Faster bi-stable visual switching in psychosis.

Bi-stable stimuli evoke two distinct perceptual interpretations that alternate and compete for dominance. Bi-stable perception is thought to be driven at least in part by mutual suppression between distinct neural populations that represent each percept. Abnormal visual perception has been observed among people with psychotic psychopathology (PwPP), and there is evidence to suggest that these visual deficits may depend on impaired neural suppression in the visual cortex. However, it is not yet clear whether bi-stable visual perception is abnormal among PwPP. Here, we examined bi-stable perception in a visual structure-from-motion task using a rotating cylinder illusion in a group of 65 PwPP, 44 first-degree biological relatives, and 43 healthy controls. Data from a 'real switch' task, in which physical depth cues signaled real switches in rotation direction were used to exclude individuals who did not show adequate task performance. In addition, we measured concentrations of neurochemicals, including glutamate, glutamine, and γ-amino butyric acid (GABA), involved in excitatory and inhibitory neurotransmission. These neurochemicals were measured non-invasively in the visual cortex using 7 tesla MR spectroscopy. We found that PwPP and their relatives showed faster bi-stable switch rates than healthy controls. Faster switch rates also correlated with significantly higher psychiatric symptom levels, specifically disorganization, across all participants. However, we did not observe any significant relationships across individuals between neurochemical concentrations and SFM switch rates. Our results are consistent with a reduction in suppressive neural processes during structure-from-motion perception in PwPP, and suggest that genetic liability for psychosis is associated with disrupted bi-stable perception.

Differences in the neural correlates of schizophrenia with positive and negative formal thought disorder in patients with schizophrenia in the ENIGMA dataset.

Formal thought disorder (FTD) is a clinical key factor in schizophrenia, but the neurobiological underpinnings remain unclear. In particular, the relationship between FTD symptom dimensions and patterns of regional brain volume loss in schizophrenia remains to be established in large cohorts. Even less is known about the cellular basis of FTD. Our study addresses these major obstacles by enrolling a large multi-site cohort acquired by the ENIGMA Schizophrenia Working Group (752 schizophrenia patients and 1256 controls), to unravel the neuroanatomy of FTD in schizophrenia and using virtual histology tools on implicated brain regions to investigate the cellular basis. Based on the findings of previous clinical and neuroimaging studies, we decided to separately explore positive, negative and total formal thought disorder. We used virtual histology tools to relate brain structural changes associated with FTD to cellular distributions in cortical regions. We identified distinct neural networks positive and negative FTD. Both networks encompassed fronto-occipito-amygdalar brain regions, but positive and negative FTD demonstrated a dissociation: negative FTD showed a relative sparing of orbitofrontal cortical thickness, while positive FTD also affected lateral temporal cortices. Virtual histology identified distinct transcriptomic fingerprints associated for both symptom dimensions. Negative FTD was linked to neuronal and astrocyte fingerprints, while positive FTD also showed associations with microglial cell types. These results provide an important step towards linking FTD to brain structural changes and their cellular underpinnings, providing an avenue for a better mechanistic understanding of this syndrome.

The relationship between blast-related mild traumatic brain injury and executive function is moderated by white matter integrity.

Blast-related mild traumatic brain injury (BR mTBI) is a critical research area in recent combat veterans due to increased prevalence of survived blasts. Post-BR mTBI outcomes are highly heterogeneous and defining neurological differences may help in discrimination and prediction of cognitive outcomes. This study investigates whether white matter integrity, measured with diffusion tensor imaging (DTI), could influence how remote BR mTBI history is associated with executive control. The sample included 151 Veterans from the Minneapolis Veterans Affairs Medical Center who were administered a clinical/TBI assessment, neuropsychological battery, and DTI scan as part of a larger battery. From previous research, six white matter tracts were identified as having a putative relationship with blast severity: the cingulum, hippocampal cingulum, corticospinal tract, inferior fronto-occipital fasciculus, superior longitudinal fasciculus and uncinate. Fractional anisotropy (FA) of the a priori selected white matter tracts and report of BR mTBI were used as predictors of Trail-Making Test B (TMT-B) performance in a multiple linear regression model. Statistical analysis revealed that FA of the hippocampal cingulum moderated the association between report of at least one BR mTBI and poorer TMT-B performance (p < 0.008), such that lower FA value was associated with worse TMT-B outcomes in individuals with BR mTBI. No significant moderation existed for other selected tracts, and the effect was not observed with predictors aside from history of BR mTBI. Investigation at the individual-tract level may lead to a deeper understanding of neurological differences between blast-related and non-blast related injuries.

