Aperiodic brain activity in major depression: Increased inhibition and developmental effects of childhood maltreatment

Aperiodic brain activity in major depression: Increased inhibition and developmental effects of childhood maltreatment | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Aperiodic brain activity in major depression: Increased inhibition and developmental effects of childhood maltreatment Kristian Jensen, Kirstine Andersen, Cheng Teng Ip, Vibe Frokjaer, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7530123/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract The aperiodic exponent of EEG-power spectra is emerging as a non-oscillatory marker of cortical excitation-inhibition balance (E/I balance). Altered E/I balance has been proposed in major depressive disorder (MDD), but evidence from clinical cohorts remains limited and inconsistent, and the impact of developmental risk factors is unknown. We analysed resting-state EEG from 91 unmedicated MDD patients and 35 healthy controls enrolled in the NeuroPharm-1 study. Patients received 10–20 mg of escitalopram treatment for 8 weeks, with 39 undergoing follow-up EEG. Before treatment, MDD patients showed significantly greater frontal aperiodic exponents compared to healthy controls (Cohen's d = 0.44, p = 0.03), consistent with increased cortical inhibition in depression. Importantly, pretreatment frontal aperiodic exponent showed a strong negative association with childhood trauma severity ( p < 0.001), independent of current depressive symptoms and familial predisposition for depression, suggesting that early adversity leaves a lasting imprint on cortical dynamics. No associations were found with treatment, and aperiodic exponents remained unchanged during SSRI treatment. These findings demonstrate that aperiodic EEG activity captures state-related alterations in unmedicated depression and highlight long-term developmental signatures of childhood trauma. This underscores the potential of aperiodic measures as translational markers of environmentally shaped vulnerability in psychiatric disorders. Biological sciences/Physiology Health sciences/Biomarkers/Predictive markers Health sciences/Diseases/Psychiatric disorders/Depression major depressive disorder excitation-inhibition balance aperiodic neural activity resting state EEG childhood trauma parenting Figures Figure 1 Figure 2 1. Introduction The underlying pathophysiology of depression remains unclear. Up to one-third of patients with Major depressive disorder (MDD) are resistant to standard pharmacological treatment 1 , 2 , and many experience recurrence 3 , 4 or undesired medication side effects 5 – 7 . Hence, elucidating the neurobiology and identifying predictive biomarkers of treatment outcomes is pressing 8 . Electroencephalography (EEG) has long been investigated as a tool for this purpose, and conventional oscillatory markers have shown promise for predicting treatment outcomes in depression 9 and informing personalised treatment approaches 10 . Recent methodological advances extend this approach by focusing on the aperiodic component of EEG signals, which has been historically overlooked as "noise" 11 – 14 . EEG power spectra can be decomposed into rhythmic oscillations (periodic) 15 and a broadband aperiodic 1/ f component, the latter quantified by the aperiodic exponent 13 , 16 . Aperiodic activity follows a scale-free distribution, in which power decreases with frequency, and has been proposed as a non-invasive index of cortical excitation-inhibition (E/I) balance 17 . Such a power law relationship is conveniently plotted in a double logarithmic plot and characterised by the y-axis intercept (offset) and the 1/ f X slope derived from a linear fit to the original EEG power spectrum density 13 . Anaesthesia reliably shifts this balance toward inhibition, producing a greater exponent and steeper slopes 14 , 18 . Disrupted E/I balance is implicated in depression pathophysiology 19 , 20 , particularly within prefrontal circuits supporting emotional regulation and cognitive control 19 , 21 . The GABAergic deficit hypothesis posits that chronic stress impairs inhibitory neurotransmission, contributing to core depressive symptomatology 22 , 23 . Early-life stress, especially childhood maltreatment, is a potent risk factor for adult depression 24 , 25 and may induce lasting cortical E/I balance changes during critical developmental periods, creating enduring vulnerability 24 , 26 , 27 . This developmental perspective suggests that aperiodic measures might capture both state-related changes in MDD and long-term neurobiological vulnerability shaped by early adversity 27 , 28 . Yet, studies examining aperiodic activity in depression have yielded conflicting results. Two small studies (≤44 patients) observed flatter aperiodic slopes in patients with MDD than healthy controls (HC) 29 , 30 , whereas larger studies (≤119 patients) reported no difference 31 , 32 . Supporting its clinical relevance, an intracranial EEG study in treatment-resistant depression found that fluctuations in the 1/ f slope within the ventromedial prefrontal cortex closely tracked symptom severity over minutes to hours, with flatter slopes consistently associated with clinical improvement. 33 However, no study has examined how genetic predisposition or childhood trauma, leaving developmental and heritable contributions to aperiodic activity unexplored. Regarding depression treatment, short-term escitalopram flatten slopes in healthy females 34 , consistent with increased cortical excitation. In contrast, steeper frontal aperiodic slopes have been observed after electroconvulsive therapy (ECT), which mechanistically increases seizure threshold throughout treatment series, and magnetic seizure therapy (MST) in treatment-resistant patients 35 . More broadly, evidence from anaesthesia further suggests that the aperiodic exponent may also index the presence of consciousness itself. In healthy participants, steeper broadband slopes during unconsciousness (xenon/propofol) and wake-like exponents with ketamine, which selectively flattens higher frequencies (20–40 Hz) 18 . Collectively, these findings highlight the exponent’s sensitivity to drug-induced changes in E/I balance and conscious state. However, clinical studies of neuromodulation are inconsistent: with some studies linking steeper slopes to symptom relief 35 – 37 and others reporting the opposite 33 , 38 . Thus, the role of aperiodic activity in antidepressant mechanisms and its potential utility as a predictive biomarker remain unresolved. To address these gaps, we investigated aperiodic EEG activity in a well-characterised cohort of unmedicated MDD patients and HC 39 . First, we assessed whether patients exhibit altered frontal aperiodic activity compared to controls, providing evidence for disrupted cortical E/I balance in depression. Second, we examined whether risk factors for depression, including childhood maltreatment and familial predisposition, are reflected in aperiodic activity, to disentangle developmental and heritable pathways. Third, we evaluated the clinical utility of this marker by assessing whether pretreatment aperiodic measures predict selective serotonin reuptake inhibitor (SSRI) response or excitation-related side effects, i.e. insomnia and tension. Lastly, we explored whether the aperiodic activity changes over the course of treatment. We hypothesised that MDD patients would demonstrate steeper frontal exponents reflecting increased cortical inhibition consistent with the GABAergic deficit hypothesis, that childhood maltreatment would show independent associations with altered aperiodic activity, and that pretreatment aperiodic measures would predict clinical outcomes. 2. Materials and methods We used data from the NeuroPharm-1 study, a 12-week open-label clinical trial investigating biomarkers for antidepressant treatment (clinicaltrial.gov: NCT02869035). The National Committee on Health Research Ethics approved the study (H-15017713). A detailed study protocol is available elsewhere 39 , 40 . The current analysis on aperiodic activity was conducted as an exploratory extension and was not prespecified in the original study protocol. 2.1 Participants Patients 18–65 years old with a moderate to severe episode of depression consistent with ICD-10 criteria for less than two years, and a Hamilton Depression Rating Scale (HAMD 17 ) > 17 were recruited through the primary health care centre or directly referred by five collaborating general practitioners. Their diagnosis was confirmed by a certified psychiatrist using the Mini-International Neuropsychiatric Interview 41 . Ninety-two patients underwent pretreatment EEG (one patient was excluded due to spontaneous remission in the first week after assessment and was concluded not to be depressed). Of the remaining patients, 86 initiated treatment, and 39 treatment-adherent patients underwent a follow-up EEG after eight weeks. See the supplementary material and the CONSORT diagram (Figure S1 ) for more information. Thirty-five participants without current or past mental illness were included as HC. 2.2 Antidepressant treatment Patients started treatment with escitalopram, individually adjusted to 10–20 mg daily depending on response and side effects. Per standard practice, patients experiencing intolerable side-effects or < 25% reduction in HAMD 6 , a 6-item subscale of the HAMD 17 capturing core depressive symptoms 42 , from pretreatment to week four were offered to switch to duloxetine (n = 6) and were individually adjusted to 30–90 mg daily. Plasma medication levels at week eight were assessed to evaluate treatment adherence. Arousal-related SSRI-side effects were evaluated with two items from the clinician-rated “Udvalg for kliniske undersøgelser” (UKU) scale 43 . Item 1 “Inner unrest/Tension”, covering anxiety, jitteriness and restlessness, and item 2 “Insomnia”, were noted if reported within the initial four weeks of treatment when these side effects typically appear 44 . 2.3 Childhood trauma, predispositions and symptoms The presence of familial predisposition was defined as having a first-degree relative with past or present depression or suicide attempt. Childhood maltreatment was assessed by the total score from the Child Abuse and Trauma Scale (CATS) 45 . The Parental Bonding Instrument (PBI) complemented the CATS Neglect/Negative Home Atmosphere subscale. Anhedonia was measured by the Snaith–Hamilton Pleasure Scale (SHAPS) 46 and depression severity by the Beck Depression Inventory–II (BDI-II). 