMN evoked power in individuals with schizophrenia. Notably, our findings reveal that while antipsychotic treatment significantly improves clinical symptoms, its impact on cognitive function and neurophysiological markers such as MMN amplitude and theta evoke power is limited. Cognitive dysfunction in patients with schizophrenia is considered a significant pathological manifestation, persisting even after treatment of core clinical symptoms such as hallucinations and delusions. Moreover, it closely correlates with the functional outcome of patients. The process of cognitive change over the course of schizophrenia remains controversial. The current general research view is that the cognitive function of patients with schizophrenia is basically stable over time [ 20 , 21 ] , but some studies have found that cognitive function declines over time and even improves in some cognitive areas [ 22 , 23 ] . When comparing the individual cognitive function between patients with first-episode and chronic schizophrenia, no statistically significant differences were observed in the function of each cognitive domain [ 13 ] . This finding supports the notion that as the disease progresses, individuals with schizophrenia maintain a stable state in terms of their cognitive function. Furthermore, several studies have reported impaired cognitive function in clinical clinical high risk (CHR) [ 24 , 25 ] and among first-grade relatives (FDRs) [ 26 , 27 ] , suggesting that cognitive deficits in schizophrenia patients could serve as an indicator of vulnerability. Interestingly, this study revealed that non-medicated individuals with schizophrenia who received antipsychotic treatment for a duration of 4 weeks exhibited enhancements in word learning and working memory. In order to elucidate this finding, we initially considered the potential influence of a short-term follow-up period on the observed practice effect. However, Jahshan C [ 22 ] conducted a 6-month follow-up study on first-episode schizophrenia and observed that speech learning exhibited the most significant enhancement. Consequently, it can be inferred with accuracy that while the majority of cognitive functions in individuals with schizophrenia remain stable throughout the course of the disease, specific cognitive abilities such as word learning may exhibit improvement through interventions like medication. Impairment of MMN amplitude in schizophrenia is considered to be one of the most potentially robust biomarkers for schizophrenia [ 28 ] . Previous studies have demonstrated a more pronounced impairment of MMN amplitude in individuals with chronic schizophrenia compared to those with first-episode schizophrenia; however, no significant association has been observed between the extent of MMN amplitude impairment and the progression of schizophrenia [ 29 ] . One potential explanation is that the decline in MMN amplitude among individuals with schizophrenia progressively deteriorates within 1–2 years following diagnosis, and subsequently stabilizes after reaching a critical stage. This hypothesis is supported by a study demonstrating a correlation between the impairment of MMN amplitude and disease progression during the initial 18 months [ 30 ] . The findings of this study revealed a decrement in MMN amplitude as the 4-week disease course progressed. Although no significant statistical difference was observed, these results may suggest that the observed decline in MMN amplitude among individuals with schizophrenia follows a non-linear growth trajectory, indicating an absence of linear correlation [ 29 ] . Furthermore, our results suggest that the decline in MMN amplitude may worsen as the disease progresses, potentially indicating a progressive nature of MMN deficits due to cortical tissue loss in areas associated with attention regulation and orienting [ 31 ] or medication-related effects. The findings from our trial indicate that antipsychotics do not effectively ameliorate MMN amplitude and impairment in patients with schizophrenia. One possible explanation for the previous conflicting results on whether antipsychotics improve MMN amplitude is that drugs with a strong serotonergic influence, such as aripiprazole [ 32 ] or quetiapine [ 15 ] tablets, may enhance MMN amplitude. A separate study demonstrated that the administration of escitalopram tablets to healthy participants resulted in a significant modulation of MMN amplitude. This observation suggests that the regulation of MMN may involve serotonergic mechanisms [ 33 ] . However, MMN deficits are not improved by other second-generation antipsychotics that have a strong affinity for serotonin receptors [ 34 ] . In addition, our findings indicate that antipsychotics do not show any significant impact on the enhancement of evoke theta power. Numerous hypotheses have been proposed to explain the mechanisms underlying MMN impairment in individuals with schizophrenia; however, the most widely acknowledged hypothesis among researchers is that it is associated with deficient NMDAR function in this patient population. The impaired function of NMDAR in patients with schizophrenia is widely acknowledged within the field of schizophrenia research. Previous investigations have demonstrated a decline in mRNA expression levels and diminished protein levels specifically of N1-type NMDA receptors within the prefrontal cortex among individuals diagnosed with this disorder [ 35 ] . Both studies conducted on non-human primates using intracranial [ 36 ] and surface [ 37 ] recording techniques, as well as investigations involving healthy volunteers [ 38 ] administered with ketamine (an NMDAR antagonist), have provided evidence suggesting that insufficient activity of individual NMDR receptors may be associated with MMN impairment. Importantly, this impairment is not believed to have any correlation with 5-hydroxytryptamine (5-HT) receptors or dopamine receptor function [ 39 ] .Recent studies have found that D-serine (which enhances NMDA receptor function as an endogenous ligand at the NMDAR regulatory site [ 40 ] or glycine (which enhances NMDAR function) [ 41 ] ameliorates MMN impairment in schizophrenic patients, corroborating that MMN impairment in schizophrenic patients may be related to their NMDA receptor insufficiency. As well as, it is preferable that antipsychotics do not ameliorate MMN impairment as the impairment of evoke theta power is also linked to NMDAR and can be enhanced by N-methyl-D-aspartic acid receptor (NMDAR) modulators [ 42 ] . 