Intrusive Traumatic Re-Experiencing Domain: Functional Connectivity Feature Classification by the ENIGMA PTSD Consortium.

Background: Intrusive traumatic re-experiencing domain (ITRED) was recently introduced as a novel perspective on posttraumatic psychopathology, proposing to focus research of posttraumatic stress disorder (PTSD) on the unique symptoms of intrusive and involuntary re-experiencing of the trauma, namely, intrusive memories, nightmares, and flashbacks. The aim of the present study was to explore ITRED from a neural network connectivity perspective. Methods: Data were collected from 9 sites taking part in the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) PTSD Consortium (n= 584) and included itemized PTSD symptom scores and resting-state functional connectivity (rsFC) data. We assessed the utility of rsFC in classifying PTSD, ITRED-only (no PTSD diagnosis), and trauma-exposed (TE)-only (no PTSD or ITRED) groups using a machine learning approach, examining well-known networks implicated in PTSD. A random forest classification model was built on a training set using cross-validation, and the averaged cross-validation model performance for classification was evaluated using the area under the curve. The model was tested using a fully independent portion of the data (test dataset), and the test area under the curve was evaluated. Results: rsFC signatures differentiated TE-only participants from PTSD and ITRED-only participants at about 60% accuracy. Conversely, rsFC signatures did not differentiate PTSD from ITRED-only individuals (45% accuracy). Common features differentiating TE-only participants from PTSD and ITRED-only participants mainly involved default mode network-related pathways. Some unique features, such as connectivity within the frontoparietal network, differentiated TE-only participants from one group (PTSD or ITRED-only) but to a lesser extent from the other group. Conclusions: Neural network connectivity supports ITRED as a novel neurobiologically based approach to classifying posttrauma psychopathology.

Clarifying Cognitive Control Deficits in Psychosis via Drift Diffusion Modeling and Attractor Dynamics.

BACKGROUND AND HYPOTHESIS: Cognitive control deficits are prominent in individuals with psychotic psychopathology. Studies providing evidence for deficits in proactive control generally examine average performance and not variation across trials for individuals-potentially obscuring detection of essential contributors to cognitive control. Here, we leverage intertrial variability through drift-diffusion models (DDMs) aiming to identify key contributors to cognitive control deficits in psychosis. STUDY DESIGN: People with psychosis (PwP; N = 122), their first-degree biological relatives (N = 78), and controls (N = 50) each completed 120 trials of the dot pattern expectancy (DPX) cognitive control task. We fit full hierarchical DDMs to response and reaction time (RT) data for individual trials and then used classification models to compare the DDM parameters with conventional measures of proactive and reactive control. STUDY RESULTS: PwP demonstrated slower drift rates on proactive control trials suggesting less efficient use of cue information. Both PwP and relatives showed protracted nondecision times to infrequent trial sequences suggesting slowed perceptual processing. Classification analyses indicated that DDM parameters differentiated between the groups better than conventional measures and identified drift rates during proactive control, nondecision time during reactive control, and cue bias as most important. DDM parameters were associated with real-world functioning and schizotypal traits. CONCLUSIONS: Modeling of trial-level data revealed that slow evidence accumulation and longer preparatory periods are the strongest contributors to cognitive control deficits in psychotic psychopathology. This pattern of atypical responding during the DPX is consistent with shallow basins in attractor dynamic models that reflect difficulties in maintaining state representations, possibly mediated by excess neural excitation or poor connectivity.

Connectome architecture shapes large-scale cortical alterations in schizophrenia: a worldwide ENIGMA study.