2.4 Aperiodic activity Resting state EEG was recorded in four 3-minute periods, counterbalanced as OCOC or COCO (O: eyes open, C: eyes closed) between subjects using a 256-channel system HydroCel Sensor Net system (EGI, Inc., Eugene, OR) using a sampling rate of 1000 Hz, a high-pass filter of 0.1 Hz and a low-pass filter of 100 Hz. Impedance was maintained below 50 kΩ. Only eyes-closed data were included in the current analysis. Data were average-referenced; bad channels interpolated; band-pass filtered (0.5–70 Hz) with 50 Hz notch; ocular/artefactual components removed via ICA; and 1-s epochs with residual artefact were rejected. Power spectral densities (PSDs) were computed from 1–40 Hz using the MNE-Python toolbox, consistent with prior work on aperiodic EEG dynamics 18 . Welch’s method was applied using 4-s sliding windows (50% overlap, zero-padding), and PSDs were averaged across time segments before input into the FOOOF (Fitting Oscillations & One-Over-F) toolbox v1.1.0 13 . FOOOF parameterises periodic and aperiodic components by applying Gaussian fits to oscillatory peaks and subtracting them from the spectrum, isolating the aperiodic component. Model settings included fixed aperiodic mode, peak width limit of 1–8 Hz, a maximum of eight peaks, and a peak threshold of three. Aperiodic exponents were then extracted for each channel, and regional values were derived by averaging electrodes within frontal, temporal, parietal, and occipital clusters, with frontal activity serving as the primary focus. 2.5 Statistics Statistics were done using JASP 0.95.1 47 , estimates are presented with [95%-confidence intervals], and results p < 0.05 were considered statistically significant. The age between patients and HC was compared using a Mann–Whitney U test due to leftward skew (median age 25 years) and sex distribution by Fisher’s exact test. Despite no significant age or sex group differences, all models below were adjusted for age, as the aperiodic exponent linearly decreases with age in adulthood 48 , 49 , and sex. 2.6 Group differences An ANCOVA (type III) was performed to compare the frontal aperiodic exponent in MDD patients vs. HC with age and sex as covariates. We also explored group differences in the aperiodic exponent across the other three regions (Table S1 ). In an exploratory analysis of the effect of hormonal contraceptives on the frontal exponent, premenopausal women with contraceptive use information were grouped into non-users, and those using combination oral contraceptives (COC), levonorgestrel-releasing intrauterine devices (LNG-IUD) and progestin-only oral contraceptives (POC). As there were no healthy POC users, the five patients with POC were omitted from the analysis (Table S2). We performed an ANCOVA with group, hormonal contraceptive use (None, COC, LNG-IUD), and their interaction as fixed factors with age as a covariate. Simple contrasts were used to follow up significant group effects. The ANCOVA assumptions were met, with no violation of the homogeneity of variances and normally distributed residuals. 2.7 Familial predisposition, childhood trauma and depressive symptoms To examine the associations between frontal exponent and depression risk factors and symptom measures, we conducted four separate linear regression models with frontal exponent as the dependent variable. Each model included one primary predictor: childhood trauma (CATS), anhedonia (SHAPS), depressive symptoms (BDI-II), or familial predisposition. All models included age and sex. We fitted each model twice: first without group as a covariate to examine overall associations, and second, including diagnostic group (MDD vs. HC) to assess dimensional relationships independent of depressive state. This approach allowed us to determine whether associations reflected diagnostic group differences or represented dimensional effects across the sample. Multiple comparisons across the four predictors were controlled using false discovery rate (FDR) correction (Benjamini–Hochberg). Post hoc, we tested three CATS subscales in models adjusted for group, age, and sex. Having observed a strong relationship with the CATS subscale Neglect/Negative Home Environment, we attempted to replicate this using the Parental Bonding Instrument (PBI), which comprises two subscales: parental care and overprotection. Diagnostic evaluations, including Q-Q plots, assessments of homoscedasticity, and inspection of influence statistics (e.g., IVF), indicated that the assumptions were adequately satisfied. 2.8 Frontal aperiodic exponent after eight weeks of SSRI treatment The change in the frontal aperiodic exponent after eight weeks of treatment was examined using a paired t-test in 39 treatment-adherent patients with a follow-up EEG. 2.9 Pretreatment frontal aperiodic exponent and treatment outcome To examine whether pretreatment frontal aperiodic exponents were associated with antidepressant effects, a linear regression analysis was conducted using the percentage change in HAMD 6 from baseline to weeks 4 and 8, with age and sex included as covariates (Supplementary Table 3). Confidence intervals and p -values were estimated using 1,000 bootstrap resamples to improve robustness. FDR correction was applied to adjust for multiple comparisons. Post hoc, we conducted a logistic regression (also with bootstrapping) with treatment response at week 8 (> 50% reduction in HAMD 6 from baseline). Three patients had dropped out between weeks 7 and 8 due to adverse side effects, acute suicidality and hospitalisation, or lost contact. Based on their deterioration and limited symptom reduction at the prior week 4 assessment, we coded them as non-responding to treatment (n = 83 patients). Age and sex were included as covariates. Wald tests were used to assess the significance of predictors, and model performance was evaluated using accuracy and area under the curve (AUC). Logistic regression models (with bootstrapping) were fitted to assess the association between the frontal aperiodic exponent and the presence of insomnia and tension side effects during the first week of treatment, while controlling for age and sex. 3. Results Participants were 18–60 years old and 72% female. There were no significant differences in age ( U = 1294, p = 0.11) or sex distribution (Odds ratio: 1.06, p = 1.00) between patients and HC. Additional demographics are in Table 1 . Table 1 Group Characteristics Data presented as mean and SD or n and %. HAMD 17 : 17-item Hamilton Depression Rating Scale. Education level was rated on a scale of 1–5, with 1 corresponding to elementary school and 5 corresponding to higher education, e.g., a master’s degree. a Data was only available for 74 patients and 34 HC, b 76 patients and 34 HC, c 90 patients, and d 86 patients and 34 HC. As is typical, familial predisposition was more frequent among patients than HC (OR = 0.23 [0.07; 0.70], p = 0.006), and patients also had greater childhood trauma than HC (Cohen’s d = 0.91 [0.48; 1.33], p < 0.001). MDD (n = 91) HC ( n = 35) Sex (female) 66 (73%) 25 (71%) Age ( years ) 27.4 (8.4) 29.9 (10.3) Education level a 3.3 (1.6) 4.2 (1.3) Familial predisposition ( present ) a 45 (39%) 10 (29%) Childhood trauma b 29.7 (19.2) 16 (9.3) First episode depression c 39 (43%) BDI-II d 33.5 (8.0) 2.9 (3.3) SHAPS d 7.7 (3.2) 0.3 (0.8) HAMD 17 22.9 (3.4) 3.1 Greater frontal aperiodic exponent in MDD compared with HC Frontal exponent was significantly greater (0.081 [0.008; 0.155], ω²ₚ = 0.03, Cohen’s d = 0.44) in patients than HCs (F(1, 122) = 4.80, p = 0.030, Fig. 1 ). There was, as expected, a significant negative effect of age (ω²ₚ = 0.21, p < 0.001), but no sex effect on the exponent ( p = 0.393). Age showed a strong negative effect across brain regions ( p < .001, ω²ₚ = 0.22), while sex did not ( p = 0.460). There was no significant main effect of region ( p = 0.191) and no interaction between region and group ( p = 0.898), suggesting group differences were not region-specific. There was a significant interaction between region and sex ( p < .001), although the effect size was negligible (ω²ₚ = 0.007; Figure S2). Among premenopausal women, the frontal exponent was significantly higher in patients than controls ( F (1, 64) = 4.36, p = 0.041, ω²ₚ = 0.045, d = 0.59). Hormonal contraceptive type did not affect exponents ( p = 0.440), and there was no significant interaction between diagnostic group and hormonal contraceptive type ( p = 0.203; Figure S3). 3.2 Frontal aperiodic exponent and symptoms, exposures and predispositions We examined how childhood trauma, familial predisposition and depression symptoms related to the frontal exponent using separate linear regression models with and without group to determine whether associations reflected true dimensional effects or depression status (Table S3). Anhedonia showed a significant positive association with the frontal exponent ( β = 0.251, p = 0.005, p FDR = 0.019), but this effect was reduced and nonsignificant after adjusting for diagnostic group (β = 0.183, p = 0.142). Depressive symptom severity demonstrated a similar pattern, with a significant association (β = 0.182, p = 0.030, p FDR = 0.059) that was reduced and non-significant when controlling for group (β = 0.110, p = 0.555). This suggests that the relation with anhedonia and depressive symptoms primarily reflects the diagnostic group rather than a dimensional effect. Familial predisposition for depression showed no significant associations with frontal exponent in either model ( p values ≥ 0.588). In contrast, childhood maltreatment showed a significant negative association with frontal exponent both before (β = -0.182, p = 0.028, p FDR = 0.059) and after controlling for depression status (β = -0.296, p FDR = 0.003, Fig. 2 ). This model explained the most variance (adjusted R² = 0.347, compared to R² ≤ 0.243, Table S3), signifying that it provides the most comprehensive explanation of the observed variance in frontal aperiodic activity. Neglect/Negative Home Atmosphere primarily drove the overall association (β = -0.301, p = 0.004), while Sexual Abuse and Punishment were not significant ( p ≥ 0.390). We further examined the home atmosphere (Table S4). Maternal overprotection demonstrated a significant negative association with frontal exponent (β = -0.210, p = 0.036), while maternal care showed no significant association (β = 0.003, p = 0.297). In contrast, paternal care showed a positive association (β = 0.277, p = 0.006), while paternal overprotection showed no significant effect ( p = 0.997). 3.3 Frontal aperiodic exponent after SSRI treatment The frontal exponent did not significantly change after eight weeks of treatment (Cohen’s d = 0.11 [-0.43; 0.22], p = 0.501, Figure S4). 