Neuroplasticity-the brain's capacity to modify synaptic strength and connectivity-likely underlies both the pathophysiology of psychiatric disorders and the mechanisms through which treatments exert therapeutic effects. Direct assessment of plasticity requires measuring changes in synaptic responses, which remains technically challenging in humans. The most proximal human indicators are behavioral changes reflecting learning and memory, or physiological responses to neurostimulation paradigms that engage cortical circuits. More commonly, plasticity is inferred indirectly through postmortem analyses of neuronal and glial structure or via neuroimaging measures such as functional and structural connectivity. Together, these approaches suggest that altered and potentially reversible plasticity is central to understanding and treating psychiatric illness, but the field needs to be cautious about what is, what could be, and what is not plasticity.

BACKGROUND:Childhood maltreatment (CM), encompassing abuse and neglect, is highly prevalent and associated with elevated risk for major depressive disorder (MDD), posttraumatic stress disorder (PTSD), and other related conditions. However, the extent to which neuroanatomical alterations in MDD and PTSD are attributable to CM is uncertain. METHODS:Here, we analyzed CM and whole-brain magnetic resonance imaging (MRI) data from 3711 participants in the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) MDD and PTSD Working Groups (25 sites; mean age = 33.3 ± 13.0 years; 59.9% female). Normative modeling estimated deviation z scores for 14 subcortical volume, 68 cortical thickness (CT), and 68 surface area (SA) measures. To identify transdiagnostic effects, associations between CM and brain deviation scores were evaluated across all participants (patients and healthy control participants) stratified by sex and 3 age bins (pediatric, young adult, older adult). RESULTS:In young adults (ages 18-35), abuse was associated with larger volumes in the thalamus and pallidum, thinner isthmus cingulate and middle frontal regions, and thicker medial orbitofrontal cortex; there were no significant effects in pediatric (≤18 years) participants. The strongest effects were observed in young female adults (|β| = 0.07-0.22, q < .05): Greater abuse and neglect were correlated with smaller hippocampus and putamen volumes, thinner entorhinal cortex, and smaller SA in fusiform/inferior parietal regions and with larger SA in the orbitofrontal and occipital cortices. In males, abuse had widespread effects on CT and SA (|β| = 0.1-0.18, q < .05); effects for neglect were minimal. CONCLUSIONS:Our findings of age- and sex-specific instantiations of CM on brain morphometry highlight the importance of developmental context in understanding how adverse experiences shape neurobiological vulnerability to MDD and PTSD.

Posttraumatic stress disorder (PTSD) is a psychiatric condition that may develop after trauma exposure. PTSD is characterized by considerable clinical heterogeneity. The amygdala's key role in fear conditioning makes it an important focus for investigating the neurobiology of PTSD. However, associations between amygdala volume and PTSD have been inconsistent. The amygdala consists of functionally distinct nuclei. Specific associations between amygdala nuclei volumes and PTSD may account for previous discrepancies between PTSD and whole amygdala volume. This study investigates the associations between amygdala nuclei volumes, PTSD diagnosis, severity, symptom cluster scores, age of onset and childhood trauma. Individuals with a PTSD diagnosis (n = 771) and controls (n = 1 081, 72% trauma-exposed) were sourced from the Enhancing Neuro-Imaging Genetics through Meta-Analysis and Psychiatric Genomics Consortium (mean age = 32.4 years, (SD = 13 years), 60% male). Nine amygdala nuclei volumes were compared to PTSD diagnosis, age of onset, overall severity, symptom cluster scores (re-experiencing, arousal, and avoidance/emotional numbing), and childhood trauma subscales. Analyses were performed using ordinary least-squares regression, corrected for age, sex, intracranial volume, and whole amygdala volume. PTSD diagnosis was not significantly associated with amygdala nuclei volumes. PTSD severity scores were associated with smaller right lateral nucleus volume (β = -0.26, pBON = 0.01). Smaller right lateral nucleus volume was also associated with re-experiencing (β = -1.01, pBON = 0.04) and arousal (β = -0.9, pBON = 0.04), smaller left paralaminar nucleus volume was associated with re-experiencing (β = -0.1, pBON = 0.04), smaller left corticoamygdaloid transition area volume was associated with avoidance (β = -0.31, pBON = 0.02). Larger left and right central nucleus volumes were significantly associated with childhood physical abuse (β = 0.24, pBON = 9 × 10-3) and neglect (β = 0.29, pBON = 0.04), respectively. Differences in select amygdala nuclei volumes among adults are associated with PTSD severity, symptom cluster scores, and childhood physical abuse and neglect. These findings demonstrate nuclei-specific patterns consistent with their functional roles in fear learning and expression.