Schizophrenia is a prototypical network disorder with widespread brain-morphological alterations, yet it remains unclear whether these distributed alterations robustly reflect the underlying network layout. We tested whether large-scale structural alterations in schizophrenia relate to normative structural and functional connectome architecture, and systematically evaluated robustness and generalizability of these network-level alterations. Leveraging anatomical MRI scans from 2439 adults with schizophrenia and 2867 healthy controls from 26 ENIGMA sites and normative data from the Human Connectome Project (n = 207), we evaluated structural alterations of schizophrenia against two network susceptibility models: (i) hub vulnerability, which examines associations between regional network centrality and magnitude of disease-related alterations; (ii) epicenter mapping, which identifies regions whose typical connectivity profile most closely resembles the disease-related morphological alterations. To assess generalizability and specificity, we contextualized the influence of site, disease stages, and individual clinical factors and compared network associations of schizophrenia with that found in affective disorders. Our findings show schizophrenia-related cortical thinning is spatially associated with functional and structural hubs, suggesting that highly interconnected regions are more vulnerable to morphological alterations. Predominantly temporo-paralimbic and frontal regions emerged as epicenters with connectivity profiles linked to schizophrenia's alteration patterns. Findings were robust across sites, disease stages, and related to individual symptoms. Moreover, transdiagnostic comparisons revealed overlapping epicenters in schizophrenia and bipolar, but not major depressive disorder, suggestive of a pathophysiological continuity within the schizophrenia-bipolar-spectrum. In sum, cortical alterations over the course of schizophrenia robustly follow brain network architecture, emphasizing marked hub susceptibility and temporo-frontal epicenters at both the level of the group and the individual. Subtle variations of epicenters across disease stages suggest interacting pathological processes, while associations with patient-specific symptoms support additional inter-individual variability of hub vulnerability and epicenters in schizophrenia. Our work outlines potential pathways to better understand macroscale structural alterations, and inter- individual variability in schizophrenia.

Reward anticipation-related neural activation following cued reinforcement in adults with psychotic psychopathology and biological relatives.

BACKGROUND: Schizophrenia is associated with hypoactivation of reward sensitive brain areas during reward anticipation. However, it is unclear whether these neural functions are similarly impaired in other disorders with psychotic symptomatology or individuals with genetic liability for psychosis. If abnormalities in reward sensitive brain areas are shared across individuals with psychotic psychopathology and people with heightened genetic liability for psychosis, there may be a common neural basis for symptoms of diminished pleasure and motivation. METHODS: We compared performance and neural activity in 123 people with a history of psychosis (PwP), 81 of their first-degree biological relatives, and 49 controls during a modified Monetary Incentive Delay task during fMRI. RESULTS: PwP exhibited hypoactivation of the striatum and anterior insula (AI) during cueing of potential future rewards with each diagnostic group showing hypoactivations during reward anticipation compared to controls. Despite normative task performance, relatives demonstrated caudate activation intermediate between controls and PwP, nucleus accumbens activation more similar to PwP than controls, but putamen activation on par with controls. Across diagnostic groups of PwP there was less functional connectivity between bilateral caudate and several regions of the salience network (medial frontal gyrus, anterior cingulate, AI) during reward anticipation. CONCLUSIONS: Findings implicate less activation and connectivity in reward processing brain regions across a spectrum of disorders involving psychotic psychopathology. Specifically, aberrations in striatal and insular activity during reward anticipation seen in schizophrenia are partially shared with other forms of psychotic psychopathology and associated with genetic liability for psychosis.

Limited Consistency and Strength of Neural Oscillations During Sustained Visual Attention in Schizophrenia.

BACKGROUND: Neural oscillations support perception, attention, and higher-order decision making. Aberrations in the strength or consistency of these oscillations in response to stimuli may underlie impaired visual perception and attention in schizophrenia. Here, we examined the phase and power of alpha oscillations (8-12 Hz) as well as aspects of beta and theta frequency oscillations during a demanding visual sustained attention task. METHODS: Patients with schizophrenia (n = 74) and healthy control participants (n = 68) completed the degraded stimulus continuous performance task during electroencephalography. We used time-frequency analysis to evaluate the consistency (intertrial phase coherence) of the alpha cycle shortly after stimulus presentation (50-250 ms). For oscillation strength, we examined event-related desynchronization in a later window associated with decision making (360-700 ms). RESULTS: Alpha intertrial phase coherence was reduced in schizophrenia, and similar reductions were observed in theta (4-7 Hz) and beta (13-20 Hz), suggesting a lack of responsiveness in slower oscillations to visual stimuli. Alpha and beta event-related desynchronization were also reduced in schizophrenia and associated with worse task performance, increased symptoms, and poorer cognition, suggesting that limited responsiveness of oscillations is related to impairments in the disorder. Individuals with lower intertrial phase coherence had slower resting-state alpha rhythms consistent with dysfunctional oscillations persisting across default and task-related brain states. CONCLUSIONS: In schizophrenia, abnormalities in the phase consistency and strength of slower oscillations during visual perception are related to symptoms and cognitive functioning. Altered visual perception and impaired attention in the disorder may be the consequence of aberrant slower oscillations that fail to dynamically reset and modulate in response to stimuli.