3.4 Pretreatment frontal aperiodic exponent and treatment outcomes Pretreatment frontal aperiodic exponent was not associated with baseline depression severity (HAMD 17 ; β = 0.008 [-0.004;0.020], p = 0.300) or with change in depression severity at weeks four (β = -0.24 [-38.8; 39.1], p = 0.965) and eight (β = -35.0 [–70.0, 3.5], p = 0.077, p -FDR = 0.154). The frontal aperiodic exponent was not associated with week eight treatment response ( p = 0.703) or SSRI side effects of insomnia or tension at week four ( p ≥ 0.477), and the logistic model performed poorly (accuracies of ≤63%, AUCs of ≤0.65). 4. Discussion This study explored aperiodic EEG activity as an indicator of cortical excitation-inhibition (E/I) balance in MDD. We found significantly greater frontal aperiodic exponents in unmedicated MDD patients compared to healthy controls, consistent with increased cortical inhibition. Second, childhood maltreatment, particularly neglect and negative home atmosphere, was robustly associated with flatter exponents, suggesting lasting alterations of E/I balance shaped by early adversity. Notably, familial predisposition to depression showed no association with aperiodic activity, indicating that childhood adversity rather than genetic vulnerability drives these neural alterations. Pretreatment exponents did not predict treatment outcomes or side effects, indicating limited prognostic value for conventional antidepressant response, and aperiodic exponent did not change after SSRI treatment. Together, these results suggest that aperiodic activity may index both state-related alterations in depression and long-term developmental influences, but not SSRI treatment response. 4.1 Greater aperiodic activity in MDD Our findings reveal moderately greater frontal aperiodic exponents (steeper slope) in unmedicated MDD patients compared to HCs, providing electrophysiological support for enhanced cortical inhibition relative to excitation 11 , 14 , 50 . This aligns with fMRI and TMS–EEG evidence for elevated inhibition in prefrontal circuits 51 , 52 and the GABAergic deficit hypothesis of depression, which suggests that chronic stress-induced impairments in GABAergic and glutamatergic systems lead to dysregulated synaptic inhibition in prefrontal regions 22 , 23 , 27 . However, our findings contrast with smaller studies reporting flatter aperiodic slopes in patients with depression 29 , 30 , while aligning with larger studies that find similar directional, but non-significant effects 31 , 32 . 4.2 Lower aperiodic activity from childhood trauma Childhood trauma, particularly neglect/negative home atmosphere , demonstrated a strong negative association with frontal aperiodic exponents (flatter slope) that not only remained significant when controlling for depression diagnosis but strengthened substantially. The lack of significant associations with sexual abuse and punishment likely reflects the predominantly sub-clinical trauma exposure in our sample, where chronic negative home atmosphere rather than discrete traumatic events characterised the adverse childhood experiences. Nonetheless, the model incorporating both diagnostic group status and childhood maltreatment also achieved the highest explained variance, indicating that trauma history provides unique and complementary information about cortical function beyond that captured by depressive state alone. This pattern suggests that early adversity shapes adult cortical function towards greater excitation through mechanisms that are independent of current depressive state, as observed in adults without depression 53 . This suggests that chronic environmental stressors and emotional neglect during development may be particularly detrimental to the establishment of optimal cortical E/I balance by leading to increased neural noise and compromised cortical organisation 48 , 54 . To replicate and extend these findings, we examined the quality of parental bonding. Maternal overprotection (i.e. overcontrol and intrusiveness) was associated with lower frontal exponents similar to the neglect/negative home atmosphere measure, while paternal care (warmth and affection) showed a robust positive association. These findings complementary suggest that specific dimensions of maternal and paternal restrictiveness and emotional availability differentially relate to adult cortical function, suggesting that fathers and mothers may contribute uniquely to the development of cortical excitation-inhibition balance. From a developmental neurobiology perspective, these findings align with research demonstrating that childhood maltreatment alters brain development trajectories 55 . Early adversity during sensitive periods can disrupt normal developmental processes, resulting in lasting alterations in cortical microcircuitry that persist into adulthood. The specificity of our findings to neglect and negative home atmosphere suggests that chronic emotional deprivation and unpredictable caregiving environments may be particularly toxic to developing inhibitory systems, though more severe maltreatment might produce even greater developmental disruption. Preclinical studies examining the effects of developmental stress have yielded mixed results, with some showing increased inhibition and others decreased inhibition depending on the specific stress paradigm, timing, and brain region examined 28 , 56 . This complexity likely reflects the multifactorial nature of E/I balance regulation 11 , 57 , where both excessive inhibition and insufficient inhibition can be pathological depending on circuit demands and developmental context 58 . Our finding that childhood trauma is associated with flatter slopes reflecting reduced inhibition (or increased noise) while current depression is associated with steeper slopes reflecting increased inhibition suggests that these phenomena may have distinct underlying mechanisms and temporal dynamics. Importantly, familial predisposition to depression showed no association with frontal aperiodic activity in either model configuration, indicating that environmental exposure rather than genetic vulnerability drives these neural alterations. This finding suggests that the neurobiological sequelae are mediated by experiential factors during critical developmental periods rather than inherited susceptibility. 4.3 Aperiodic activity and antidepressant treatment A change in E/I balance is proposed as a mechanism of action of antidepressants 59 , and it has been shown to decrease the frontal aperiodic exponent during sleep after one week of antidepressants in MDD 29 and after one week of escitalopram in healthy awake females 34 . In contrast, we found no change in frontal aperiodic activity after eight weeks of escitalopram treatment. This discrepancy may reflect temporal dynamics in antidepressant effects, whereby acute changes in aperiodic activity are later normalised through adaptive neural mechanisms. Alternatively, the observed differences may be state-dependent, as aperiodic slopes are naturally steeper during sleep due to circadian variations in E/I balance 60 , 61 , and antidepressant effects on aperiodic activity may only be detectable during sleep when baseline synchronisation is enhanced. The heterogeneous findings from neuromodulation studies underscore the complexity. While some studies of DBS, ECT and MST report correlations between steeper aperiodic slopes and depressive relief 35 – 37 , the opposite has also been observed in ECT and DBS 33 , 38 , with others showing no associations for DBS 32 . However, ECT increases seizure threshold throughout the treatment series and often steepens slopes, but heterogeneity likely reflects timing of EEG relative to sessions and post-seizure dynamics While pharmacological interventions gradually modulate neurotransmitter systems, neuromodulation techniques like ECT and DBS produce more immediate circuit-level effects with potentially variable recovery patterns. The frontal aperiodic exponent not only remained stable during SSRI treatment, but pretreatment frontal aperiodic activity was also not associated with treatment outcome, similar to ECT and MST 62 . Since one week of escitalopram induced aperiodic slope flattening, suggesting increased cortical excitability, in healthy females 34 , we hypothesised that this contributes to the common excitation-related side-effects of increased anxiety and insomnia during the first weeks of SSRI initiation. However, we found no association between pretreatment aperiodic activity and these SSRI-related symptoms. Collectively, there is no support that a change in aperiodic activity and E/I balance drives the antidepressant effect of SSRIs or is a potential prognostic biomarker of treatment effects. 4.4 Methodological considerations A major strength of this study is the relatively large sample of unmedicated patients with MDD and the inclusion of both familial predisposition and childhood maltreatment measures. Nonetheless, several methodological limitations should be considered. First, the cross-sectional design precludes causal inference regarding whether aperiodic changes reflect consequences or precursors of depression and early adversity. Second, we relied on awake resting-state recordings, which are clinically feasible but more variable than sleep EEG and may be less sensitive to subtle medication effects observed elsewhere 29 , 34 . Third, the temporal dynamics of treatment effects represent an important consideration. Antidepressants may produce acute changes in aperiodic activity within a week 29 , 34 . Our single-time-point assessment at eight weeks may have missed these early changes because treatment effects manifest differently during treatment. Finally, the physiological interpretation of the aperiodic exponent remains debated 63 – 65 . While several studies propose aperiodic measures linked to cortical E/I balance 14 , 18 , 50 , 54 , 66 , it may also reflect vigilance states or oscillatory-aperiodic interactions 67 , 68 . Nevertheless, aperiodic EEG activity offers a complementary and largely unexplored biomarker, providing a broader perspective compared to conventional oscillatory measures 15 , 68 . 