Psychiatry Research: Neuroimaging

Intermittent explosive disorder (IED) is associated with impulsive aggression in ambiguous social contexts. Prior neuroimaging studies have treated IED as a homogenous group, but identical social situations may elicit divergent responses across IED individuals. Here, we test the hypothesis that IED is characterized by idiosyncratic neural responses to social cues during naturalistic social-emotional processing. IED individuals and healthy controls completed a validated paradigm where they were presented with video vignettes of interpersonal interactions while undergoing fMRI. We computed the intersubject correlation (ISC) in neural time courses between pairs of participants to quantify neural similarity, and assessed whether similarity differed between Healthy-Healthy and IED-IED dyads using Bayesian multilevel models, controlling for self-reported emotional responses and intention attributions for each vignette. Healthy-Healthy dyads showed significantly higher ISC than IED-IED dyads, indicating that neural responses to the videos were similar among healthy participants, but idiosyncratic in IED individuals. These effects were observed in regions in the default mode and salience networks, including the precuneus, medial prefrontal cortex, superior temporal sulcus, insula, and dorsal anterior cingulate cortex. Individuals with IED exhibited idiosyncratic neural responses during naturalistic social-emotional processing, even after accounting for differences in emotional reaction and intention attribution. This neural idiosyncrasy may reflect atypical integration of social cues, giving rise to maladaptive interpretations and impulsive aggression. Assessing neural synchrony during ecologically valid paradigms offers a promising tool for identifying neural markers of interpersonal dysfunction and informing targeted interventions.

BackgroundChallenges in correctly identifying bipolar II disorder (BD-II) during depressive states have led to poor clinical outcomes. BD-II-specific imaging investigations are lacking. This study addresses current knowledge gaps by comparing white matter (WM) integrity in BD-II and unipolar depression (UD) using fixel-based analysis. MethodFibre density (FD), fibre cross-section (FC), and the combined measure (FDC) within 72 WM tracts were compared among 33 individuals with BD-II, 50 with UD, and 51 healthy controls (HC). The effects of illness characteristics on FBA correlates were also examined. Sensitivity analyses compared these measures among unmedicated participants to check whether medication status affects the results. ResultsParticipants with BD-II and UD showed reduced FD in the left parieto-occipito-pontine (POPT) and striato-occipital (ST-OCC) tracts. Compared to UD, BD-II was associated with lower FD in the left arcuate fascicle (AF) and bilateral superior longitudinal fasciculi I and II (SLF-I and II). In BD-II, illness duration negatively correlated with FD in left AF, left POPT, and right ST-OCC, while the number of lifetime BD-II depressive episodes positively correlated with FDC in left SLF-I. Group differences were significant but less pronounced in unmedicated participants. ConclusionsOur findings demonstrate shared and distinct WM abnormalities in tracts involved in visuomotor and executive processes in BD-II and UD, with BD-II exhibiting more extensive alterations. With BD-II, but not UD, longer illness duration was linked to lower FD, while depression recurrence was associated with higher FDC, suggesting potential degenerative and compensatory neurobiological mechanisms. Longitudinal studies should investigate the joint trajectories of symptomatology and WM alterations.

Self-referential processing is a fundamental cognitive function, and abnormalities in its neural implementation have been reported across a range of psychiatric disorders, leading to the proposal that such alterations may constitute a transdiagnostic neurobiological feature. Yet claiming transdiagnostic requires rigorous evidence. Here, we examined the evidence for such a hypothesis by conducting a systematic review and coordinate-based meta-analysis of psychiatric neuroimaging studies that employed self-referential tasks. The systematic review identified 36 neuroimaging studies across 9 broad categories of psychiatric disorders, suggesting that the neural aberrancy of self-referential processing is indeed of great interest across different diagnosis. Of these, 27 studies were eligible for the ALE meta-analysis. The ALE results revealed hypoactivation of the right precuneus in psychiatric groups relative to health controls, alongside hyperactivation of the right triangular part of the inferior frontal gyrus (IFGtri) during self-referential processing in psychiatric groups. Notably the precuneus and IFGtri are core nodes of the default mode network and the frontal-parietal control network, respectively, suggesting that aberrant self-referential processing across psychiatric disorders may be characterized by disrupted default mode network engagement accompanied by compensatory or maladaptive recruitment of control-related frontal regions. Together, our findings revealed a strong research interest in neural aberrancy of self-referential processing as a transdiagnostic feature. However, available evidence only provided preliminary evidence for such statement. To move forward, the field needs coordinated efforts to systematically accumulate data and collecting new datasets.