Examining the association between posttraumatic stress disorder and disruptions in cortical networks identified using data-driven methods.

Posttraumatic stress disorder (PTSD) is associated with lower cortical thickness (CT) in prefrontal, cingulate, and insular cortices in diverse trauma-affected samples. However, some studies have failed to detect differences between PTSD patients and healthy controls or reported that PTSD is associated with greater CT. Using data-driven dimensionality reduction, we sought to conduct a well-powered study to identify vulnerable networks without regard to neuroanatomic boundaries. Moreover, this approach enabled us to avoid the excessive burden of multiple comparison correction that plagues vertex-wise methods. We derived structural covariance networks (SCNs) by applying non-negative matrix factorization (NMF) to CT data from 961 PTSD patients and 1124 trauma-exposed controls without PTSD. We used regression analyses to investigate associations between CT within SCNs and PTSD diagnosis (with and without accounting for the potential confounding effect of trauma type) and symptom severity in the full sample. We performed additional regression analyses in subsets of the data to examine associations between SCNs and comorbid depression, childhood trauma severity, and alcohol abuse. NMF identified 20 unbiased SCNs, which aligned closely with functionally defined brain networks. PTSD diagnosis was most strongly associated with diminished CT in SCNs that encompassed the bilateral superior frontal cortex, motor cortex, insular cortex, orbitofrontal cortex, medial occipital cortex, anterior cingulate cortex, and posterior cingulate cortex. CT in these networks was significantly negatively correlated with PTSD symptom severity. Collectively, these findings suggest that PTSD diagnosis is associated with widespread reductions in CT, particularly within prefrontal regulatory regions and broader emotion and sensory processing cortical regions.

Phenotyping Depression After Mild Traumatic Brain Injury: Evaluating the Impact of Multiple Injury, Gender, and Injury Context.

The chronic mental health consequences of mild traumatic brain injury (TBI) are a leading cause of disability. This is surprising given the expectation of significant recovery after mild TBI, which suggests that other injury-related factors may contribute to long-term adverse outcomes. The objective of this study was to determine how number of prior injuries, gender, and environment/context of injury may contribute to depressive symptoms after mild TBI among deployed United States service members and veterans (SMVs). Data from the Long-term Impact of Military-Relevant Brain Injury Consortium Prospective Longitudinal Study was used to assess TBI injury characteristics and depression scores previously measured on the Patient Health Questionnaire-9 (PHQ-9) among a sample of 1456 deployed SMVs. Clinical diagnosis of mild TBI was defined via a multi-step process centered on a structured face-to-face interview. Logistical and linear regressions stratified by gender and environment of injury were used to model depressive symptoms controlling for sociodemographic and combat deployment covariates. Relative to controls with no history of mild TBI (n = 280), the odds ratios (OR) for moderate/severe depression (PHQ-9 ≥ 10) were higher for SMVs with one mild TBI (n = 358) OR: 1.62 (95% confidence interval [CI] 1.09-2.40, p = 0.016) and two or more mild TBIs (n = 818) OR: 1.84 (95% CI 1.31-2.59, p < 0.001). Risk differences across groups were assessed in stratified linear models, which found that depression symptoms were elevated in those with a history of multiple mild TBIs compared with those who had a single mild TBI (p < 0.001). Combat deployment-related injuries were also associated with higher depression scores than injuries occurring in non-combat or civilian settings (p < 0.001). Increased rates of depression after mild TBI persisted in the absence of post-traumatic stress disorder. Both men and women SMVs separately exhibited significantly increased depressive symptom scores if they had had combat-related mild TBI. These results suggest that contextual information, gender, and prior injury history may influence long-term mental health outcomes among SMVs with mild TBI exposure.