5. Conclusion We observed greater frontal aperiodic exponents in unmedicated patients with MDD than HC, potentially indicating an E/I balance favouring frontocortical inhibition in depression. Childhood trauma, but not current stress, was negatively associated with frontal aperiodic exponent, suggesting childhood to be a sensitive period for establishing the adult aperiodic spectral profile. No significant relations were found between aperiodic activity and treatment outcomes. These findings contribute to understanding neurophysiological changes in depression and highlight aperiodic activity as a potential biomarker for investigating E/I balance in psychiatric disorders. Declarations Acknowledgements We gratefully acknowledge investigators from the NeuroPharm-1 study, Köhler-Forsberg Kristin, and the Center for Referral and Diagnostics, Mental Health Services, Capital Region of Copenhagen, for helping recruit patients. Author contributions KHA, KRJ, and CTI contributed to the conception and design of the study and wrote the draft of the manuscript. KHA, KRJ, and CTI performed the analyses. VGF, MBJ, and GMK conceptualised NeuroPharm, and CTI collected the data. All authors contributed to the interpretation and revised the manuscript. Competing interest SO is a co-founder and shareholder at DeepPsy AG, which CTI is also a shareholder of and has served as a consultant for. MBJ has given talks sponsored by H. Lundbeck and Boehringer Ingelheim. GMK has served as a consultant for SAGE Therapeutics and Sanos. VGF has served as a consultant for SAGE Therapeutics and given talks sponsored by Lundbeck A/S, Janssen-Cilag A/S and Gedeon-Richter A/S. The other authors have nothing to disclose. Role of Funding KHA and KRJ were supported by the Research Fund of the Mental Health Services – Capital Region of Denmark. CTI was supported by the University of Macau (SRG2023–00040-ICI and MYRG-GRG2024-00022-ICI). KHA, KRJ, CTI, and VGF were also funded by The Lundbeck Foundation (R279-2018-1145). The Innovation Fund Denmark (4108-00004B) funded the NeuroPharm study. References Fava M, Davidson KG. Definition and epidemiology of treatment-resistant depression. 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Circadian dynamics in measures of cortical excitation and inhibition balance. Sci Rep 2016; 6: 33661. Schneider B, Szalárdy O, Ujma PP, Simor P, Gombos F, Kovács I et al. Scale-free and oscillatory spectral measures of sleep stages in humans. Front Neuroinformatics 2022; 16: 989262. Smith SE, Kosik EL, Engen Q van, Hill AT, Zomorrodi R, Blumberger DM et al. Magnetic seizure therapy and electroconvulsive therapy increase frontal aperiodic activity. Medrxiv 2023; 13: 347. Hegerl U, Wilk K, Olbrich S, Schoenknecht P, Sander C. Hyperstable regulation of vigilance in patients with major depressive disorder. World J Biol Psychiatry 2012; 13: 436–446. Olbrich S, Tränkner A, Surova G, Gevirtz R, Gordon E, Hegerl U et al. CNS- and ANS-arousal predict response to antidepressant medication: Findings from the randomized iSPOT-D study. J Psychiatr Res 2016; 73: 108–115. Ip C-T, Ganz M, Dam VH, Ozenne B, Rüesch A, Köhler-Forsberg K et al. NeuroPharm study: EEG wakefulness regulation as a biomarker in MDD. J Psychiatr Res 2021; 141: 57–65. Lendner JD, Helfrich RF, Mander BA, Romundstad L, Lin JJ, Walker MP et al. An electrophysiological marker of arousal level in humans. eLife 2020; 9: e55092. Salvatore SV, Lambert PM, Benz A, Rensing NR, Wong M, Zorumski CF et al. Periodic and aperiodic changes to cortical EEG in response to pharmacological manipulation. bioRxiv 2023; 09: 558828. Brake N, Duc F, Rokos A, Arseneau F, Shahiri S, Khadra A et al. A neurophysiological basis for aperiodic EEG and the background spectral trend. Nat Commun 2024; 15: 1514. Additional Declarations Yes SO is a co-founder and shareholder at DeepPsy AG, which CTI is also a shareholder of and has served as a consultant for. MBJ has given talks sponsored by H. Lundbeck and Boehringer Ingelheim. GMK has served as a consultant for SAGE Therapeutics and Sanos. VGF has served as a consultant for SAGE Therapeutics and given talks sponsored by Lundbeck A/S, Janssen-Cilag A/S and Gedeon-Richter A/S. The other authors have nothing to disclose. Supplementary Files Supplementarymaterial.docx Supplementary material Cite Share Download PDF Status: Under Review Version 1 posted Review # 2 received at journal 30 Mar, 2026 Reviewer # 2 agreed at journal 19 Mar, 2026 Review # 1 received at journal 17 Oct, 2025 Reviewer # 1 agreed at journal 13 Oct, 2025 Reviewers invited by journal 13 Oct, 2025 Editor assigned by journal 04 Sep, 2025 Submission checks completed at journal 04 Sep, 2025 First submitted to journal 03 Sep, 2025 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. 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14:13:39","extension":"xml","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":156865,"visible":true,"origin":"","legend":"","description":"","filename":"2025TP0021140structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7530123/v1/136341e40a236c43aac014e4.xml"},{"id":100896310,"identity":"d1d5526b-2642-4b8a-8c15-d5ec2bc7635e","added_by":"auto","created_at":"2026-01-22 14:13:32","extension":"html","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":174803,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7530123/v1/72b71c3b111cc40937ce134f.html"},{"id":100896314,"identity":"68958538-9ff3-40d3-886e-446009066006","added_by":"auto","created_at":"2026-01-22 14:13:33","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":289255,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGreater aperiodic exponents were in MDD patients than in HC\u003c/strong\u003e\u003cbr\u003e\nA) Frontal aperiodic exponents with mean and SD for MDD patients and HC. B) Topoplot of aperiodic exponents in MDD patients and HC, and C) group difference.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7530123/v1/23aa30a7ac1fa61646241932.jpeg"},{"id":100896320,"identity":"26f605cd-9968-4271-b059-f5e829fc5185","added_by":"auto","created_at":"2026-01-22 14:13:34","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":42452,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMarginal effects of childhood trauma and depression on frontal aperiodic exponent.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMarginal effects plot demonstrating the association between childhood trauma exposure and frontal aperiodic exponent, with comparison between healthy controls (HC) and patients with unmedicated major depressive disorder (MDD). The continuous relationship shows decreasing frontal aperiodic exponent with increasing childhood trauma exposure (β = -0.296 [-0.207; -0.057], \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001). Group comparison reveals significantly higher frontal aperiodic exponent in MDD compared to HC (β = 0.145 [0.068; 0.221], \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001). Models were adjusted for age and sex. Error bars represent 95% confidence intervals. Tick marks along the x-axis indicate the distribution of childhood trauma values in the sample.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7530123/v1/a34259502cfa07ef3f2d664c.jpg"},{"id":100952794,"identity":"18abfab2-c9a2-4eee-8284-940c539fb552","added_by":"auto","created_at":"2026-01-23 07:18:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1368542,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7530123/v1/19edc150-a38f-4c66-a84d-cb3a6a2d462f.pdf"},{"id":100950138,"identity":"ad116f6e-a1bd-49e7-836d-54418aa334b9","added_by":"auto","created_at":"2026-01-23 07:06:57","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1823231,"visible":true,"origin":"","legend":"Supplementary material","description":"","filename":"Supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-7530123/v1/86fc8f431b0b74646264c6a5.docx"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e\nSO is a co-founder and shareholder at DeepPsy AG, which CTI is also a shareholder of and has served as a consultant for. MBJ has given talks sponsored by H. Lundbeck and Boehringer Ingelheim. GMK has served as a consultant for SAGE Therapeutics and Sanos. VGF has served as a consultant for SAGE Therapeutics and given talks sponsored by Lundbeck A/S, Janssen-Cilag A/S and Gedeon-Richter A/S. The other authors have nothing to disclose.","formattedTitle":"Aperiodic brain activity in major depression: Increased inhibition and developmental effects of childhood maltreatment","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe underlying pathophysiology of depression remains unclear. Up to one-third of patients with Major depressive disorder (MDD) are resistant to standard pharmacological treatment \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, and many experience recurrence \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e or undesired medication side effects \u003csup\u003e\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Hence, elucidating the neurobiology and identifying predictive biomarkers of treatment outcomes is pressing \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eElectroencephalography (EEG) has long been investigated as a tool for this purpose, and conventional oscillatory markers have shown promise for predicting treatment outcomes in depression \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e and informing personalised treatment approaches \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Recent methodological advances extend this approach by focusing on the aperiodic component of EEG signals, which has been historically overlooked as \"noise\" \u003csup\u003e\u003cspan additionalcitationids=\"CR12 CR13\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. EEG power spectra can be decomposed into rhythmic oscillations (periodic) \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e and a broadband aperiodic 1/\u003cem\u003ef\u003c/em\u003e component, the latter quantified by the aperiodic exponent \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Aperiodic activity follows a scale-free distribution, in which power decreases with frequency, and has been proposed as a non-invasive index of cortical excitation-inhibition (E/I) balance \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Such a power law relationship is conveniently plotted in a double logarithmic plot and characterised by the y-axis intercept (offset) and the 1/\u003cem\u003ef\u003c/em\u003e\u003csup\u003e\u003cem\u003eX\u003c/em\u003e\u003c/sup\u003e slope derived from a linear fit to the original EEG power spectrum density \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Anaesthesia reliably shifts this balance toward inhibition, producing a greater exponent and steeper slopes \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eDisrupted E/I balance is implicated in depression pathophysiology \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, particularly within prefrontal circuits supporting emotional regulation and cognitive control \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. The GABAergic deficit hypothesis posits that chronic stress impairs inhibitory neurotransmission, contributing to core depressive symptomatology \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Early-life stress, especially childhood maltreatment, is a potent risk factor for adult depression \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e and may induce lasting cortical E/I balance changes during critical developmental periods, creating enduring vulnerability \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. This developmental perspective suggests that aperiodic measures might capture both state-related changes in MDD and long-term neurobiological vulnerability shaped by early adversity \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eYet, studies examining aperiodic activity in depression have yielded conflicting results. Two small studies (\u0026le;44 patients) observed flatter aperiodic slopes in patients with MDD than healthy controls (HC) \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e, whereas larger studies (\u0026le;119 patients) reported no difference \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Supporting its clinical relevance, an intracranial EEG study in treatment-resistant depression found that fluctuations in the 1/\u003cem\u003ef\u003c/em\u003e slope within the ventromedial prefrontal cortex closely tracked symptom severity over minutes to hours, with flatter slopes consistently associated with clinical improvement.