5. Limitation Despite the strengths of our study, several limitations must be acknowledged. The sample size of 31 patients is relatively small, which may limit the generalizability of our findings. The four-week follow-up period is also relatively short, preventing us from assessing the long-term effects of antipsychotic treatment on cognitive and neurophysiological outcomes. Future research should aim to include larger, more diverse samples and extend the follow-up period to capture long-term effects. Furthermore, combining antipsychotic treatment with cognitive behavioral therapy (CBT) or other psychosocial interventions could provide a more comprehensive understanding of how to address the multifaceted nature of schizophrenia. 6. Conclusion In conclusion, our study highlights the efficacy of antipsychotic medications in improving clinical symptoms of schizophrenia but also underscores the need for additional interventions to address cognitive deficits and MMN abnormalities. These findings have important implications for clinical practice and policy-making, suggesting that a more integrated treatment approach may be necessary to fully support the recovery of schizophrenia patients. Future research should focus on larger, more diverse populations and longer follow-up periods to validate and extend these findings. Declarations Acknowledgments The authors thank all the subjects for participating in this study. Authors’ contributions YBX and QBG contributed to manuscript preparation. YBX, QJB and XBL performed the neurophysiological data analysis and statistics. YBX and YL oversaw MMN data/demographic data collection. CYW looked over the MMN test. CYW was in charge of design and implementation of the study and contributed to data interpretation. Funding This work was supported by the Basic Research Projects of Shanxi Province China (202203021222341). Conflicts of interest All authors declare that they have no conflicts of interest. Clinical trial number ChiCTR2000038961. Ethics approval and consent to participate This study obtained approval from the Ethics Committee of Beijing Anding Hospital (LL-SQ-fj-3.8.1-1.3) and all subjects provided informed consent before participating (1.2/ 2017.07.07). Consent for publication Not applicable as we do not provide personal information for publication. Availability of data and material The data that support the findings of this study are available from the corresponding author, CYW, upon reasonable request. References McCutcheon RA, Reis Marques T, Howes OD: Schizophrenia-An Overview. JAMA psychiatry 2020, 77(2):201-210. Bueno-Antequera J, Munguía-Izquierdo D: Exercise and Schizophrenia. Advances in experimental medicine and biology 2020, 1228:317-332. Jauhar S, Johnstone M, McKenna PJ: Schizophrenia. Lancet (London, England) 2022, 399(10323):473-486. Näätänen R: The mismatch negativity: a powerful tool for cognitive neuroscience. Ear and hearing 1995, 16(1):6-18. 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Greenwood LM, Leung S, Michie PT, Green A, Nathan PJ, Fitzgerald P, Johnston P, Solowij N, Kulkarni J, Croft RJ: The effects of glycine on auditory mismatch negativity in schizophrenia. Schizophrenia research 2018, 191:61-69. Lee M, Balla A, Sershen H, Sehatpour P, Lakatos P, Javitt DC: Rodent Mismatch Negativity/theta Neuro-Oscillatory Response as a Translational Neurophysiological Biomarker for N-Methyl-D-Aspartate Receptor-Based New Treatment Development in Schizophrenia. Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology 2018, 43(3):571-582. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 18 Dec, 2024 Read the published version in BMC Psychiatry → Version 1 posted Editorial decision: Revision requested 16 Sep, 2024 Editor assigned by journal 12 Sep, 2024 Submission checks completed at journal 12 Sep, 2024 First submitted to journal 07 Sep, 2024 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5049624","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":354741447,"identity":"2c20fcc3-f6ff-49a8-89d8-7852273fde22","order_by":0,"name":"Yan-Bing Xiong","email":"","orcid":"","institution":"Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Third Hospital of Shanxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yan-Bing","middleName":"","lastName":"Xiong","suffix":""},{"id":354741448,"identity":"e19a295d-9e97-4d99-aa7a-0d3e286df4b3","order_by":1,"name":"Qi-Jing Bo","email":"","orcid":"","institution":"Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Qi-Jing","middleName":"","lastName":"Bo","suffix":""},{"id":354741455,"identity":"fdbfe8ba-af97-4859-990c-756b19de7742","order_by":2,"name":"Xian-Bin Li","email":"","orcid":"","institution":"Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xian-Bin","middleName":"","lastName":"Li","suffix":""},{"id":354741456,"identity":"87a1a3c1-dd8c-4d5e-8b29-65773b1d4c69","order_by":3,"name":"Yi Liu","email":"","orcid":"","institution":"Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yi","middleName":"","lastName":"Liu","suffix":""},{"id":354741457,"identity":"365d3458-4846-47bf-8801-e656ddbf26f6","order_by":4,"name":"Qi-BO Guo","email":"","orcid":"","institution":"The Fifth Hospital of Shanxi Medical University, The Fifth Clinical Medical College of Shanxi Medical University, Shanxi Provincial People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Qi-BO","middleName":"","lastName":"Guo","suffix":""},{"id":354741458,"identity":"2049b7c9-39fb-40e2-ac26-9a37234be748","order_by":5,"name":"Chuan-Yue Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAv0lEQVRIiWNgGAWjYBADOTb29gOkaTHm4zmTAKQNiNeSOE/CwYA4LQbHzx5+wVBzOL1NgiGBuaDiDxFazuSlWTAcO5zbJt14gHnGGSJsMTuQY2bA2ADUInMggZm3jRgt59+AtaSzSSQYMPP+I0bLjRzjB0AtCRAtDURosb/xxowh4Vi6YRswkA/zHDMmrEWyP8f4w4caa3n59vaDj3lq5AhrAQKgkxiawawDRKkHAuYPDAx1xCoeBaNgFIyCkQgA1OI39ZOJv3QAAAAASUVORK5CYII=","orcid":"","institution":"Capital