Adaptation in Young Military Recruits: Protocol for the Advancing Research on Mechanisms of Resilience (ARMOR) Prospective Longitudinal Study.

BACKGROUND: Military services provide a unique opportunity for studying resilience, a dynamic process of successful adaptation (ie, doing well in terms of functioning and symptoms) in response to significant adversity. Despite the tremendous interest in positive adaptation among military service members, little is known about the processes underlying their resilience. Understanding the neurobiological, cognitive, and social mechanisms underlying adaptive functioning following military stressor exposure is essential for enhancing the resilience of military service members. OBJECTIVE: The primary objective of the Advancing Research on Mechanisms of Resilience (ARMOR) longitudinal study is to characterize the trajectories of positive adaptation among young military recruits in response to basic combat training (BCT), a well-defined, uniform, and 10-week period of intense stress (aim 1), and identify promotive and protective processes contributing to individual variations in resilience (aim 2). The secondary objective is to investigate the pathways by which neurobehavioral markers of self-regulation assessed using electroencephalography and magnetic resonance imaging contribute to adaptive trajectories (aim 3). METHODS: ARMOR is an ongoing, prospective longitudinal cohort study of young military recruits who recently joined the National Guard but have not yet shipped out for BCT. Participants (N=1201) are assessed at 5 time points over the initial >2 years of military service beginning before BCT (baseline) and followed up at 2 weeks and 6, 12, and 18 months after BCT. Participants complete web-based questionnaires assessing vulnerability and protective factors, mental health, and socioemotional functioning at each time point and a battery of neurocognitive tests at time 0. A subset of participants also complete structured diagnostic interviews and additional self-report measures and perform neurobehavioral tasks before and after BCT during electroencephalography sessions and before BCT only during magnetic resonance imaging sessions. RESULTS: This UG3/UH3 project was initially funded in August 2017, with the UG3 pilot work completed at the end of 2018. The UH3 phase of the project was funded in March 2019. Study enrollment for the UH3 phase began on April 14, 2019, and ended on October 16, 2021. A total of 1201 participants are enrolled in the study. Follow-up data collection for the UH3 phase is ongoing and projected to continue through February 2024. We will disseminate the findings through conferences, webinars, open access publications, and communications with participants and stakeholders. CONCLUSIONS: The ARMOR study provides a rich data set to identify the predictors and mechanisms of resilient and nonresilient outcomes in the context of military stressors, which are intended to empirically inform the development of prevention and intervention strategies to enhance the resilience of military trainees and potentially other young people facing significant life challenges. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/51235.

Resting-State Functional Connectivity Explained Psychotic-like Experiences in the General Population and Partially Generalized to Patients and Relatives.

Background: Psychotic-like experiences (PLEs) are considered the subclinical portion of the psychosis continuum. Research suggests that there are resting-state functional connectivity (rsFC) substrates of PLEs, yet it is unclear if the same substrates underlie more severe psychosis. Here, to our knowledge, we report the first study to build a cross-validated rsFC model of PLEs in a large community sample and directly test its ability to explain psychosis in an independent sample of patients with psychosis and their relatives. Methods: Resting-state FC of 855 healthy young adults from the WU-Minn Human Connectome Project (HCP) was used to predict PLEs with elastic net. An rsFC composite score based on the resulting model was correlated with psychotic traits and symptoms in 118 patients with psychosis, 71 nonpsychotic first-degree relatives, and 45 healthy control subjects from the psychosis HCP. Results: In the HCP, the cross-validated model explained 3.3% of variance in PLEs. Predictive connections spread primarily across the default, frontoparietal, cingulo-opercular, and dorsal attention networks. The model partially generalized to a younger, but not older, subsample in the psychosis HCP, explaining two measures of positive/disorganized psychotic traits (the Structured Interview for Schizotypy: ß = 0.25, pone-tailed = .027; the Schizotypy Personality Questionnaire positive factor: ß = 0.14, pone-tailed = .041). However, it did not differentiate patients from relatives and control subjects or explain psychotic symptoms in patients. Conclusions: Some rsFC substrates of PLEs are shared across the psychosis continuum. However, explanatory power was modest, and generalization was partial. It is equally important to understand shared versus distinct rsFC variances across the psychosis continuum.

Long-term resting EEG correlates of repetitive mild traumatic brain injury and loss of consciousness: alterations in alpha-beta power.