Cognitive deficits are a core feature of schizophrenia, yet their neural mechanisms remain poorly understood. Network switching, a measure of how frequently brain networks change their interactions over time, has been linked to cognitive performance in healthy individuals and has been reported to be altered in schizophrenia. Recent evidence further suggests that the relationship between network switching and cognition depends on arousal, which is itself disrupted in schizophrenia. However, whether arousal-related alterations in network switching contribute to cognitive impairment in schizophrenia remains unclear. Here, we used concurrent resting-state functional MRI (fMRI) and pulse oximetry data from 39 healthy controls (HC), 27 psychiatric controls (PC), and 39 individuals with schizophrenia spectrum disorders (SSD) to examine whether network switching relates to indices of autonomic arousal. Additionally, in HC and SSD participants, we tested whether arousal moderated the association between network switching and performance on an attention task. We observed no group differences in autonomic arousal. However, PC exhibited higher dorsal default mode and anterior salience network switching rates compared to SSD participants. Additionally, autonomic arousal significantly moderated the relationship between network switching and cognitive performance in HC, an effect that was absent in SSD. Notably, these findings implicate network switching as a potential neural biomarker that differentiates PC from SSD. They also suggest that disrupted coupling between arousal state and network switching, rather than switching alone, may underlie cognitive dysfunction in SSD.

Major depressive disorder (MDD) is a highly prevalent neuropsychiatric disorder characterized by depressed mood, feelings of sadness, loss of interest, and reduced pleasure related to daily activities. The clinical etiology of depression has been extensively studied, with research indicating biological, social, and psychological factors related to onset of depressive symptoms. Despite increased knowledge related to MDD, there is no tangible biomarker developed for MDD. Neuroimaging modalities such as single photon emission computed tomography (SPECT) have been utilized to characterize regional cerebral perfusion (rCBF). Functional dysconnectivity in depressed patients have been examined, with depressed individuals showing elevated depression scores and decreased rCBF in cognition and executive functioning networks. While SPECT can be utilized to monitor rCBF changes with respect to symptom severity, it alone cannot be utilized to develop a potent biomarker. Advanced multivariate methods such as independent component analysis (ICA) have been used to visualize disconnected functional patterns across disorders including depression and schizophrenia. Given no current SPECT studies examine transdiagnostic clinical profiles, the current study aims to bridge this gap. We utilized the 68 NeuroMark SPECT template across six patient groups. Factor scores investigating three key symptoms of depression: worry/rumination, moodiness, and social disinterest, and measured the loading parameter strength (i.e. component expression for each NeuroMark domain/subdomain) across the 68 components were examined. We identified significant relationships between symptoms and frontal, triple network, sensorimotor, and visual components across the three symptom profiles. Future studies should examine these trends across larger sample sizes, and increased clinical samples.

Excessive self-blaming emotions are commonly observed in anxiety disorders, with qualitatively similar symptomatology reported in subclinical populations. Interpretation of moral information requires assessing the social conceptual information, a process overseen by the superior anterior temporal lobe (sATL). Feelings of self-blame evoke interactions of sATL and socio-affective regions, and previous research shows that subclinical anxiety modulates the organisation of the self-blame circuitry. This study aimed to extend these findings by exploring links of trait-anxiety with (i) self-blaming emotions and associated behaviours in an experimental task, and (ii) self-blame-dependent neural activity and connectivity, as observed during reliving of autobiographical guilt memories. We also explored the role of resting-state fMRI in linking these phenomena. Increased anxiety was linked to stronger self-blaming emotions, and more pronounced self-attacking and hiding. When experiencing negative emotions about themselves (i.e. shame and self-anger), anxious individuals were also less likely to disengage from self-focused thoughts. These behavioural findings were paralleled by enhanced self-blame-related connectivity between the left sATL and bilateral posterior subgenual cingulate cortex. Distinct patterns of activity and connectivity within the ATL-related circuitry were furthermore linked to individual differences in intensity of the self-blaming emotions and approach-avoidance motivation towards the guilt memories. As such, the results of the current study link stronger self-blaming emotions in anxious individuals with specific maladaptive patterns of behaviour. Furthermore, the work provides robust evidence for the important role of ATL-related circuitry in self-blame processing, supporting its broader involvement in social conceptual processing and its alterations in subclinical anxiety.