Medical University","correspondingAuthor":true,"prefix":"","firstName":"Chuan-Yue","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-09-07 15:40:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5049624/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5049624/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12888-024-06314-w","type":"published","date":"2024-12-18T15:57:41+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":69351217,"identity":"00eeac69-ac20-42ec-8105-025b1d5098fb","added_by":"auto","created_at":"2024-11-19 13:08:02","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":152182,"visible":true,"origin":"","legend":"\u003cp\u003e(A1-A2) Mismatch negativity amplitudes before and after antipsychotic treatment. (B1-B2) evoke power before and after antipsychotic treatment\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5049624/v1/8ae7c21454ba06b0e96d6ef8.png"},{"id":72201732,"identity":"9357b4ca-4174-49b6-8922-f6238872adfc","added_by":"auto","created_at":"2024-12-23 16:10:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":821407,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5049624/v1/8f99f3f9-c2cf-49a6-93c1-8584e0ab8dbc.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effect of antipsychotic on mismatch negativity amplitude and evoked theta power in drug- naïve patients with schizophrenia","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSchizophrenia is a severe mental disorder that significantly impacts patients' cognitive functions, social capabilities, and overall quality of life. With a prevalence rate of approximately 1%, schizophrenia imposes substantial psychological and economic burdens on patients and society\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. More than 50% of those observed experience intermittent yet persistent psychiatric problems, while approximately 20% suffer from lifelong chronic clinical symptoms and disability. This not only causes severe harm to the individuals but also imposes a significant burden on society, with the anticipated disease burden expected to more than double by 2030\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. Therefore, reducing the increasing disease burden of mental disorders such as schizophrenia has become a priority in mental health and is also important for improving the social functioning of patients. However, the current prevention, control, and diagnosis of schizophrenia are not ideal mainly due to difficulties in early identification and intervention in patients with schizophrenia, resulting in poor prognosis for these individuals and an inability to effectively restore their social functions\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eMismatch negativity (MMN) is an event-related potential (ERP) that occurs when a stimulus with different properties, such as duration (dMMN) or frequency (fMMN), is presented together with a standard stimulus that is more frequently presented\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/sup\u003e MMN serves as an indicator of a memory-driven cerebral auditory sensory reaction to identifiable alterations in a sequence of stimuli, even when attention is not present\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. The MMN component of the evoked potential has been discovered to offer valuable insights into the importance of regularity sensitivity in perception and cognition\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. The MMN paradigm has gained considerable attention in recent years due to its capacity to provide insights into the underlying mechanisms of sensory information processing by detecting deviations\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. The correlation between MMN and both neurocognitive abilities and functional outcomes among individuals diagnosed with schizophrenia has been well-established in prior research\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eCognitive impairment constitutes a fundamental manifestation of schizophrenia\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. Revised sentence: Previous research has consistently demonstrated that individuals with schizophrenia exhibit cognitive deficits across multiple domains, consistently performing 0.5\u0026ndash;1.75 standard deviations below the mean of healthy individuals on neuropsychological tasks assessing various cognitive functions\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. The recovery of cognitive function plays a pivotal role in determining the reintegration of individuals with schizophrenia into society. Biomarkers are indispensable for achieving precision medicine in schizophrenia, and among various neurophysiological and neurocognitive measures, MMN reduction stands out as one of the most robust findings in patients with this disorder. Our previous study revealed a significant association between MMN amplitude impairment in individuals with schizophrenia and deficits in word learning and working memory within the cognitive domain\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003ePrevious study has demonstrated the lack of efficacy of antipsychotic medication in ameliorating MMN deficits among individuals diagnosed with schizophrenia\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. However, some studies have also found that antipsychotic medication improves MMN impairment in schizophrenia\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. The cause of the variability in these results is unknown, and further follow-up studies are required. Furthermore, previous follow-up studies investigating antipsychotic therapy for MMN deficiency in patients with schizophrenia have primarily focused on assessing the amplitude of MMN. Relative to MMN amplitude, which can only provide local potential information on evoked potentials, event related spectral perturbation (ERSP) analysis can provide both potential-level and molecular-level information, in addition to more complex physiological information\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. It has been shown that the ERSP evoked power of auditory MMN is mainly concentrated in the theta band (4\u0026ndash;7 Hz), and the presence of impaired ERSP energy in the theta band evoked by MMN was found to be a biomarker of schizophrenia\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. Our group also found that impaired evoked theta power deficits in schizophrenia was associated with working memory\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. However, there are no current studies on follow-up studies of antipsychotic drugs inducing theta power deficits in patients with schizophrenia.