Objective: Long-term changes to EEG spectra after mild traumatic brain injury (mTBI, i.e., concussion) have been reported; however, the role of injury characteristics in long-term EEG changes is unclear. It is also unclear how any chronic EEG changes may underlie either subjective or objective cognitive difficulties, which might help explain the variability in recovery after mTBI. Methods: This study included resting-state high-density electroencephalography (EEG) and mTBI injury data from 340 service members and veterans collected on average 11 years after injury as well as measures of objective and subjective cognitive functioning. The average absolute power within standard bands was computed across 11 spatial regions of the scalp. To determine how variation in brain function was accounted for by injury characteristics and aspects of cognition, we used regression analyses to investigate how EEG power was predicted by mTBI history characteristics [number, number with post-traumatic amnesia and witnessed loss of consciousness (PTA + LOC), context of injury (combat or non-combat), potentially concussive blast exposures], subjective complaints (TBIQOL General Cognitive and Executive Function Concerns), and cognitive performance (NIH Toolbox Fluid Intelligence and premorbid IQ). Results: Post-traumatic amnesia (PTA) and loss of consciousness (LOC), poorer cognitive performance, and combat experience were associated with reduced power in beta frequencies. Executive function complaints, lower premorbid IQ, poorer cognitive performance, and higher psychological distress symptoms were associated with greater power of delta frequencies. Multiple regression confirmed the relationship between PTA + LOC, poor cognitive performance, cognitive complaints, and reduced power in beta frequencies and revealed that repetitive mTBI was associated with a higher power in alpha and beta frequencies. By contrast, neither dichotomous classification of the presence and absence of mTBI history nor blast exposures showed a relationship with EEG power variables. Conclusion: Long-term alterations in resting EEG spectra measures of brain function do not appear to reflect any lasting effect of a history of mTBI or blast exposures. However, power in higher frequencies reflects both injury characteristics and subjective and objective cognitive difficulties, while power in lower frequencies is related to cognitive functions and psychological distress associated with poor long-term outcomes after mTBI.

Clarifying Cognitive Control Deficits in Psychosis via Drift Diffusion Modeling.

Cognitive control deficits are consistently identified in individuals with schizophrenia and other psychotic psychopathologies. In this analysis, we delineated proactive and reactive control deficits in psychotic psychopathology via hierarchical Drift Diffusion Modeling (hDDM). People with psychosis (PwP; N=123), their first-degree relatives (N=79), and controls (N=51) completed the Dot Pattern Expectancy task, which allows differentiation between proactive and reactive control. PwP demonstrated slower drift rates on proactive control trials suggesting less efficient use of cue information for proactive control. They also showed longer non-decision times than controls on infrequent stimuli sequences suggesting slower perceptual processing. An explainable machine learning analysis indicated that the hDDM parameters were able to differentiate between the groups better than conventional measures. Through DDM, we found that cognitive control deficits in psychosis are characterized by slower motor/perceptual time and slower evidence-integration primarily in proactive control.

Neural abnormalities of reward processing in adolescents with bipolar disorders: An ERP study.

Adolescent onset is common in bipolar disorders (BDs) and is associated with a worse illness course in adulthood. A model of BDs suggests that a dysregulated behavioral approach system (BAS), a neural system that mobilizes reward-seeking behavior, is at the root of BDs. Normative adolescence is often accompanied by dynamic changes to neural structures underlying the BAS and related cognitive processes. It is possible that adolescent-onset BDs is associated with abnormal BAS neurodevelopment. Consistently, the present study is the first to compare specific BAS-relevant anticipatory and consummatory reward processes as indexed by event-related potentials (ERPs) in adolescents with BDs and typically developing peers. Using a sample of 43 adolescents with BDs and 56 without psychopathology, we analyzed N1 and P3 responses to anticipatory cues and feedback-related negativity (FRN) and P3 responses to feedback stimuli during a monetary incentive delay (MID) task. Hierarchical linear models examined relationships between ERP amplitudes and diagnostic group, MID condition, sex, and age. During anticipation phase, adolescent boys with BDs exhibited significantly larger N1 amplitudes in loss than even or gain trials. During feedback phase, compared to their healthy peers, adolescents with BDs had smaller FRN amplitudes across all conditions. Additional effects involving age, sex and trial type were observed. The findings indicate subtle, non-ubiquitous BAS-relevant neural abnormalities involving early attentional processes during reward anticipation and reward learning following feedback in adolescents with BDs. Adolescents with BDs did not show overall hypersensitive neural responses to monetary reward anticipation or feedback observed in adults with BDs.