\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e However, no study has examined how genetic predisposition or childhood trauma, leaving developmental and heritable contributions to aperiodic activity unexplored.\u003c/p\u003e\u003cp\u003eRegarding depression treatment, short-term escitalopram flatten slopes in healthy females \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e, consistent with increased cortical excitation. In contrast, steeper frontal aperiodic slopes have been observed after electroconvulsive therapy (ECT), which mechanistically increases seizure threshold throughout treatment series, and magnetic seizure therapy (MST) in treatment-resistant patients \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. More broadly, evidence from anaesthesia further suggests that the aperiodic exponent may also index the presence of consciousness itself. In healthy participants, steeper broadband slopes during unconsciousness (xenon/propofol) and wake-like exponents with ketamine, which selectively flattens higher frequencies (20\u0026ndash;40 Hz)\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Collectively, these findings highlight the exponent\u0026rsquo;s sensitivity to drug-induced changes in E/I balance and conscious state. However, clinical studies of neuromodulation are inconsistent: with some studies linking steeper slopes to symptom relief \u003csup\u003e\u003cspan additionalcitationids=\"CR36\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e and others reporting the opposite \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. Thus, the role of aperiodic activity in antidepressant mechanisms and its potential utility as a predictive biomarker remain unresolved.\u003c/p\u003e\u003cp\u003eTo address these gaps, we investigated aperiodic EEG activity in a well-characterised cohort of unmedicated MDD patients and HC \u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. First, we assessed whether patients exhibit altered frontal aperiodic activity compared to controls, providing evidence for disrupted cortical E/I balance in depression. Second, we examined whether risk factors for depression, including childhood maltreatment and familial predisposition, are reflected in aperiodic activity, to disentangle developmental and heritable pathways. Third, we evaluated the clinical utility of this marker by assessing whether pretreatment aperiodic measures predict selective serotonin reuptake inhibitor (SSRI) response or excitation-related side effects, i.e. insomnia and tension. Lastly, we explored whether the aperiodic activity changes over the course of treatment. We hypothesised that MDD patients would demonstrate steeper frontal exponents reflecting increased cortical inhibition consistent with the GABAergic deficit hypothesis, that childhood maltreatment would show independent associations with altered aperiodic activity, and that pretreatment aperiodic measures would predict clinical outcomes.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cp\u003eWe used data from the NeuroPharm-1 study, a 12-week open-label clinical trial investigating biomarkers for antidepressant treatment (clinicaltrial.gov: NCT02869035). The National Committee on Health Research Ethics approved the study (H-15017713). A detailed study protocol is available elsewhere \u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. The current analysis on aperiodic activity was conducted as an exploratory extension and was not prespecified in the original study protocol.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Participants\u003c/h2\u003e\u003cp\u003ePatients 18\u0026ndash;65 years old with a moderate to severe episode of depression consistent with ICD-10 criteria for less than two years, and a Hamilton Depression Rating Scale (HAMD\u003csub\u003e17\u003c/sub\u003e)\u0026thinsp;\u0026gt;\u0026thinsp;17 were recruited through the primary health care centre or directly referred by five collaborating general practitioners. Their diagnosis was confirmed by a certified psychiatrist using the Mini-International Neuropsychiatric Interview \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. Ninety-two patients underwent pretreatment EEG (one patient was excluded due to spontaneous remission in the first week after assessment and was concluded not to be depressed). Of the remaining patients, 86 initiated treatment, and 39 treatment-adherent patients underwent a follow-up EEG after eight weeks. See the supplementary material and the CONSORT diagram (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) for more information.\u003c/p\u003e\u003cp\u003eThirty-five participants without current or past mental illness were included as HC.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Antidepressant treatment\u003c/h2\u003e\u003cp\u003ePatients started treatment with escitalopram, individually adjusted to 10\u0026ndash;20 mg daily depending on response and side effects. Per standard practice, patients experiencing intolerable side-effects or \u0026lt;\u0026thinsp;25% reduction in HAMD\u003csub\u003e6\u003c/sub\u003e, a 6-item subscale of the HAMD\u003csub\u003e17\u003c/sub\u003e capturing core depressive symptoms \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e, from pretreatment to week four were offered to switch to duloxetine (n\u0026thinsp;=\u0026thinsp;6) and were individually adjusted to 30\u0026ndash;90 mg daily. Plasma medication levels at week eight were assessed to evaluate treatment adherence. Arousal-related SSRI-side effects were evaluated with two items from the clinician-rated \u0026ldquo;Udvalg for kliniske unders\u0026oslash;gelser\u0026rdquo; (UKU) scale \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. Item 1 \u0026ldquo;Inner unrest/Tension\u0026rdquo;, covering anxiety, jitteriness and restlessness, and item 2 \u0026ldquo;Insomnia\u0026rdquo;, were noted if reported within the initial four weeks of treatment when these side effects typically appear \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Childhood trauma, predispositions and symptoms\u003c/h2\u003e\u003cp\u003e The presence of familial predisposition was defined as having a first-degree relative with past or present depression or suicide attempt. Childhood maltreatment was assessed by the total score from the Child Abuse and Trauma Scale (CATS) \u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. The Parental Bonding Instrument (PBI) complemented the CATS Neglect/Negative Home Atmosphere subscale.\u003c/p\u003e\u003cp\u003eAnhedonia was measured by the Snaith\u0026ndash;Hamilton Pleasure Scale (SHAPS) \u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e and depression severity by the Beck Depression Inventory\u0026ndash;II (BDI-II).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Aperiodic activity\u003c/h2\u003e\u003cp\u003eResting state EEG was recorded in four 3-minute periods, counterbalanced as OCOC or COCO (O: eyes open, C: eyes closed) between subjects using a 256-channel system HydroCel Sensor Net system (EGI, Inc., Eugene, OR) using a sampling rate of 1000 Hz, a high-pass filter of 0.1 Hz and a low-pass filter of 100 Hz. Impedance was maintained below 50 kΩ.\u003c/p\u003e\u003cp\u003eOnly eyes-closed data were included in the current analysis. Data were average-referenced; bad channels interpolated; band-pass filtered (0.5\u0026ndash;70 Hz) with 50 Hz notch; ocular/artefactual components removed via ICA; and 1-s epochs with residual artefact were rejected.\u003c/p\u003e\u003cp\u003ePower spectral densities (PSDs) were computed from 1\u0026ndash;40 Hz using the MNE-Python toolbox, consistent with prior work on aperiodic EEG dynamics \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Welch\u0026rsquo;s method was applied using 4-s sliding windows (50% overlap, zero-padding), and PSDs were averaged across time segments before input into the FOOOF (Fitting Oscillations \u0026amp; One-Over-F) toolbox v1.1.0 \u003csup\u003e13\u003c/sup\u003e. FOOOF parameterises periodic and aperiodic components by applying Gaussian fits to oscillatory peaks and subtracting them from the spectrum, isolating the aperiodic component. Model settings included fixed aperiodic mode, peak width limit of 1\u0026ndash;8 Hz, a maximum of eight peaks, and a peak threshold of three. Aperiodic exponents were then extracted for each channel, and regional values were derived by averaging electrodes within frontal, temporal, parietal, and occipital clusters, with frontal activity serving as the primary focus.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Statistics\u003c/h2\u003e\u003cp\u003eStatistics were done using JASP 0.95.1 \u003csup\u003e47\u003c/sup\u003e, estimates are presented with [95%-confidence intervals], and results \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered statistically significant.\u003c/p\u003e\u003cp\u003eThe age between patients and HC was compared using a Mann\u0026ndash;Whitney \u003cem\u003eU\u003c/em\u003e test due to leftward skew (median age 25 years) and sex distribution by Fisher\u0026rsquo;s exact test. Despite no significant age or sex group differences, all models below were adjusted for age, as the aperiodic exponent linearly decreases with age in adulthood \u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e,\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e, and sex.