\u003c/p\u003e \u003cp\u003eIn summary, both MMN amplitude and evoked theta power can serve as potential biomarkers for precise interventions targeting cognitive impairment in schizophrenia; however, the effect of antipsychotics on MMN wave amplitude remains inconclusive based on previous studies, and there is a lack of follow-up research investigating the impact of antipsychotic treatment on evoked theta power. In this study, we administered a 4-week course of antipsychotic treatment to drug-na\u0026iuml;ve patients with schizophrenia in order to investigate the impact of antipsychotics on both MMN amplitude and evoked theta power, aiming to elucidate whether antipsychotics can effectively ameliorate these deficits. The findings from this research have the potential to inform the development of more efficacious therapeutic strategies for managing cognitive deficits in schizophrenia, ultimately enhancing patient outcomes.\u003c/p\u003e"},{"header":"2. Method and material","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Participants\u003c/h2\u003e \u003cp\u003eThirty-one drug-na\u0026iuml;ve individuals diagnosed with schizophrenia were recruited as participants from Beijing Anding Hospital, Capital Medical University. The inclusion criteria for this study involved the validation of diagnoses using the Structured Clinical Interview for DSM-IV (SCID). Participants ranged in age from 18 to 45 years and all had IQ scores equal to or greater than 70. Exclusion criteria encompassed hearing impairments, learning difficulties, neurological disorders, a history of seizures or head injuries, prior electroconvulsive therapy, and substance abuse. This study obtained approval from the Ethics Committee of Beijing Anding Hospital and all subjects provided informed consent before participating.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Procedures\u003c/h2\u003e \u003cp\u003eThe auditory stimuli comprised a series of binaural tones (825 trials) presented in a random sequence with a stimulus onset asynchrony ranging from 500 to 550 ms. The majority of the trials (675, accounting for 82%) featured standard tones characterized by a frequency of 1000 Hz, sound intensity level of 75 dB, and duration of 50 ms. In contrast, deviant tones included variations in both frequency and duration. Frequency deviants (75 trials, representing 9% of the total) had a frequency of 1500 Hz, sound intensity level of 75 dB, and duration of 50 ms. Duration deviants (another set comprising approximately 9% or 75 trials overall) maintained the same frequency as the standard tones but had an extended duration lasting for 100 ms instead. To establish baseline standards at the experiment's outset, we employed the initial set consisting of fifteen stimuli as our reference.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Electroencephalogram (EEG) data acquisition and processing\u003c/h2\u003e \u003cp\u003eElectroencephalogram (EEG) data were recorded from all participants using a 128-channel electrode system (Electrical Geodesics, Inc., Oregon, USA) with standard reference and grounding procedures. The signal impedance was adjusted to be \u0026ge;\u0026thinsp;50 KΩ while maintaining a sampling rate of 1000 Hz. During the experiment, subjects were seated comfortably in a specially designed room that minimized potential external factors that could affect the study. The test consisted of three sections separated by breaks lasting for 60 seconds each.\u003c/p\u003e \u003cp\u003eFor the ERP analyses, we employed EEGLAB 14.1.1b (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://sccn.ucsd.edu/eeglab/\u003c/span\u003e\u003cspan address=\"http://sccn.ucsd.edu/eeglab/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), a MATLAB-based tool for neural electrophysiological analysis. The EEG data were processed using a finite impulse response filter with a bandpass range of 0.1\u0026ndash;40 Hz to ensure optimal signal quality. To eliminate power frequency noise at 50 Hz, notch processing was applied as an additional step in the preprocessing pipeline. We adopted a global brain average reference as the new electrode configuration to enhance spatial comparability across subjects and minimize potential bias introduced by individual differences in scalp topography. Independent component analysis (ICA) was utilized to effectively remove artifacts caused by eye movement, ensuring accurate interpretation of the underlying neural activity patterns. Segmentation of the EEG data encompassed a time window from 100 ms before stimulus onset to 500 ms after stimulus initiation, allowing us to capture both pre-stimulus baseline activity and post-stimulus responses within an appropriate temporal context for further analysis purposes. MMN waveforms were derived by subtracting the deviant stimulus from the standard stimulus specifically at the frontal midline (Fz) electrode location.\u003c/p\u003e \u003cp\u003eFor the analysis of evoked (average) power, we employed the short-time Fourier transformation (STFT) method in MATLAB (MathWorks, Natick, MA, USA) to convert ERP waves. The segmented EEG signal underwent continuous wavelet transformation over time. The EEG data spanned from 100 ms prior to stimulus initiation to 500 ms after stimulus onset relative to presentation time. A frequency range of 1\u0026ndash;20 Hz was applied for the wavelet transformation. Furthermore, temporal power values corresponding to each frequency point were averaged across trials to obtain an EEG power time-frequency distribution on a channel-by-channel basis. For statistical analysis purposes, maximum power values within each subject's theta frequency band of 4\u0026ndash;7 Hz and between 100\u0026ndash;250 ms were extracted. This range represents the primary active frequency band of neural oscillation in response to the standard stimulus.