Transcranial magnetic stimulation (TMS) is a cornerstone tool for causal inference in human brain function and an increasingly used neuromodulation therapy, yet it induces well-recognized discomfort that may systematically bias measured outcomes. Despite its ubiquity, a critical gap remains in understanding how TMS-induced discomfort is represented across the brain and to what extent it contributes to TMS-evoked neural responses. Using concurrent TMS-fMRI across 11 cortical targets, we collected an unprecedented dataset (165 participants; 1,535 runs) spanning healthy participants and those with elevated affective symptoms. Cross-validated multivariate modeling revealed that TMS-induced discomfort engages distributed cortical and subcortical regions across sensorimotor, attentional, default mode, and limbic networks, with both shared and group-specific patterns. Discomfort-related activity accounted for approximately 12% and 25% of TMS-evoked responses in healthy and elevated-symptom groups, respectively, and varied systematically across stimulating sites. These findings identify TMS-induced discomfort as a substantial and previously under-characterized component of TMS-evoked neural responses, underscoring the need to explicitly measure and model it. By providing a whole-brain map of regional contributions associated with TMS-induced discomfort and an analytic framework to dissociate direct neuromodulatory effects from discomfort-related responses, this work improves the interpretability of TMS-evoked signals and supports more rigorous causal inference and therapeutic applications.

The thalamus is a heterogeneous structure crucial for corticocortical communication, affective-perceptual integration, motor preparation, and memory-related functions. Posttraumatic stress disorder (PTSD) is characterized by various symptoms that likely relate to thalamic functions. Group-level and individual differential structural covariance (SC) analyses were conducted on intrathalamic, thalamocortical, and thalamosubcortical volumetric networks by segmenting structural MRI data from 2,784 subjects (PTSD n = 1,306; controls n = 1,478) into 25 thalamic nuclei per hemisphere. We found that PTSD was associated with stronger intrathalamic and thalamocortical network strength and stronger SC between the limbic thalamus and the somatomotor and auditory thalamus. PTSD severity was related to specific regional alterations in the intrathalamic network involving the lateral pulvinar. Comorbid depression severity positively correlated with global intrathalamic alterations, while avoidance symptoms positively correlated with global thalamosubcortical alterations. Hyperarousal symptoms related to altered SC in the thalamocortical network between the reuniens, central medial, paratenial, centromedian, and limitans-suprageniculate nuclei and lateral cortical regions spanning the occipital, temporal, and orbitofrontal cortices. Differential associations between avoidance, hyperarousal, and comorbid depression symptoms and thalamic SC in PTSD suggest that specific thalamic covariance patterns may be involved in unique facets of PTSD symptomatology.

Psychiatric disorders carry a major public health burden, yet advances in treatment have been slow to emerge, partly owing to reliance on traditional symptom-based diagnostic frameworks. In this Perspective, we explore the emerging paradigm of precision psychiatry, which seeks to align therapeutic development with underlying neural biology dysfunctions using biomarkers. Drawing lessons from the success of precision oncology and neurology, precision psychiatry utilizes patient-specific biological measures of brain function - such as electroencephalography, objective behavioural assessments, functional magnetic resonance imaging and peripheral biomarkers - to understand drugs' effects on the brain, define indications and stratify patient populations for targeted intervention development. We discuss mechanistic approaches that focus on excitation-inhibition balance, reward and aversion circuits, hippocampal-prefrontal neuroplasticity, and processing of social cues, highlighting how these frameworks can elucidate drug mechanisms and predict treatment responses. Proof-of-concept examples, including predictors of response to standard-of-care treatments, and patient subgroup-driven successes in postpartum depression and schizophrenia, underscore the potential of stratified trials to reduce development risks and improve clinical outcomes. We address ongoing and future regulatory, commercial and clinical considerations for integrating scalable and reproducible biomarkers into drug development. Precision psychiatry thus represents a new strategy to refine clinical trial design and develop biology-defined treatments, which may help to overcome longstanding challenges in psychiatric drug discovery.