The identification of objective, dimensional indices of mental health is of central importance in the pursuit of transdiagnostic multi-dimensional frameworks of psychopathology. Altered visual processing occupies a specific domain of interest and motivated the present investigation aimed to quantify the visuocortical impact of affective naturalistic distractor cues on limited capacity attentional resources in obsessive-compulsive disorder (OCD). The current investigation examined the extent to which attentional resources are allocated toward task cues under affective and disorder-relevant distraction in participants with OCD (N = 33) and control participants (N = 31). Steady-state visual evoked potentials (ssVEPs) in response to task-relevant cues were examined using a foreground task where participants detected coherent motion in a flickering random dot kinematogram (RDK) overlaid on naturalistic distractor pictures ranging in emotional content (pleasant, neutral, unpleasant, and OCD-evoking pictures). Amplitude envelopes of ssVEPs in response to the motion stimulus served as an index of visuocortical engagement with task-relevant cues. Data were also fitted to the distraction under competition model (DUC), a computational framework of attention selection. Group differences emerged with stronger visuocortical competition effects (attenuated task engagement) for the OCD group, driven largely by the unpleasant pictures, followed by the OCD-evoking pictures. Furthermore, the DUC model fit well in both groups, demonstrated the dominance of the visuocortical competition observed in response to the unpleasant pictures, and revealed the presence of substantial competition in response to the OCD-evoking pictures in the OCD group.

BackgroundLarge-scale T1-weighted MRI studies have established grey-matter abnormalities in bipolar disorder (BD), with our group contributing to consensus findings. However, structural connectivity, particularly within emotion- and reward-related circuits, remains poorly understood. Diffusion-weighted MRI (dMRI) enables investigation of white-matter pathways, yet prior work is constrained by small samples, methodological heterogeneity, and unclear medication effects. We conducted the largest dMRI network analysis in BD, relating symptom burden and polypharmacy to tractography-derived connectivity and graph-theoretic metrics. MethodsCross-sectional structural and diffusion MRI scans from 449 individuals with BD (35.7{+/-}12.6 years) and 510 controls (33.3{+/-}12.6 years), aged 18-65, were analyzed across 16 ENIGMA-BD sites. Standardized segmentation/parcellation and constrained spherical deconvolution tractography generated individual structural connectivity matrices. Graph-theoretic metrics of global and subnetwork organization were related to symptom severity and medications. ResultsBD showed widespread network alterations (lower density and efficiency, longer path length, and higher betweenness centrality), altered microstructural organization in a limbic-basal ganglia circuit, and abnormal streamline counts in a default-mode/salience/fronto-limbic-basal ganglia network. Longer illness duration, later onset, and psychosis history were associated with greater abnormalities in network architecture, whereas more manic episodes were associated with greater fronto-limbic connectivity. Antidepressant (particularly SSRI), anticonvulsant, and antipsychotic use related to poorer global and fronto-limbic connectivity; no clear lithium effects emerged. ConclusionsAs the largest structural connectivity study in BD, we reveal widespread disruption in reward and emotion-regulation networks influenced by illness severity and medication use. Results show that multisite harmonization is feasible and highlight ENIGMA-BD as a scalable framework for identifying reproducible neurobiological markers.