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.6 Group differences\u003c/h2\u003e\u003cp\u003eAn ANCOVA (type III) was performed to compare the frontal aperiodic exponent in MDD patients vs. HC with age and sex as covariates. We also explored group differences in the aperiodic exponent across the other three regions (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn an exploratory analysis of the effect of hormonal contraceptives on the frontal exponent, premenopausal women with contraceptive use information were grouped into non-users, and those using combination oral contraceptives (COC), levonorgestrel-releasing intrauterine devices (LNG-IUD) and progestin-only oral contraceptives (POC). As there were no healthy POC users, the five patients with POC were omitted from the analysis (Table S2). We performed an ANCOVA with group, hormonal contraceptive use (None, COC, LNG-IUD), and their interaction as fixed factors with age as a covariate.\u003c/p\u003e\u003cp\u003eSimple contrasts were used to follow up significant group effects. The ANCOVA assumptions were met, with no violation of the homogeneity of variances and normally distributed residuals.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e2.7 Familial predisposition, childhood trauma and depressive symptoms\u003c/h2\u003e\u003cp\u003eTo examine the associations between frontal exponent and depression risk factors and symptom measures, we conducted four separate linear regression models with frontal exponent as the dependent variable. Each model included one primary predictor: childhood trauma (CATS), anhedonia (SHAPS), depressive symptoms (BDI-II), or familial predisposition. All models included age and sex. We fitted each model twice: first without group as a covariate to examine overall associations, and second, including diagnostic group (MDD vs. HC) to assess dimensional relationships independent of depressive state. This approach allowed us to determine whether associations reflected diagnostic group differences or represented dimensional effects across the sample. Multiple comparisons across the four predictors were controlled using false discovery rate (FDR) correction (Benjamini\u0026ndash;Hochberg).\u003c/p\u003e\u003cp\u003ePost hoc, we tested three CATS subscales in models adjusted for group, age, and sex. Having observed a strong relationship with the CATS subscale Neglect/Negative Home Environment, we attempted to replicate this using the Parental Bonding Instrument (PBI), which comprises two subscales: parental care and overprotection.\u003c/p\u003e\u003cp\u003eDiagnostic evaluations, including Q-Q plots, assessments of homoscedasticity, and inspection of influence statistics (e.g., IVF), indicated that the assumptions were adequately satisfied.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e2.8 Frontal aperiodic exponent after eight weeks of SSRI treatment\u003c/h2\u003e\u003cp\u003eThe change in the frontal aperiodic exponent after eight weeks of treatment was examined using a paired t-test in 39 treatment-adherent patients with a follow-up EEG.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e2.9 Pretreatment frontal aperiodic exponent and treatment outcome\u003c/h2\u003e\u003cp\u003eTo examine whether pretreatment frontal aperiodic exponents were associated with antidepressant effects, a linear regression analysis was conducted using the percentage change in HAMD\u003csub\u003e6\u003c/sub\u003e from baseline to weeks 4 and 8, with age and sex included as covariates (Supplementary Table\u0026nbsp;3).\u003c/p\u003e\u003cp\u003eConfidence intervals and \u003cem\u003ep\u003c/em\u003e-values were estimated using 1,000 bootstrap resamples to improve robustness. FDR correction was applied to adjust for multiple comparisons.\u003c/p\u003e\u003cp\u003ePost hoc, we conducted a logistic regression (also with bootstrapping) with treatment response at week 8 (\u0026gt;\u0026thinsp;50% reduction in HAMD\u003csub\u003e6\u003c/sub\u003e from baseline). Three patients had dropped out between weeks 7 and 8 due to adverse side effects, acute suicidality and hospitalisation, or lost contact. Based on their deterioration and limited symptom reduction at the prior week 4 assessment, we coded them as non-responding to treatment (n\u0026thinsp;=\u0026thinsp;83 patients). Age and sex were included as covariates. Wald tests were used to assess the significance of predictors, and model performance was evaluated using accuracy and area under the curve (AUC).\u003c/p\u003e\u003cp\u003eLogistic regression models (with bootstrapping) were fitted to assess the association between the frontal aperiodic exponent and the presence of insomnia and tension side effects during the first week of treatment, while controlling for age and sex.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eParticipants were 18\u0026ndash;60 years old and 72% female. There were no significant differences in age (\u003cem\u003eU\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1294, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.11) or sex distribution (Odds ratio: 1.06, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.00) between patients and HC. Additional demographics are 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\u003e\u003cb\u003eGroup Characteristics\u003c/b\u003e Data presented as mean and SD or n and %. HAMD\u003csub\u003e17\u003c/sub\u003e: 17-item Hamilton Depression Rating Scale. Education level was rated on a scale of 1\u0026ndash;5, with 1 corresponding to elementary school and 5 corresponding to higher education, e.g., a master\u0026rsquo;s degree. \u003csup\u003ea\u003c/sup\u003e Data was only available for 74 patients and 34 HC, \u003csup\u003eb\u003c/sup\u003e 76 patients and 34 HC, \u003csup\u003ec\u003c/sup\u003e 90 patients, and \u003csup\u003ed\u003c/sup\u003e 86 patients and 34 HC. As is typical, familial predisposition was more frequent among patients than HC (OR\u0026thinsp;=\u0026thinsp;0.23 [0.07; 0.70], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006), and patients also had greater childhood trauma than HC (Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.91 [0.48; 1.33], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMDD (n\u0026thinsp;=\u0026thinsp;91)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHC (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;35)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex (female)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e66 (73%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25 (71%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (\u003cem\u003eyears\u003c/em\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27.4 (8.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29.9 (10.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation level \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.3 (1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.2 (1.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFamilial predisposition (\u003cem\u003epresent\u003c/em\u003e) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e45 (39%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10 (29%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChildhood trauma \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29.7 (19.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16 (9.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFirst episode depression \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e39 (43%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBDI-II \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33.5 (8.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.9 (3.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSHAPS \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.7 (3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.3 (0.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHAMD\u003csub\u003e17\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22.9 (3.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Greater frontal aperiodic exponent in MDD compared with HC\u003c/h2\u003e\u003cp\u003eFrontal exponent was significantly greater (0.081 [0.008; 0.155], ω\u0026sup2;ₚ = 0.03, Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.44) in patients than HCs (F(1, 122)\u0026thinsp;=\u0026thinsp;4.80, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.030, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). There was, as expected, a significant negative effect of age (ω\u0026sup2;ₚ = 0.21, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), but no sex effect on the exponent (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.393).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAge showed a strong negative effect across brain regions (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, ω\u0026sup2;ₚ = 0.22), while sex did not (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.460). There was no significant main effect of region (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.191) and no interaction between region and group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.898), suggesting group differences were not region-specific. There was a significant interaction between region and sex (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), although the effect size was negligible (ω\u0026sup2;ₚ = 0.007; Figure S2).\u003c/p\u003e\u003cp\u003eAmong premenopausal women, the frontal exponent was significantly higher in patients than controls (\u003cem\u003eF\u003c/em\u003e(1, 64)\u0026thinsp;=\u0026thinsp;4.36, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.041, ω\u0026sup2;ₚ = 0.045, \u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.59). Hormonal contraceptive type did not affect exponents (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.440), and there was no significant interaction between diagnostic group and hormonal contraceptive type (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.203; Figure S3).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Frontal aperiodic exponent and symptoms, exposures and predispositions\u003c/h2\u003e\u003cp\u003eWe examined how childhood trauma, familial predisposition and depression symptoms related to the frontal exponent using separate linear regression models with and without group to determine whether associations reflected true dimensional effects or depression status (Table S3).