Hippocampal activity supports memory and many other brain functions. Transcranial magnetic stimulation (TMS) guided by hippocampal functional connectivity (FC) shows promise in improving memory, but direct neural evidence of its capacity to engage and modulate hippocampal activity is lacking. Here we combined TMS with intracranial electroencephalography (iEEG) in 8 neurosurgical patients and with functional magnetic resonance imaging (fMRI) in 79 neurologically healthy participants. We identified that (1) single-pulse TMS to individualized parietal cortex guided by hippocampal-FC preferentially evoked distinct temporal and spectral activity patterns in the hippocampus, (2) variability in TMS-evoked hippocampal responses related to individual differences in parietal-hippocampus FC strength, and (3) repetitive TMS to hippocampal-FC-guided parietal cortex selectively suppressed hippocampal theta oscillations. These findings provide multimodal causal neural evidence and important mechanistic insights supporting the development of personalized neuromodulation strategies aimed at improving hippocampus-dependent functions.

BACKGROUND:Patients with posttraumatic stress disorder (PTSD) exhibit smaller regional brain volumes in commonly reported regions including the amygdala and hippocampus, regions associated with fear and memory processing. In the current study, we have conducted a voxel-based morphometry (VBM) meta-analysis using whole-brain statistical maps with neuroimaging data from the ENIGMA-PGC PTSD working group. METHODS:T1-weighted structural neuroimaging scans from 36 cohorts (PTSD n = 1309; controls n = 2198) were processed using a standardized VBM pipeline (ENIGMA-VBM tool). We meta-analyzed the resulting statistical maps for voxel-wise differences in gray matter (GM) and white matter (WM) volumes between PTSD patients and controls, performed subgroup analyses considering the trauma exposure of the controls, and examined associations between regional brain volumes and clinical variables including PTSD (CAPS-4/5, PCL-5) and depression severity (BDI-II, PHQ-9). RESULTS:PTSD patients exhibited smaller GM volumes across the frontal and temporal lobes, and cerebellum, with the most significant effect in the left cerebellum (Hedges' g = 0.22, pcorrected = .001), and smaller cerebellar WM volume (peak Hedges' g = 0.14, pcorrected = .008). We observed similar regional differences when comparing patients to trauma-exposed controls, suggesting these structural abnormalities may be specific to PTSD. Regression analyses revealed PTSD severity was negatively associated with GM volumes within the cerebellum (p corrected  = .003), while depression severity was negatively associated with GM volumes within the cerebellum and superior frontal gyrus in patients (p corrected  = .001). CONCLUSIONS:PTSD patients exhibited widespread, regional differences in brain volumes where greater regional deficits appeared to reflect more severe symptoms. Our findings add to the growing literature implicating the cerebellum in PTSD psychopathology.

BACKGROUND:Previous investigations of whole thalamus and thalamic nuclei volumes in posttrauma psychopathology have been sparse and limited in scope and have yielded inconsistent results. To address this, volumetric estimates of whole thalamus and thalamic nuclei were obtained from structural brain magnetic resonance imaging scans from 2058 participants across 20 worldwide sites in the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Posttraumatic Stress Disorder (PTSD) working group. METHODS:Thalamic volumes were compared in trauma-exposed participants with PTSD (n = 238), major depressive disorder (MDD) (n = 184), and comorbid PTSD+MDD (n = 618) and in trauma-exposed control participants (n = 1018). PTSD and MDD symptom severity, PTSD symptom clusters, and childhood trauma were similarly examined for associations with thalamic volume. RESULTS:Participants with PTSD had smaller sensorimotor thalamic nuclei, while participants with MDD or comorbid PTSD+MDD had smaller mediodorsal (MD) thalamus volumes relative to control participants. Severity of PTSD and MDD symptoms negatively correlated with MD volume. A significant interaction between PTSD and MDD severity was found, such that MDD severity was positively associated with whole thalamus volume only among individuals with high PTSD severity. We observed both positive and negative volumetric associations for specific PTSD symptom clusters and childhood trauma subtypes. CONCLUSIONS:Whole thalamus volume and volumes of the sensorimotor and limbic thalamus may play an important role in the development of PTSD and MDD in the aftermath of trauma exposure. The interaction between PTSD and MDD symptoms and contrasting effects across PTSD symptom clusters and types of childhood adversity suggest that multiple neurobiological mechanisms are involved in shaping thalamic volume posttrauma.