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Clinical, intelligence quotient and neuropsychological assessment\u003c/h2\u003e \u003cp\u003eThe clinical symptoms of each patient were evaluated with the Positive and Negative Symptom Scale (PANSS, Chinese version), which was previously described. The Chinese intelligence quotient (IQ) test tool was revised short form the Wechsler adult intelligence scale-revised, and the four included subsets for this evaluation were information, similarities, picture completion, and block design\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e.The MATRICS consensus cognitive battery (MCCB, Chinese version) was used to evaluated cognitive deficits in patients with schizophrenia and healthy controls\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Statistical analysis\u003c/h2\u003e \u003cp\u003eThe statistical analysis was performed using SPSS 20.0 (IBM, Chicago, IL, USA). To compare PANSS scores, MCCB scores, amplitudes of MMN and evoke power between the baseline and 4-week treatment sessions, we utilized paired-samples T tests. A significance level of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was employed for the statistical analysis.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Demographics and Clinical Characteristics\u003c/h2\u003e \u003cp\u003eThe mean age of individuals diagnosed with schizophrenia was 27.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5.7 years, with a majority (77%) being male. The average duration of education for these individuals was 13.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5 years, while the mean age at onset of symptoms was recorded as 25.6\u0026thinsp;\u0026plusmn;\u0026thinsp;5.3 years, and the average illness duration stood at 26.4\u0026thinsp;\u0026plusmn;\u0026thinsp;30.7 months. Furthermore, the conversion to olanzapine-equivalent dosage resulted in an average daily intake of 15.9\u0026thinsp;\u0026plusmn;\u0026thinsp;6.3 mg/dose per patient's requirement. The detailed results are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGeneral demographic and clinical data characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePatients (N\u0026thinsp;=\u0026thinsp;31)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (male / %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 / 77%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation years (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOnset age (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.6\u0026thinsp;\u0026plusmn;\u0026thinsp;5.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCourse (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, month)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.4\u0026thinsp;\u0026plusmn;\u0026thinsp;30.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eolanzapine-equivalent dosage (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, mg/d)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.9\u0026thinsp;\u0026plusmn;\u0026thinsp;6.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Comparisons of PANSS before and after antipsychotics treatment\u003c/h2\u003e \u003cp\u003eAfter a 4-week treatment regimen with a single antipsychotic medication, there was a significant improvement in the symptoms of patients diagnosed with schizophrenia. Specifically, statistically significant differences were observed in PANSS positive symptom scores (df\u0026thinsp;=\u0026thinsp;30, t\u0026thinsp;=\u0026thinsp;11.991, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), negative symptom scores (df\u0026thinsp;=\u0026thinsp;30, t\u0026thinsp;=\u0026thinsp;8.650, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), general symptom scores (df\u0026thinsp;=\u0026thinsp;30, t\u0026thinsp;=\u0026thinsp;14.086, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and the overall PANSS score (df\u0026thinsp;=\u0026thinsp;30, t\u0026thinsp;=\u0026thinsp;16.898 p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The detailed results are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePANSS scores before and after antipsychotic treatment\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eAfter 4-week treatments\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003ePaired-samples T tests\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e (2-tailed)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive symptom scale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e11.991\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative symptom scale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8.650\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal psychopathology scale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e14.086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePANSS (total scores)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e77.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e47.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e16.898\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Comparisons of MCCB before and after antipsychotics treatment\u003c/h2\u003e \u003cp\u003eThe neurocognitive treatment using MCCB demonstrated significant improvements in word learning (df\u0026thinsp;=\u0026thinsp;30, t = -3.393, p\u0026thinsp;=\u0026thinsp;0.002), working memory (df\u0026thinsp;=\u0026thinsp;30, t = -3.766, p\u0026thinsp;=\u0026thinsp;0.001), and total MCCB cognitive score (df\u0026thinsp;=\u0026thinsp;30, t = -3.042, p\u0026thinsp;=\u0026thinsp;0.005). However, no significant improvements were observed in other cognitive domains. Specific detailed results are shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMCCB scores before and after antipsychotic treatment\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eAfter 4-week treatments\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003ePaired-samples T tests\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e (2-tailed)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpeed of processing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-1.349\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.188\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAttention/Vigilance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e34.