Posttraumatic reexperiencing and alcohol use: mediofrontal theta as a neural mechanism for negative reinforcement.

Objective: Over half of US military veterans with posttraumatic stress disorder (PTSD) use alcohol heavily, potentially to cope with their symptoms. This study investigated the neural underpinnings of PTSD symptoms and heavy drinking in veterans. We focused on brain responses to salient outcomes within predictive coding theory. This framework suggests the brain generates prediction errors (PEs) when outcomes deviate from expectations. Alcohol use might provide negative reinforcement by reducing the salience of negatively-valenced PEs and dampening experiences like loss. Methods: We analyzed electroencephalography (EEG) responses to unpredictable gain/loss feedback in veterans of Operations Enduring and Iraqi Freedom. We used time-frequency principal components analysis of event-related potentials to isolate neural responses indicative of PEs, identifying mediofrontal theta linked to losses (feedback-related negativity, FRN) and central delta associated with gains (reward positivity, RewP). Results: Intrusive reexperiencing symptoms of PTSD were associated with intensified mediofrontal theta signaling during losses, suggesting heightened negative PE sensitivity. Conversely, increased hazardous alcohol use was associated with reduced theta responses, implying a dampening of these negative PEs. The separate delta-RewP component showed associations with alcohol use but not PTSD symptoms. Conclusions: Findings suggest a common neural component of PTSD and hazardous alcohol use involving altered PE processing. We suggest that reexperiencing enhances the intensity of salient negative PEs, while chronic alcohol use may reduce their intensity, thereby providing negative reinforcement by muting emotional disruption from reexperienced trauma. Modifying the mediofrontal theta response could address the intertwined nature of PTSD symptoms and alcohol use, providing new avenues for treatment.

Advancing Research on Mechanisms of Resilience (ARMOR) Prospective Longitudinal Study of Adaptation in Young Military Recruits: Protocol and rationale for methods and measures.

Background: Military service provides a unique opportunity for studying resilience, a dynamic process of successful adaptation (i.e., doing well in terms of functioning and symptoms) in response to significant adversity. Despite tremendous interest in positive adaptation among military service members, little is known about the processes underlying their resilience. Understanding neurobiological, cognitive, and social mechanisms underlying adaptive functioning following military stressor exposure is essential to enhance the resilience of military service members. Objectives: The primary objective of the Advancing Research on Mechanisms of Resilience (ARMOR) longitudinal study is to characterize trajectories of positive adaptation among young military recruits in response to Basic Combat Training (BCT), a well-defined, uniform, 10-week period of intense stress (Aim 1) and identify promotive and protective processes contributing to individual variations in resilience (Aim 2). The secondary objective is to investigate pathways by which neurobehavioral markers of self-regulation assessed by electroencephalography (EEG) and magnetic resonance imaging (MRI) contribute to adaptive trajectories (Aim 3). Methods: ARMOR is an ongoing, prospective longitudinal cohort study of young military recruits who recently joined the National Guard but have not yet shipped for BCT. Participants (N=1,201) are assessed at five timepoints over the initial 2+ years of military service beginning before BCT (baseline) and followed up at 2 weeks, 6, 12, and 18 months post-BCT. At each time point, participants complete online questionnaires assessing vulnerability and protective factors, mental health and social-emotional functioning, and, at Time 0 only, a battery of neurocognitive tests. A subset of participants also complete structured diagnostic interviews, additional self-report measures, and perform neurobehavioral tasks before and after BCT during EEG sessions, and, at pre-BCT only, during MRI sessions. Results: Study enrollment began April 14, 2019 and ended in October 16, 2021. A total of 1,201 participants are enrolled in the study (68.9% male; mean age = 18.9, SD = 3.0). Follow-up data-collection is ongoing and projected to continue through March 2024. We will disseminate findings through conferences, webinars, open access publications, and communications with participants and stakeholders. Conclusions: Results are expected to elucidate how young military recruits adapt to military stressors during the initial years of military service. Understanding positive adaptation of military recruits in the face of BCT has implications for developing prevention and intervention strategies to enhance resilience of military trainees and potentially other young people facing significant life challenges.