Background:Posttraumatic stress disorder (PTSD) is a debilitating condition that disproportionately impacts females. Prior research indicates that males with PTSD exhibit hypoconnectivity of frontal brain regions measured with resting electroencephalography (EEG). In the current study, we examined functional connectivity among females with PTSD and trauma-exposed control females, as well as the impact of sex hormones. Methods:Participants included 61 females (mean age = 31.41 years, SD = 8.64) who endorsed criterion A trauma exposure. Resting-state EEG data were recorded for 5 minutes in the eyes-open position. Using a linear mixed-effects model, functional connectivity of the theta band (4-7 Hz) served as the response variable. Results:Compared with the control group, the PTSD group showed hyperconnectivity between visual brain regions and the rest of the cerebral cortex (false discovery rate-corrected p [p FDR] < .05). Additionally, participants with PTSD demonstrated enhanced connectivity between the default mode network and frontoparietal control network compared with control participants (p FDR < .05), as well as increased connectivity between the ventral attention network and the rest of the cerebral cortex (p FDR < .05). Estradiol was associated with higher connectivity, while progesterone was associated with lower connectivity, but these associations did not survive correction. Conclusions:The results are consistent with prior research indicating that PTSD is associated with altered connectivity in visual brain regions, which may reflect disrupted visual processing related to reexperiencing symptoms (e.g., intrusive memories). Our findings provide additional support for the relevance of the theta frequency range in PTSD given its role in fear learning and regulation processes.

Identifying robust neural signatures of posttraumatic stress disorder (PTSD) symptoms is important to facilitate precision psychiatry and help in understanding and treatment of the disorder. Emergent research suggests structural covariance of early visual regions is associated with later PTSD development. However, large-scale analyses are needed – in heterogeneous samples of trauma-exposed and trauma naive individuals – to determine if such a neural signature is a robust – and potentially a pretrauma – marker of vulnerability. We analyzed data from the ENIGMA-PTSD dataset (n = 2,814) and the Human Connectome Project – Young Adult (HCP-YA) dataset (n = 890) to investigate whether structural covariance of early visual cortex is associated with either PTSD symptoms or perceived stress. Structural covariance was derived from a multimodal pattern previously identified in recent trauma survivors, and participant loadings on the profile were included in linear mixed effects models to evaluate associations with stress. Early visual cortex covariance loadings were negatively associated with PTSD symptoms in the ENIGMA-PTSD dataset. The relationship persisted when accounting for prior childhood maltreatment; supporting PTSD symptom specificity, no relationship was observed with depressive symptoms and no association was observed between loadings and perceived stress measures in the HCP-YA dataset. Structural covariance of early visual cortex was robustly associated with PTSD symptoms across an international, heterogeneous sample of trauma survivors. Future studies should aim to identify specific mechanisms that underlie structural alterations in the visual cortex to better understand posttrauma psychopathology.

BACKGROUND:Identifying robust neural signatures of posttraumatic stress disorder (PTSD) symptoms is important to facilitate precision psychiatry and help in understanding and treatment of the disorder. Emergent research suggests that the structural covariance of early visual regions is associated with later PTSD development. However, large-scale analyses are needed in heterogeneous samples of trauma-exposed and trauma-naïve individuals to determine whether such a neural signature is a robust marker of vulnerability. METHODS:We analyzed data from the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis)-PTSD dataset (N = 2814) and the HCP-YA (Human Connectome Project-Young Adult) dataset (N = 890) to investigate whether the structural covariance of the early visual cortex is associated with either PTSD symptoms or perceived stress. Structural covariance was derived from a multimodal pattern previously identified in recent trauma survivors, and participant loadings on the profile were included in linear mixed effects models to evaluate associations with stress. RESULTS:Early visual cortex covariance loadings were negatively associated with PTSD symptoms in the ENIGMA-PTSD dataset. The relationship persisted when accounting for prior childhood maltreatment; supporting PTSD symptom specificity, no relationship was observed with depressive symptoms, and no association was observed between loadings and perceived stress measures in the HCP-YA dataset. CONCLUSIONS:The structural covariance of early visual cortex was robustly associated with PTSD symptoms across an international, heterogeneous sample of trauma survivors. Future studies should aim to identify specific mechanisms that underlie structural alterations in the visual cortex to better understand posttrauma psychopathology.