\u003c/p\u003e\u003cp\u003eAnhedonia showed a significant positive association with the frontal exponent (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.251, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005, \u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e = 0.019), but this effect was reduced and nonsignificant after adjusting for diagnostic group (β\u0026thinsp;=\u0026thinsp;0.183, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.142). Depressive symptom severity demonstrated a similar pattern, with a significant association (β\u0026thinsp;=\u0026thinsp;0.182, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.030, \u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e = 0.059) that was reduced and non-significant when controlling for group (β\u0026thinsp;=\u0026thinsp;0.110, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.555). This suggests that the relation with anhedonia and depressive symptoms primarily reflects the diagnostic group rather than a dimensional effect.\u003c/p\u003e\u003cp\u003eFamilial predisposition for depression showed no significant associations with frontal exponent in either model (\u003cem\u003ep\u003c/em\u003e values \u0026ge; 0.588). In contrast, childhood maltreatment showed a significant negative association with frontal exponent both before (β = -0.182, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.028, \u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e = 0.059) and after controlling for depression status (β = -0.296, \u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e = 0.003, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This model explained the most variance (adjusted R\u0026sup2; = 0.347, compared to R\u0026sup2; \u0026le; 0.243, Table S3), signifying that it provides the most comprehensive explanation of the observed variance in frontal aperiodic activity. Neglect/Negative Home Atmosphere primarily drove the overall association (β = -0.301, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004), while Sexual Abuse and Punishment were not significant (\u003cem\u003ep\u003c/em\u003e \u0026ge; 0.390).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWe further examined the \u003cem\u003ehome atmosphere\u003c/em\u003e (Table S4). Maternal overprotection demonstrated a significant negative association with frontal exponent (β = -0.210, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.036), while maternal care showed no significant association (β\u0026thinsp;=\u0026thinsp;0.003, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.297). In contrast, paternal care showed a positive association (β\u0026thinsp;=\u0026thinsp;0.277, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006), while paternal overprotection showed no significant effect (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.997).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Frontal aperiodic exponent after SSRI treatment\u003c/h2\u003e\u003cp\u003eThe frontal exponent did not significantly change after eight weeks of treatment (Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.11 [-0.43; 0.22], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.501, Figure S4).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Pretreatment frontal aperiodic exponent and treatment outcomes\u003c/h2\u003e\u003cp\u003ePretreatment frontal aperiodic exponent was not associated with baseline depression severity (HAMD\u003csub\u003e17\u003c/sub\u003e; β\u0026thinsp;=\u0026thinsp;0.008 [-0.004;0.020], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.300) or with change in depression severity at weeks four (β = -0.24 [-38.8; 39.1], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.965) and eight (β = -35.0 [\u0026ndash;70.0, 3.5], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.077, \u003cem\u003ep\u003c/em\u003e-FDR\u0026thinsp;=\u0026thinsp;0.154).\u003c/p\u003e\u003cp\u003eThe frontal aperiodic exponent was not associated with week eight treatment response (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.703) or SSRI side effects of insomnia or tension at week four (\u003cem\u003ep\u003c/em\u003e \u0026ge; 0.477), and the logistic model performed poorly (accuracies of \u0026le;63%, AUCs of \u0026le;0.65).\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study explored aperiodic EEG activity as an indicator of cortical excitation-inhibition (E/I) balance in MDD. We found significantly greater frontal aperiodic exponents in unmedicated MDD patients compared to healthy controls, consistent with increased cortical inhibition. Second, childhood maltreatment, particularly neglect and negative home atmosphere, was robustly associated with flatter exponents, suggesting lasting alterations of E/I balance shaped by early adversity. Notably, familial predisposition to depression showed no association with aperiodic activity, indicating that childhood adversity rather than genetic vulnerability drives these neural alterations. Pretreatment exponents did not predict treatment outcomes or side effects, indicating limited prognostic value for conventional antidepressant response, and aperiodic exponent did not change after SSRI treatment. Together, these results suggest that aperiodic activity may index both state-related alterations in depression and long-term developmental influences, but not SSRI treatment response.\u003c/p\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Greater aperiodic activity in MDD\u003c/h2\u003e\u003cp\u003eOur findings reveal moderately greater frontal aperiodic exponents (steeper slope) in unmedicated MDD patients compared to HCs, providing electrophysiological support for enhanced cortical inhibition relative to excitation \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. This aligns with fMRI and TMS\u0026ndash;EEG evidence for elevated inhibition in prefrontal circuits \u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e,\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e and the GABAergic deficit hypothesis of depression, which suggests that chronic stress-induced impairments in GABAergic and glutamatergic systems lead to dysregulated synaptic inhibition in prefrontal regions \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. However, our findings contrast with smaller studies reporting flatter aperiodic slopes in patients with depression \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e, while aligning with larger studies that find similar directional, but non-significant effects \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Lower aperiodic activity from childhood trauma\u003c/h2\u003e\u003cp\u003eChildhood trauma, particularly \u003cem\u003eneglect/negative home atmosphere\u003c/em\u003e, demonstrated a strong negative association with frontal aperiodic exponents (flatter slope) that not only remained significant when controlling for depression diagnosis but strengthened substantially. The lack of significant associations with sexual abuse and punishment likely reflects the predominantly sub-clinical trauma exposure in our sample, where chronic negative home atmosphere rather than discrete traumatic events characterised the adverse childhood experiences. Nonetheless, the model incorporating both diagnostic group status and childhood maltreatment also achieved the highest explained variance, indicating that trauma history provides unique and complementary information about cortical function beyond that captured by depressive state alone.\u003c/p\u003e\u003cp\u003eThis pattern suggests that early adversity shapes adult cortical function towards greater excitation through mechanisms that are independent of current depressive state, as observed in adults without depression \u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. This suggests that chronic environmental stressors and emotional neglect during development may be particularly detrimental to the establishment of optimal cortical E/I balance by leading to increased neural noise and compromised cortical organisation \u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e,\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eTo replicate and extend these findings, we examined the quality of parental bonding. Maternal overprotection (i.e. overcontrol and intrusiveness) was associated with lower frontal exponents similar to the \u003cem\u003eneglect/negative home atmosphere\u003c/em\u003e measure, while paternal care (warmth and affection) showed a robust positive association. These findings complementary suggest that specific dimensions of maternal and paternal restrictiveness and emotional availability differentially relate to adult cortical function, suggesting that fathers and mothers may contribute uniquely to the development of cortical excitation-inhibition balance.\u003c/p\u003e\u003cp\u003eFrom a developmental neurobiology perspective, these findings align with research demonstrating that childhood maltreatment alters brain development trajectories \u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e. Early adversity during sensitive periods can disrupt normal developmental processes, resulting in lasting alterations in cortical microcircuitry that persist into adulthood. The specificity of our findings to neglect and negative home atmosphere suggests that chronic emotional deprivation and unpredictable caregiving environments may be particularly toxic to developing inhibitory systems, though more severe maltreatment might produce even greater developmental disruption.\u003c/p\u003e\u003cp\u003ePreclinical studies examining the effects of developmental stress have yielded mixed results, with some showing increased inhibition and others decreased inhibition depending on the specific stress paradigm, timing, and brain region examined \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e. This complexity likely reflects the multifactorial nature of E/I balance regulation \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e, where both excessive inhibition and insufficient inhibition can be pathological depending on circuit demands and developmental context \u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eOur finding that childhood trauma is associated with flatter slopes reflecting reduced inhibition (or increased noise) while current depression is associated with steeper slopes reflecting increased inhibition suggests that these phenomena may have distinct underlying mechanisms and temporal dynamics. Importantly, familial predisposition to depression showed no association with frontal aperiodic activity in either model configuration, indicating that environmental exposure rather than genetic vulnerability drives these neural alterations. This finding suggests that the neurobiological sequelae are mediated by experiential factors during critical developmental periods rather than inherited susceptibility.