Slowed alpha oscillations and percept formation in psychotic psychopathology.

Introduction: Psychosis is in part defined by disturbances in perception. Recent investigations have implicated the speed of alpha oscillations observed in brain electrical activity as reflective of a sampling rate of the visual environment and perception. Although both slowed alpha oscillations and aberrant percept formation are evident in disorders of psychotic psychopathology such as schizophrenia it is unclear whether slow alpha accounts for abnormal visual perception in these disorders. Methods: To examine the role of the speed of alpha oscillations in perception in psychotic psychopathology we gathered resting-state magneto-encephalography data from probands with psychotic psychopathology (i.e., schizophrenia, schizoaffective disorder, and bipolar disorder with a history of psychosis), their biological siblings, and healthy controls. We appraised visual perceptual function without the confound of cognitive ability and effort through the use of a simple binocular rivalry task. Results: We found a slowed pace of alpha oscillations in psychotic psychopathology that was associated with longer percept durations during binocular rivalry, consistent with the assertion that occipital alpha oscillations govern the rate of accumulation of visual information used to generate percepts. Alpha speed varied widely across individuals with psychotic psychopathology and was highly stable across several months indicating that it is likely a trait characteristic of neural function that is relevant to visual perception. Finally, a lower speed of alpha oscillation was associated with a lower IQ and greater disorder symptomatology implying that the effects of the endogenous neural oscillation on visual perception may have wider consequences for everyday functioning. Discussion: Slowed alpha oscillations in individuals with psychotic psychopathology appear to reflect altered neural functions related to percept formation.

Neural Correlates of Positive and Negative Formal Thought Disorder in Individuals with Schizophrenia: An ENIGMA Schizophrenia Working Group Study.

Formal thought disorder (FTD) is a key clinical factor in schizophrenia, but the neurobiological underpinnings remain unclear. In particular, relationship between FTD symptom dimensions and patterns of regional brain volume deficiencies in schizophrenia remain to be established in large cohorts. Even less is known about the cellular basis of FTD. Our study addresses these major obstacles based on a large multi-site cohort through the ENIGMA Schizophrenia Working Group (752 individuals with schizophrenia and 1256 controls), to unravel the neuroanatomy of positive, negative and total FTD in schizophrenia and their cellular bases. We used virtual histology tools to relate brain structural changes associated with FTD to cellular distributions in cortical regions. We identified distinct neural networks for positive and negative FTD. Both networks encompassed fronto-occipito-amygdalar brain regions, but negative FTD showed a relative sparing of orbitofrontal cortical thickness, while positive FTD also affected lateral temporal cortices. Virtual histology identified distinct transcriptomic fingerprints associated for both symptom dimensions. Negative FTD was linked to neuronal and astrocyte fingerprints, while positive FTD was also linked to microglial cell types. These findings relate different dimensions of FTD to distinct brain structural changes and their cellular underpinnings, improve our mechanistic understanding of these key psychotic symptoms.

ETSNet: A deep neural network for EEG-based temporal-spatial pattern recognition in psychiatric disorder and emotional distress classification.

The use of EEG for evaluating and diagnosing neurological abnormalities related to psychiatric diseases and identifying human emotions has been improved by deep learning advancements. This research aims to categorize individuals with schizophrenia (SZ), their biological relatives (REL), and healthy controls (HC) using resting EEG brain source signal data defined by regions of interest (ROIs). The proposed solution is a deep neural network for the cortical source signals of the ROIs, incorporating a Squeeze-and-Excitation Block and multiple CNNs designed for eyes-open and closed resting states. The model, called EEG Temporal Spatial Network (ETSNet), has two variants: ETSNets and ETSNetf. Two evaluations were conducted to show the effectiveness of the proposed model. The average accuracy for the classification of SZ, REL, and HC using EEG resting data was 99.57% (ETSNetf), and the average accuracy for the classification of eyes-open (EO) and eyes-closed (EC) resting states was 93.15% (ETSNets). An ablation study was also conducted using two public datasets for intellectual and developmental disorders and emotional states, showing improved classification accuracy compared to advanced EEG classification algorithms when using ETSNets.