Mild Behavioural Impairment (MBI) is defined by later-life onset of persistent behavioural changes and is recognized as a risk marker for cognitive decline and dementia. Apathy, a core MBI domain characterized by diminished interest, initiative, and emotional reactivity, can emerge before dementia and is hypothesized to be associated with structural brain changes. While previous studies have explored Alzheimer disease (AD)-related neuroanatomical substrates of apathy in the dementia clinical stage, few have investigated these associations in cognitively normal (CN) or mild cognitive impairment (MCI) individuals with persistent apathy consistent with MBI. Thus, this study explores structural brain differences between individuals with MBI-apathy and those without neuropsychiatric symptoms (no-NPS). Participants (n = 446; mean age = 69.6 years; 79.8% CN; 62.8% female) were drawn from the National Alzheimers Coordinating Center and categorized into MBI-apathy (n = 59) and no-NPS (n = 387) groups. Linear regressions were used to model associations between NPS group and regional brain measures, with adjustments for age, sex, years of education, apolipoprotein E4 carrier status, intracranial volume, and Mini-Mental State Examination score, with false discovery rate (FDR) correction for multiple comparisons. Primary outcomes included two predefined AD meta-regions-of-interest (ROIs): 1) thickness: a composite measure of mean cortical thickness across the entorhinal cortex, inferior temporal gyrus, middle temporal gyrus, inferior parietal lobule, fusiform gyrus, and precuneus; and 2) volume: a composite measure of mean cortical and subcortical grey matter volume across the hippocampus, entorhinal cortex, amygdala, middle temporal gyrus, inferior parietal lobule, and precuneus. Primary outcomes also included cortical thickness and grey matter volume among individual ROIs including the ventral striatum (VS), anterior cingulate cortex (ACC), orbitofrontal cortex (OFC), ventrolateral prefrontal cortex (vlPFC), and dorsolateral prefrontal cortex (dlPFC). MBI-apathy status was associated with significantly lower AD-meta-ROI cortical thickness (Z-score difference [95% CI]; FDR-corrected p-value, -0.43 [-0.73 - [-0.12]]; 0.025) and lower AD meta-ROI grey matter volume (-0.50 [-0.71 - [-0.30]]; <0.001). MBI-apathy was also associated with significantly lower dlPFC thickness (-0.40, [-0.70 - [-0.09]]; 0.02) and volume (-0.28 [-0.50- [-0.06]]; 0.026) and lower OFC volume (-0.32, [-0.57 - [-0.07]]; 0.026) compared to the no-NPS group. Within a non-dementia sample, MBI-apathy was more strongly associated with established AD-vulnerable regions than with regions that have been traditionally implicated in apathy in dementia. Results suggests that during CN and MCI stages, MBI-apathy may reflect early AD-related neurodegeneration, with conventional apathy-related structural changes becoming more prominent as disease progresses.

IntroductionWe present here a methodology for morphometric analysis of the substantia nigra (SN), the ventral tegmental area (VTA), the dorsal raphe nucleus (DRN) and their respective structural brain circuits. MethodsOur analyses were based on multimodal T1-weighted MRI and diffusion MRI (dMRI) segmentation and tractography in 12 human subjects drawn from the Human Connectome Project (HCP) repository. ResultsWe were able to demonstrate strong connections of the SN, VTA and DRN with several brain regions, in particular the dorsolateral prefrontal cortex (DLPFC) and the cerebellum. More specifically, we created comprehensive visualizations of the SN and VTA dopaminergic as well as the DRN serotonergic structural circuits in the human brain, which, although preliminary, demonstrate the potential of multimodal neuroimaging to investigate these circuits quantitatively in clinical conditions. Finally, we created a pilot dataset for the most frequently observed structural connections, specifically those that were present more than 92% of the time among all subjects. Discussion This pilot morphometric report examines the structural circuits of the SN, VTA and DRN, which are critically involved in several biobehaviors and clinical conditions such as addiction, stress, Parkinsons disease (PD), schizophrenia, obsessive-compulsive disorder, post-traumatic stress disorder, attention deficit hyperactivity disorder, mood disorders, COVID-19 and long COVID. Importantly, the strong structural connectivity of the DLPFC and cerebellum with the SN, VTA and DRN is expected to be a potential target of noninvasive neuromodulation treatments in neuropsychiatry. Our findings demonstrate the potential of current clinical multimodal neuroimaging to delineate the dopaminergic (DA) and serotonergic (5-HT) circuits in the human brain in clinical conditions.