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.814\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWorking memory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-3.766\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVerbal learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-3.393\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVisual learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e44.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-1.829\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReasoning and problem\u003c/p\u003e \u003cp\u003esolving\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-1.864\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial cognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.700\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCCB combine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-3.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Comparisons of MMN index and after antipsychotics treatment\u003c/h2\u003e \u003cp\u003eAfter 4 weeks of monotherapy with antipsychotic medication, there was no statistically significant improvement observed in the amplitude of MMN wave frequency (df\u0026thinsp;=\u0026thinsp;30, t = -1.043, p\u0026thinsp;=\u0026thinsp;0.305), duration wave amplitude (df\u0026thinsp;=\u0026thinsp;30, t = -0.403, p\u0026thinsp;=\u0026thinsp;0.690), and evoke theta power (df\u0026thinsp;=\u0026thinsp;30, t = -1.242, p\u0026thinsp;=\u0026thinsp;0.224). Detailed results are shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMismatch negativity amplitudes and evoke power before and after antipsychotic treatment\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eAfter 4-week treatments\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003ePaired-samples T tests\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e (2-tail)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003cp\u003eMMN (\u0026micro;V)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.7911\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.2884\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.7443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.2951\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-1.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.305\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration MMN (\u0026micro;V)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-1.6588\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.5394\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.6212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.5370\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.690\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEvoke theta power\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0427\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0364\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-1.242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.224\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study focuses on the neurocognitive performance and auditory evoked potentials, specifically MMN amplitude and its related frequency band analysis, in drug-na\u0026iuml;ve patients with schizophrenia before and after antipsychotic treatment. Previous studies investigating the effects of antipsychotic drugs on MMN indexes in schizophrenia have predominantly focused on amplitude, whereas this study represents the first attempt to examine the influence of antipsychotic drugs on MMN evoked power in individuals with schizophrenia. Notably, our findings reveal that while antipsychotic treatment significantly improves clinical symptoms, its impact on cognitive function and neurophysiological markers such as MMN amplitude and theta evoke power is limited.\u003c/p\u003e \u003cp\u003eCognitive dysfunction in patients with schizophrenia is considered a significant pathological manifestation, persisting even after treatment of core clinical symptoms such as hallucinations and delusions. Moreover, it closely correlates with the functional outcome of patients. The process of cognitive change over the course of schizophrenia remains controversial. The current general research view is that the cognitive function of patients with schizophrenia is basically stable over time\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e, but some studies have found that cognitive function declines over time and even improves in some cognitive areas\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. When comparing the individual cognitive function between patients with first-episode and chronic schizophrenia, no statistically significant differences were observed in the function of each cognitive domain\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. This finding supports the notion that as the disease progresses, individuals with schizophrenia maintain a stable state in terms of their cognitive function. Furthermore, several studies have reported impaired cognitive function in clinical clinical high risk (CHR) \u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003eand among first-grade relatives (FDRs)\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e, suggesting that cognitive deficits in schizophrenia patients could serve as an indicator of vulnerability. Interestingly, this study revealed that non-medicated individuals with schizophrenia who received antipsychotic treatment for a duration of 4 weeks exhibited enhancements in word learning and working memory. In order to elucidate this finding, we initially considered the potential influence of a short-term follow-up period on the observed practice effect. However, Jahshan C\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e conducted a 6-month follow-up study on first-episode schizophrenia and observed that speech learning exhibited the most significant enhancement. Consequently, it can be inferred with accuracy that while the majority of cognitive functions in individuals with schizophrenia remain stable throughout the course of the disease, specific cognitive abilities such as word learning may exhibit improvement through interventions like medication.