BACKGROUND: Posttraumatic stress disorder (PTSD) is accompanied by disrupted cortical neuroanatomy. We investigated alteration in covariance of structural networks associated with PTSD in regions that demonstrate the case-control differences in cortical thickness (CT) and surface area (SA). METHODS: Neuroimaging and clinical data were aggregated from 29 research sites in >1300 PTSD cases and >2000 trauma-exposed control subjects (ages 6.2-85.2 years) by the ENIGMA-PGC (Enhancing Neuro Imaging Genetics through Meta Analysis-Psychiatric Genomics Consortium) PTSD working group. Cortical regions in the network were rank ordered by the effect size of PTSD-related cortical differences in CT and SA. The top-n (n = 2-148) regions with the largest effect size for PTSD > non-PTSD formed hypertrophic networks, the largest effect size for PTSD < non-PTSD formed atrophic networks, and the smallest effect size of between-group differences formed stable networks. The mean structural covariance (SC) of a given n-region network was the average of all positive pairwise correlations and was compared with the mean SC of 5000 randomly generated n-region networks. RESULTS: Patients with PTSD, relative to non-PTSD control subjects, exhibited lower mean SC in CT-based and SA-based atrophic networks. Comorbid depression, sex, and age modulated covariance differences of PTSD-related structural networks. CONCLUSIONS: Covariance of structural networks based on CT and cortical SA are affected by PTSD and further modulated by comorbid depression, sex, and age. The SC networks that are perturbed in PTSD comport with converging evidence from resting-state functional connectivity networks and networks affected by inflammatory processes and stress hormones in PTSD.

Major depressive disorder (MDD) is a prevalent condition that profoundly impairs quality of life across diverse populations. Despite widespread use, current antidepressant and psychotherapeutic treatments exhibit limited efficacy and unsatisfactory response rates. Progress in developing effective therapies is hampered by the insufficiently understood heterogeneity of MDD and its elusive underlying mechanisms. Here, to address these challenges, we develop a novel machine learning framework that identifies structure–function covariation through target-oriented fusion of structural and functional connectivity, which robustly predicts individual-level antidepressant response (sertraline, R2 = 0.31; placebo, R2 = 0.22). Validation in an independent escitalopram-medicated MDD cohort confirms the biomarker’s generalizability (P = 0.01) and suggests an overlap of psychopharmacological signatures across selective serotonin reuptake inhibitors. Our models highlight the right precuneus as a common key region for both sertraline and placebo responses, with the right middle frontal gyrus and left fusiform gyrus specific to sertraline and the left inferior and middle frontal gyri to placebo. We also find that structural connectivity is more predictive of sertraline response, while functional connectivity better predicts placebo response. The framework further decomposes the overall predictive patterns into three constitutive network constellations (default-mode regulatory, affective and sensory processing), which exhibit distinct generalizable structure–function covariation and treatment-specific association with personality traits and behavioral/cognitive profiles. These findings provide unique insights to the structure–function covariation in patients with MDD, its association to the heterogeneity in antidepressant response and the dissection of the intricate MDD neuropsychopharmacology, paving the way for precision medicine and development of more targeted antidepressant therapeutics. Clinicaltrials.gov registration: Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression (EMBARC), NCT01407094. Using a machine learning framework to predict antidepressant response in major depressive disorder by analyzing structural and functional connectivity, this study reveals distinct predictive patterns and highlights specific brain regions associated with treatment efficacy, advancing personalized therapeutic approaches.

Background:Cortical gyrification involves the formation of folds in the cerebral cortex, coinciding with key neurodevelopmental processes. Its strong correlation with increased cortical surface area and decreased cortical thickness may improve cortical signaling efficiency by decreasing cortico-cortical distance. Differences in brain structure have been found in posttraumatic stress disorder (PTSD), yet few small studies have examined cortical gyrification. Methods:Gyrification was quantified using FreeSurfer's Local Gyrification Index (lGI), derived from 3-dimensional T1-weighted volumetric brain magnetic resonance imaging in 1876 participants (PTSD n = 789, control n = 1087) across 24 sites from the ENIGMA-PGC (Enhancing Neuro Imaging Genetics through Meta-Analysis and Psychiatric Genomics Consortium) PTSD working group. Using a region of interest-based approach, we fitted a linear mixed-effects model with age (mean = 35.6, SD = 9.23, range = 8-95), sex (female = 967 [52%], male = 909 [48%]), pial surface area, PTSD, and random site effects to test associations between PTSD diagnosis/severity and regional lGI. We examined moderating effects of depression, childhood trauma, age, and sex. Results:PTSD diagnosis and severity were both associated with lower lGI for the right medial orbitofrontal and right rostral anterior cingulate cortices. The interaction of PTSD and age was associated with lower lGI for the rostral middle frontal cortex bilaterally. Contrasting comorbid PTSD and major depressive disorder with the PTSD-only group showed that comorbidity was associated with lower lGI in the left inferior and medial temporal cortices. Conclusions:Lower lGI, which is associated with impaired signaling efficiency, was observed in the PTSD group compared with the control group for the ventromedial prefrontal cortex, a region that has been strongly implicated in associative fear learning and extinction. It is possible that PTSD accelerates the typical age-associated decline in lGI of the rostral middle frontal cortices.