BackgroundImpaired glymphatic clearance, the perivascular system supporting cerebrospinal and interstitial fluid exchange, has been implicated in neurodegenerative and psychiatric disorders. Diffusion tensor imaging along the perivascular space (DTI-ALPS) provides a non-invasive proxy for glymphatic-related processes, yet its role in psychiatric conditions remains uncertain. MethodsFollowing PRISMA guidelines, we systematically searched PubMed, PsycNET, and Embase for articles published up to September 25th, 2025. The protocol was pre-registered in PROSPERO (CRD420251155430). Studies reporting diffusion-based indices of glymphatic function in psychiatric populations were included. Standardised mean differences (Hedges g) were calculated for patient-control comparisons and pooled using random-effects models. Heterogeneity, methodological moderators, and risk of bias were assessed. ResultsThirty-two studies met inclusion criteria for the systematic review, covering major psychiatric groups including mood disorders, autism spectrum disorder, ADHD, psychosis, sleep disorders, and substance-related conditions. Twenty-four studies (n = 2,855; 1,503 patients, 1,352 controls) reporting bilateral DTI-ALPS measures were included in the meta-analysis. The pooled random-effects model revealed a significant transdiagnostic reduction in DTI-ALPS index in psychiatric populations compared with healthy controls (Hedges g = -0.78, 95% CI -1.01 to -0.55, p < 0.0001). Between-study heterogeneity was substantial (I{superscript 2} = 86.3%), and there was evidence of small-study effects. ConclusionsBilateral DTI-ALPS index showed a robust but heterogeneous reduction across psychiatric disorders. Together, these results suggest that impairments of perivascular diffusion, as indexed by DTI-ALPS, may reflect a shared transdiagnostic vulnerability across psychiatric conditions. Harmonised imaging pipelines and multimodal validation are needed to clarify the biological and clinical significance of these findings. SIGNIFICANCE STATEMENTThe search for reliable transdiagnostic biomarkers remains a central challenge in contemporary psychiatry, where heterogeneous symptom profiles often obscure shared biological pathways. The glymphatic system, a glia-dependent network regulating cerebrospinal and interstitial fluid exchange, has recently been proposed as a key mechanism linking vascular, immune, and metabolic pathways to mental illness. Diffusion tensor imaging along the perivascular space (DTI-ALPS) offers a non-invasive proxy for glymphatic function, yet its specificity and clinical relevance remain debated. This systematic review and meta-analysis provide, to our knowledge, the first quantitative synthesis of DTI-ALPS findings across psychiatric disorders, critically evaluating methodological assumptions and evidence for shared pathophysiological mechanisms. By clarifying the strengths and limitations of diffusion-based glymphatic imaging, this work establishes a mechanistic framework for future translational, interventional, and biomarker research in psychiatry.

BackgroundCircadian rhythm disturbances represent a core feature of bipolar disorder (BD), with evening chronotype as a marker for poorer outcomes. We hypothesized that BD psychopathology combined with evening chronotype is associated with structural alerations in circadian-related hypothalamic regions - particularly the suprachiasmatic nucleus (SCN) - specific to BD relative to other psychiatric diagnoses. MethodsWe investigated structural neuroimaging data from the UK Biobank (113 BD, 205 major depressive disorder, 91 psychotic disorders, 199 healthy controls). The SCN-containing anterior-inferior hypothalamic subunit was segmented, central to circadian functional neuroanatomy. For each group, diagnosis x chronotype interactions on its volume were tested using analysis of variance, with post-hoc estimated marginal means and correction for multiple comparisons. Covariates included age, sex, handedness, and lithium use. Specificity was examined across four additional hypothalamic subunits. ResultsThere was a diagnosis x chronotype interaction in the SCN-containing anterior-inferior hypothalamic subunit volume (F(6, 590) = 2.87, p =.009). This was driven by larger volumes in BD individuals with evening versus morning chronotype (t = 3.24, pFWER =.004). No comparable results were found in other hypothalamic regions or diagnoses. ConclusionsHypothalamic structure differs by chronotype in BD, with chronotype related associations localized to an anterior-inferior hypothalamic region implicated in circadian regulation. These findings support chronotype as a biologically meaningful dimension of variation in BD and provide neuroanatomical evidence linking circadian preference to circadian relevant brain structure. Longitudinal and interventional studies will be important to clarify the temporal dynamics, underlying mechanisms, and potential clinical significance of these associations.