\u003c/p\u003e \u003cp\u003eImpairment of MMN amplitude in schizophrenia is considered to be one of the most potentially robust biomarkers for schizophrenia\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. Previous studies have demonstrated a more pronounced impairment of MMN amplitude in individuals with chronic schizophrenia compared to those with first-episode schizophrenia; however, no significant association has been observed between the extent of MMN amplitude impairment and the progression of schizophrenia\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e. One potential explanation is that the decline in MMN amplitude among individuals with schizophrenia progressively deteriorates within 1\u0026ndash;2 years following diagnosis, and subsequently stabilizes after reaching a critical stage. This hypothesis is supported by a study demonstrating a correlation between the impairment of MMN amplitude and disease progression during the initial 18 months\u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e. The findings of this study revealed a decrement in MMN amplitude as the 4-week disease course progressed. Although no significant statistical difference was observed, these results may suggest that the observed decline in MMN amplitude among individuals with schizophrenia follows a non-linear growth trajectory, indicating an absence of linear correlation\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e. Furthermore, our results suggest that the decline in MMN amplitude may worsen as the disease progresses, potentially indicating a progressive nature of MMN deficits due to cortical tissue loss in areas associated with attention regulation and orienting\u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e or medication-related effects.\u003c/p\u003e \u003cp\u003eThe findings from our trial indicate that antipsychotics do not effectively ameliorate MMN amplitude and impairment in patients with schizophrenia. One possible explanation for the previous conflicting results on whether antipsychotics improve MMN amplitude is that drugs with a strong serotonergic influence, such as aripiprazole\u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e or quetiapine\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e tablets, may enhance MMN amplitude. A separate study demonstrated that the administration of escitalopram tablets to healthy participants resulted in a significant modulation of MMN amplitude. This observation suggests that the regulation of MMN may involve serotonergic mechanisms\u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e. However, MMN deficits are not improved by other second-generation antipsychotics that have a strong affinity for serotonin receptors\u003csup\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e. In addition, our findings indicate that antipsychotics do not show any significant impact on the enhancement of evoke theta power.\u003c/p\u003e \u003cp\u003eNumerous hypotheses have been proposed to explain the mechanisms underlying MMN impairment in individuals with schizophrenia; however, the most widely acknowledged hypothesis among researchers is that it is associated with deficient NMDAR function in this patient population. The impaired function of NMDAR in patients with schizophrenia is widely acknowledged within the field of schizophrenia research. Previous investigations have demonstrated a decline in mRNA expression levels and diminished protein levels specifically of N1-type NMDA receptors within the prefrontal cortex among individuals diagnosed with this disorder\u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e. Both studies conducted on non-human primates using intracranial\u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e and surface\u003csup\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e recording techniques, as well as investigations involving healthy volunteers\u003csup\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/sup\u003e administered with ketamine (an NMDAR antagonist), have provided evidence suggesting that insufficient activity of individual NMDR receptors may be associated with MMN impairment. Importantly, this impairment is not believed to have any correlation with 5-hydroxytryptamine (5-HT) receptors or dopamine receptor function\u003csup\u003e[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/sup\u003e.Recent studies have found that D-serine (which enhances NMDA receptor function as an endogenous ligand at the NMDAR regulatory site\u003csup\u003e[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/sup\u003eor glycine (which enhances NMDAR function)\u003csup\u003e[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/sup\u003e ameliorates MMN impairment in schizophrenic patients, corroborating that MMN impairment in schizophrenic patients may be related to their NMDA receptor insufficiency. As well as, it is preferable that antipsychotics do not ameliorate MMN impairment as the impairment of evoke theta power is also linked to NMDAR and can be enhanced by N-methyl-D-aspartic acid receptor (NMDAR) modulators\u003csup\u003e[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e"},{"header":"5. Limitation","content":"\u003cp\u003eDespite the strengths of our study, several limitations must be acknowledged. The sample size of 31 patients is relatively small, which may limit the generalizability of our findings. The four-week follow-up period is also relatively short, preventing us from assessing the long-term effects of antipsychotic treatment on cognitive and neurophysiological outcomes. Future research should aim to include larger, more diverse samples and extend the follow-up period to capture long-term effects. Furthermore, combining antipsychotic treatment with cognitive behavioral therapy (CBT) or other psychosocial interventions could provide a more comprehensive understanding of how to address the multifaceted nature of schizophrenia.