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003e4.3 Aperiodic activity and antidepressant treatment\u003c/h2\u003e\u003cp\u003eA change in E/I balance is proposed as a mechanism of action of antidepressants \u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e, and it has been shown to decrease the frontal aperiodic exponent during sleep after one week of antidepressants in MDD \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e and after one week of escitalopram in healthy awake females \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn contrast, we found no change in frontal aperiodic activity after eight weeks of escitalopram treatment. This discrepancy may reflect temporal dynamics in antidepressant effects, whereby acute changes in aperiodic activity are later normalised through adaptive neural mechanisms.\u003c/p\u003e\u003cp\u003eAlternatively, the observed differences may be state-dependent, as aperiodic slopes are naturally steeper during sleep due to circadian variations in E/I balance \u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e,\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e, and antidepressant effects on aperiodic activity may only be detectable during sleep when baseline synchronisation is enhanced.\u003c/p\u003e\u003cp\u003eThe heterogeneous findings from neuromodulation studies underscore the complexity. While some studies of DBS, ECT and MST report correlations between steeper aperiodic slopes and depressive relief \u003csup\u003e\u003cspan additionalcitationids=\"CR36\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e, the opposite has also been observed in ECT and DBS \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e, with others showing no associations for DBS \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. However, ECT increases seizure threshold throughout the treatment series and often steepens slopes, but heterogeneity likely reflects timing of EEG relative to sessions and post-seizure dynamics While pharmacological interventions gradually modulate neurotransmitter systems, neuromodulation techniques like ECT and DBS produce more immediate circuit-level effects with potentially variable recovery patterns.\u003c/p\u003e\u003cp\u003eThe frontal aperiodic exponent not only remained stable during SSRI treatment, but pretreatment frontal aperiodic activity was also not associated with treatment outcome, similar to ECT and MST \u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e. Since one week of escitalopram induced aperiodic slope flattening, suggesting increased cortical excitability, in healthy females \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e, we hypothesised that this contributes to the common excitation-related side-effects of increased anxiety and insomnia during the first weeks of SSRI initiation. However, we found no association between pretreatment aperiodic activity and these SSRI-related symptoms.\u003c/p\u003e\u003cp\u003eCollectively, there is no support that a change in aperiodic activity and E/I balance drives the antidepressant effect of SSRIs or is a potential prognostic biomarker of treatment effects.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003e4.4 Methodological considerations\u003c/h2\u003e\u003cp\u003eA major strength of this study is the relatively large sample of unmedicated patients with MDD and the inclusion of both familial predisposition and childhood maltreatment measures. Nonetheless, several methodological limitations should be considered. First, the cross-sectional design precludes causal inference regarding whether aperiodic changes reflect consequences or precursors of depression and early adversity. Second, we relied on awake resting-state recordings, which are clinically feasible but more variable than sleep EEG and may be less sensitive to subtle medication effects observed elsewhere \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Third, the temporal dynamics of treatment effects represent an important consideration. Antidepressants may produce acute changes in aperiodic activity within a week \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Our single-time-point assessment at eight weeks may have missed these early changes because treatment effects manifest differently during treatment. Finally, the physiological interpretation of the aperiodic exponent remains debated \u003csup\u003e\u003cspan additionalcitationids=\"CR64\" citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e. While several studies propose aperiodic measures linked to cortical E/I balance \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e,\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e,\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e, it may also reflect vigilance states or oscillatory-aperiodic interactions \u003csup\u003e\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e,\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e. Nevertheless, aperiodic EEG activity offers a complementary and largely unexplored biomarker, providing a broader perspective compared to conventional oscillatory measures \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eWe observed greater frontal aperiodic exponents in unmedicated patients with MDD than HC, potentially indicating an E/I balance favouring frontocortical inhibition in depression. Childhood trauma, but not current stress, was negatively associated with frontal aperiodic exponent, suggesting childhood to be a sensitive period for establishing the adult aperiodic spectral profile. No significant relations were found between aperiodic activity and treatment outcomes. These findings contribute to understanding neurophysiological changes in depression and highlight aperiodic activity as a potential biomarker for investigating E/I balance in psychiatric disorders.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eWe gratefully acknowledge investigators from the NeuroPharm-1 study, K\u0026ouml;hler-Forsberg Kristin, and the Center for Referral and Diagnostics, Mental Health Services, Capital Region of Copenhagen, for helping recruit patients.\u003c/p\u003e\n\u003ch2\u003eAuthor contributions\u003c/h2\u003e\n\u003cp\u003eKHA, KRJ, and CTI contributed to the conception and design of the study and wrote the draft of the manuscript. KHA, KRJ, and CTI performed the analyses. VGF, MBJ, and GMK conceptualised NeuroPharm, and CTI collected the data. All authors contributed to the interpretation and revised the manuscript.\u003c/p\u003e\n\u003ch2\u003eCompeting interest\u003c/h2\u003e\n\u003cp\u003eSO is a co-founder and shareholder at DeepPsy AG, which CTI is also a shareholder of and has served as a consultant for. MBJ has given talks sponsored by H. Lundbeck and Boehringer Ingelheim. GMK has served as a consultant for SAGE Therapeutics and Sanos. VGF has served as a consultant for SAGE Therapeutics and given talks sponsored by Lundbeck A/S, Janssen-Cilag A/S and Gedeon-Richter A/S. The other authors have nothing to disclose.\u003c/p\u003e\n\u003ch2\u003eRole of Funding\u003c/h2\u003e\n\u003cp\u003eKHA and KRJ were supported by the Research Fund of the Mental Health Services \u0026ndash; Capital Region of Denmark. CTI was supported by the University of Macau (SRG2023\u0026ndash;00040-ICI and MYRG-GRG2024-00022-ICI). KHA, KRJ, CTI, and VGF were also funded by The Lundbeck Foundation (R279-2018-1145). The Innovation Fund Denmark (4108-00004B) funded the NeuroPharm study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFava M, Davidson KG. 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Altered E/I balance has been proposed in major depressive disorder (MDD), but evidence from clinical cohorts remains limited and inconsistent, and the impact of developmental risk factors is unknown. We analysed resting-state EEG from 91 unmedicated MDD patients and 35 healthy controls enrolled in the NeuroPharm-1 study. Patients received 10\u0026ndash;20 mg of escitalopram treatment for 8 weeks, with 39 undergoing follow-up EEG. Before treatment, MDD patients showed significantly greater frontal aperiodic exponents compared to healthy controls (Cohen's \u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.44, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03), consistent with increased cortical inhibition in depression. Importantly, pretreatment frontal aperiodic exponent showed a strong negative association with childhood trauma severity (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), independent of current depressive symptoms and familial predisposition for depression, suggesting that early adversity leaves a lasting imprint on cortical dynamics. No associations were found with treatment, and aperiodic exponents remained unchanged during SSRI treatment. These findings demonstrate that aperiodic EEG activity captures state-related alterations in unmedicated depression and highlight long-term developmental signatures of childhood trauma. This underscores the potential of aperiodic measures as translational markers of environmentally shaped vulnerability in psychiatric disorders.\u003c/p\u003e","manuscriptTitle":"Aperiodic brain activity in major depression: Increased inhibition and developmental effects of childhood maltreatment","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-22 14:13:03","doi":"10.21203/rs.3.rs-7530123/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"This content is not available.","date":"2026-03-30T14:15:15+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-03-19T11:08:54+00:00","index":2,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-10-17T13:20:19+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-10-14T01:16:42+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2025-10-13T20:33:55+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-04T11:31:29+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-04T11:31:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"Translational Psychiatry","date":"2025-09-03T20:28:03+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"translational-psychiatry","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"tp","sideBox":"Learn more about [Translational Psychiatry](http://www.nature.com/tp/)","snPcode":"41398","submissionUrl":"https://mts-tp.nature.com/cgi-bin/main.plex","title":"Translational Psychiatry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fc71a258-e3d0-4445-bd53-ea2a73a8cbeb","owner":[],"postedDate":"January 22nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":56478778,"name":"Biological sciences/Physiology"},{"id":56478779,"name":"Health sciences/Biomarkers/Predictive markers"},{"id":56478780,"name":"Health sciences/Diseases/Psychiatric disorders/Depression"}],"tags":[],"updatedAt":"2026-01-22T14:13:03+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-22 14:13:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7530123","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7530123","identity":"rs-7530123","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}