IntroductionLactate plays dual roles in neuronal energy metabolism and signalling. The dorsal anterior cingulate cortex (dACC), a region with high baseline glycolytic activity implicated in psychiatric disorders, may exhibit dynamic lactate responses to graded cognitive-emotional demands. Because mitochondrial function declines with age, aging may model whether fMRS-derived lactate dynamics can detect latent neurometabolic vulnerabilities. MethodsUsing fMRS, we monitored dACC metabolite changes in 34 healthy participants (aged 21-69) during an emotional face-processing task with escalating cognitive-emotional workload. The paradigm comprised a 2-minute baseline, 10-minute task of increasing intensity, and 10-minute recovery. ResultsdACC lactate increased significantly, tracking task intensity and peaking 19.5% above baseline at maximum cognitive load (z = 2.66, p = 0.004). The response showed both linear task-related increases (z = 2.08, p = 0.02) and a quadratic inverted-U profile (z = 2.72, p = 0.004). Total creatine, total NAA and Glx (Glutamate+Glutamine) exhibited no task-dependent changes. Age influenced task-period lactate AUC (z = 2.19, p = 0.014). Participants over 40 exhibited greater peak responses (54% vs 28%), steeper upslopes (14% vs 7% per block), and larger AUC (155% vs 16%) than those under 40. Sex differences were also observed. Baseline lactate did not correlate with age. ConclusionsdACC lactate dynamics are sensitive to cognitive-emotional demand, with evidence of age-and sex-dependent modulation. The dissociation between static and dynamic measures establishes a metabolic stress-testing paradigm for detecting latent neuroenergetic vulnerabilities, supporting fMRS utility for probing mitochondrial function in health and psychiatric disorders.

An inflammatory subtype of major depressive disorder (MDD) is associated with treatment resistance pointing to an unmet need for adjunctive treatments. To evaluate treatment-related changes in brain inflammation, diffusion basis spectrum imaging (DBSI) is a promising non-radiation-based technique for longitudinal designs which has been verified with histopathology. However, its use as an endpoint in clinical trials is dependent on its individual-level reliability to robustly track changes. Here, we evaluated two DBSI runs acquired in 94 participants (including 43 participants with MDD) on the same day about 1.5 h apart to assess short-term test-retest reliability. Fiber fraction (reflecting axonal/dendrite density) and hindered fraction (reflecting edema) showed moderate to high test-retest reliability in both gray and white matter regions, whereas restricted fraction (reflecting cellularity) showed lower values in gray and white matter. Group-level reliability was similar in participants with MDD, except for lower reliability of hindered fraction in gray matter. Re-identification rates of individual brain maps were higher using voxel-level white matter signatures compared to gray matter regions of interest (ROIs) (p<.001). Crucially, participants with MDD showed reduced fiber fraction (tmax=4.68, k=38) and elevated hindered fraction (tmax=4.74, k=32) in the cingulate bundle, consistent with increased white matter inflammation, while gray matter ROI-based classification failed to identify cases. We conclude that DBSI is a promising technique to track inflammatory signatures in MDD, particularly in white matter tracts. Since several frontal and subcortical gray matter ROIs showed insufficient reliability, their assessment would require multiple DBSI runs to provide robust estimates.

Background: The highly influential predictive processing theory of psychosis posits that symptoms arise from imbalances in the weighting of predictions (priors) and sensory evidence. Despite this theory's increasing prominence, studies often present conflicting results. This is particularly problematic as findings from single tasks with modest sample sizes are frequently used to advance a theory for a generalised altered reliance on priors in psychosis. Methods: This study presents a random-effects, multi-level meta-analysis (PROSPERO CRD42024574379) evaluating evidence for aberrant reliance on priors in psychosis across perceptual tasks. The search identified articles in Embase, MEDLINE, APA PsycINFO, and APA PsycArticles published between 1st January 2005 and 31st October 2024, with risk of bias assessed using the Newcastle-Ottawa Scale. Included articles (34 results from 27 studies) compared adults with schizophrenia-spectrum psychosis (SZ; n = 904) to healthy controls (n = 1,039) on behavioural measures representing reliance on priors. Results: Results provided no evidence for atypical reliance on priors in psychosis (g = .03, 95% CI [-0.27, 0.34]; p = .818) or associations with delusions (6 results; SZ = 183; r = -.16, 95% CI [-0.51, 0.19]; p = .293) or hallucinations (10 results; SZ = 370; r = .04, 95% CI [-0.28, 0.36]; p = .780). In contrast with the theory that psychosis may differentially affect priors at different levels of the cognitive hierarchy, a sub-group analysis indicated that a two-level hierarchical model of priors did not account for conflicting results (F(1,32) = 0.1, p = .758). Conclusion: These findings do not suggest that psychosis is associated with a generalised predictive processing deficit spanning multiple aspects of perception. Key words: psychosis, schizophrenia, predictive processing, prior expectations, perception