\u003c/p\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eIn conclusion, our study highlights the efficacy of antipsychotic medications in improving clinical symptoms of schizophrenia but also underscores the need for additional interventions to address cognitive deficits and MMN abnormalities. These findings have important implications for clinical practice and policy-making, suggesting that a more integrated treatment approach may be necessary to fully support the recovery of schizophrenia patients. Future research should focus on larger, more diverse populations and longer follow-up periods to validate and extend these findings.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank all the subjects for participating in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYBX and QBG contributed to manuscript preparation. YBX, QJB and XBL performed the neurophysiological data analysis and statistics. YBX and YL oversaw MMN data/demographic data collection. CYW looked over the MMN test. CYW was in charge of design and implementation of the study and contributed to data interpretation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Basic Research Projects of Shanxi Province China (202203021222341).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare that they have no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChiCTR2000038961.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study obtained approval from the Ethics Committee of Beijing Anding Hospital (LL-SQ-fj-3.8.1-1.3) and all subjects provided informed consent before participating (1.2/ 2017.07.07).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable as we do not provide personal information for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author, CYW, upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMcCutcheon RA, Reis Marques T, Howes OD: Schizophrenia-An Overview. 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Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology 2018, 43(3):571-582.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"bmc-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bpsy","sideBox":"Learn more about [BMC Psychiatry](http://bmcpsychiatry.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bpsy/default.aspx","title":"BMC Psychiatry","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Schizophrenia, Mismatch negativity, Time-frequency analysis, Antipsychotic","lastPublishedDoi":"10.21203/rs.3.rs-5049624/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5049624/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eRecurrent observations have indicated the presence of deficits in mismatch negativity (MMN) among schizophrenia. There is evidence suggesting a correlation between increased dopaminergic activity and reduced MMN amplitude, but there is no consensus on whether antipsychotic medications can improve MMN deficit in schizophrenia.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted clinical assessments, cognitive function tests, and EEG data collection and analysis on 31 drug-na\u0026iuml;ve patients with schizophrenia. Comprehensive evaluation tools such as PANSS and MCCB. MMN amplitude was analyzed by event-related potential (ERP) approaches, evoked theta power was analyzed by event-related spectral perturbation (ERSP) approaches.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOur findings indicate that antipsychotic treatment significantly improved clinical symptoms, as evidenced by reductions in PANSS positive, negative, general symptoms, and total scores (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Cognitive function improvements were observed in language learning, working memory, and overall MCCB scores (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), although other cognitive domains showed no significant changes. However, no significant improvements were noted in MMN amplitude and evoke theta power after four weeks of antipsychotic treatment (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThese results suggest that while antipsychotic medications effectively alleviate clinical symptoms, their impact on MMN amplitude and evoke theta power deficit is limited in the short term. Moreover, the amelioration of cognitive impairment in individuals with schizophrenia is not readily discernible, and it cannot be discounted that the enhancement observed in language acquisition and working memory may be attributed to a learning effect. These findings underscore the complexity of the neurobiological mechanisms involved and highlight the need for further research to optimize individualized treatment strategies for schizophrenia.\u003c/p\u003e","manuscriptTitle":"Effect of antipsychotic on mismatch negativity amplitude and evoked theta power in drug- naïve patients with schizophrenia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-19 12:59:57","doi":"10.21203/rs.3.rs-5049624/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-09-16T14:06:11+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-09-12T14:18:16+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-09-12T14:16:34+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychiatry","date":"2024-09-07T15:38:54+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bpsy","sideBox":"Learn more about [BMC Psychiatry](http://bmcpsychiatry.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bpsy/default.aspx","title":"BMC Psychiatry","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"34ec0790-6399-4acf-9d3a-f83840b36de3","owner":[],"postedDate":"November 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-23T16:02:17+00:00","versionOfRecord":{"articleIdentity":"rs-5049624","link":"https://doi.org/10.1186/s12888-024-06314-w","journal":{"identity":"bmc-psychiatry","isVorOnly":false,"title":"BMC Psychiatry"},"publishedOn":"2024-12-18 15:57:41","publishedOnDateReadable":"December 18th, 2024"},"versionCreatedAt":"2024-11-19 12:59:57","video":"","vorDoi":"10.1186/s12888-024-06314-w","vorDoiUrl":"https://doi.org/10.1186/s12888-024-06314-w","workflowStages":[]},"version":"v1","identity":"rs-5049624","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5049624","identity":"rs-5049624","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}