ObjectiveCognitive behavioral therapy (CBT) is an effective first-line treatment for obsessive-compulsive disorder (OCD), yet it remains difficult to predict who will respond to this intervention. This study investigates associations between neural activity during inhibitory control tasks and CBT outcomes, and whether task-based fMRI data could serve as a predictive marker of individual CBT response. MethodsUsing fMRI data from individuals performing an inhibitory control task across five samples (n=130, age range=8-57, 54% female) of the ENIGMA-OCD consortium, univariate associations were analyzed between activity during response inhibition and error processing and three CBT outcomes: response, remission, and pre-post treatment change in symptom severity. Random forest and support vector machine models using leave-one-sample-out cross-validation were used for prediction of CBT response and remission from fMRI activity and clinical data. ResultsRemission after CBT was associated with weaker activity in default mode regions during response inhibition and in the right supramarginal gyrus during error processing. Greater symptom reduction was linked to weaker pre-treatment activity across frontoparietal, dorsal attention, visual, and subcortical regions during response inhibition, but to stronger default mode activity during error processing. Despite these robust group-level effects, machine learning models failed to predict individual outcomes above chance level with either neuroimaging or clinical data. ConclusionWeaker activity during response inhibition in a widespread network, as well as stronger activity in default mode regions during error processing before treatment, appear beneficial to CBT response. However, these findings cannot yet be translated into individually predictive markers of CBT outcome.

Individuals at clinical high risk for psychosis (CHR) are cognitively and neurobiologically heterogeneous, which encourages the use of a clustering approach to parse this heterogeneity. Multimodal approaches are assumed to be superior to unimodal approaches in identifying subgroups. With the success of the use of cognition and electrophysiological measures collectively in established psychotic disorders, and the lack of such an approach in CHR, we were motivated to address this gap. Using the North American Psychosis-Risk Longitudinal Study (NAPLS) 2 consortia (CHR (N=764)), we applied unsupervised cluster analysis on the combined cognitive and electrophysiology measures to identify CHR subgroups and assess their relationship with clinical and functional outcomes. A two-cluster solution with modest separability was found, which prompted the use of an alternative probabilistic, rather than discrete, clustering approach. Individuals who were more likely to be in Cluster 1 exhibited poorer cognitive performance, larger N100, mismatch negativity, and P300 amplitudes, and worse functioning, as well as a younger age of onset. These findings were largely replicated in NAPLS 3 (CHR (N=628)). Taken together, the results of our previous study of cognition-only clustering and the current study of combining cognition and electrophysiology indicate that multimodal clustering, if not developmentally informed, may obscure meaningful subtyping.

Background: Bipolar disorder (BD) is increasingly conceptualized as a heterogeneous condition with a neurodevelopmental phenotype (NDP) identifying a subgroup with early neurodevelopmental vulnerability and poorer clinical outcomes. Sensory processing (SP) abnormalities are a core feature of neurodevelopmental disorders but remain poorly characterized in BD and may reflect underlying neurodevelopmental liability. We examined whether NDP load is associated with specific SP alterations in euthymic BD patients and whether NDP-based stratification explains SP variability better than conventional BD subtype (BD 1/2). Methods: We assessed 102 euthymic BD patients and 45 healthy controls (HC) using the Adolescent/Adult Sensory Profile (AASP). NDP load (0-3) was computed from nine clinical variables grouped into neonatal, comorbidity, and neurodevelopmental clusters; a median split defined BD without NDP (BD) and BD with NDP (BD-ND). Associations between NDP load and AASP quadrants were analyzed using Spearman correlations with FDR correction. Group differences (BD, BD-ND, HC) were assessed using Welch ANOVA and post-hoc tests. Nested and multivariable linear regressions examined whether NDP classification explained SP variance beyond BD subtype, adjusting for age, sex, anxiety, and residual mood symptoms. Results: Higher NDP load correlated with greater low registration (rho=0.35, p<0.001, q=0.004), sensory sensitivity (rho=0.30, p=0.001, q=0.004), and sensation avoiding (rho=0.23, p=0.014, q=0.040), but not sensation seeking. BD-ND showed higher low registration, sensory sensitivity, and sensation avoiding than BD and HC (all qs<0.01). NDP classification explained more SP variance than BD subtype; with robust associations after adjustment. Conclusions: Sensory processing alterations in BD are dimensionally associated with neurodevelopmental load and more accurately captured by NDP-based stratification than diagnostic subtype. SP alterations may represent a transdiagnostic marker of neurodevelopmental liability within BD, supporting biologically informed stratification approaches.

Recent evidence suggests that psychosis involves glutamatergic dysfunction and altered activity/connectivity within corticolimbic circuitry. While altered relationships between corticolimbic glutamatergic metabolite levels and resting-state functional connectivity (FC) have been described in schizophrenia and first-episode psychosis (FEP), whether these disruptions are also present prior to psychosis onset remains unclear. We measured Glx (glutamate + glutamine) levels in the anterior cingulate cortex (ACC) and hippocampus with magnetic resonance spectroscopy (MRS), and resting-state FC between corticolimbic regions of interest (ACC, hippocampus, amygdala and nucleus accumbens (NAc)) in antipsychotic-naive participants at clinical high-risk for psychosis (CHR-P, n=22), compared to healthy controls (HC, n=23) and FEP participants (n=10). Primary analyses compared corticolimbic Glx-FC interactions between CHR-P and HC groups. FEP individuals were included in secondary Glx comparisons but were excluded from FC analyses due to insufficient sample size after quality control. There was a significant interaction between group and ACC Glx for FC between the NAc and the bilateral amygdala and hippocampus (p-FDR=0.021), which was driven by a significant negative association in the CHR-P group (p-FDR=0.005). Complementary seed-to-whole-brain analyses revealed additional negative associations between ACC Glx and FC with the left middle temporal gyrus, and between hippocampal Glx and FC with the parahippocampal and temporal fusiform cortices in CHR-P individuals, which were absent in HC. FEP showed higher Glx than HC across both regions (p=0.015), but there were no significant Glx differences between CHR-P and HC. These data suggest that increased risk for psychosis is associated with altered relationships between corticolimbic connectivity and glutamatergic function.

In-scanner head motion is a recognized source of bias in structural magnetic resonance imaging (sMRI), yet it remains under-addressed in psychiatric neuroimaging where structural difference in patient populations are considered foundational. We examined motion-related bias in grey matter volume estimates across eight independent cohorts comprising 9,664 individuals, including 8,979 neurotypical controls (NC), 497 patients with schizophrenia (SCZ), and 188 patients with bipolar disorder (BD). Motion estimates were derived from multiple fMRI scans acquired within the same scanning session and summarized using principal component analysis. In NC, motion accounted for 1-6% of regional grey matter variance, a magnitude comparable to reported psychiatric case-control effect sizes. Adjusting for motion attenuated SCZ-NC group differences, reducing effect sizes in 85% of brain regions and yielding 5% fewer significant ROIs (pFDR<0.05). In BD, motion correction reduced effect sizes in 97% of regions, with a 24% reduction in significant ROIs. Cross-diagnostic spatial patterns were significantly correlated (r=0.63, p=3x10-{superscript 1}3), explaining a sizable portion of SCZ-BD commonalities. Critically, a falsification analysis in UK Biobank (N=5,123) showed that stratifying NC by motion alone produced grey matter differences accounting for 45-62% of SCZ case-control effect magnitude, underscoring how difficult it is to interpret SCZ-like morphometric differences as tissue properties rather than as motion-driven patterns. These findings urge caution in interpretations of sMRIdifferences in patient-control comparisons and use of systematic fMRI based motion control as standard practice in sMRI analyses.