Atypical Dynamic Functional Network Connectivity State Engagement during Social-Emotional Processing in Schizophrenia and Autism.

Autism spectrum disorder (ASD) and schizophrenia (SZ) are separate clinical entities but share deficits in social-emotional processing and static neural functional connectivity patterns. We compared patients' dynamic functional network connectivity (dFNC) state engagement with typically developed (TD) individuals during social-emotional processing after initially characterizing such dynamics in TD. Young adults diagnosed with ASD (n = 42), SZ (n = 41), or TD (n = 55) completed three functional MRI runs, viewing social-emotional videos with happy, sad, or neutral content. We examined dFNC of 53 spatially independent networks extracted using independent component analysis and applied k-means clustering to windowed dFNC matrices, identifying four unique whole-brain dFNC states. TD showed differential engagement (fractional time, mean dwell time) in three states as a function of emotion. During Happy videos, patients spent less time than TD in a happy-associated state and instead spent more time in the most weakly connected state. During Sad videos, only ASD spent more time than TD in a sad-associated state. Additionally, only ASD showed a significant relationship between dFNC measures and alexithymia and social-emotional recognition task scores, potentially indicating different neural processing of emotions in ASD and SZ. Our results highlight the importance of examining temporal whole-brain reconfiguration of FNC, indicating engagement in unique emotion-specific dFNC states.

Mega-analysis methods in ENIGMA: The experience of the generalized anxiety disorder working group.

The ENIGMA group on Generalized Anxiety Disorder (ENIGMA-Anxiety/GAD) is part of a broader effort to investigate anxiety disorders using imaging and genetic data across multiple sites worldwide. The group is actively conducting a mega-analysis of a large number of brain structural scans. In this process, the group was confronted with many methodological challenges related to study planning and implementation, between-country transfer of subject-level data, quality control of a considerable amount of imaging data, and choices related to statistical methods and efficient use of resources. This report summarizes the background information and rationale for the various methodological decisions, as well as the approach taken to implement them. The goal is to document the approach and help guide other research groups working with large brain imaging data sets as they develop their own analytic pipelines for mega-analyses.

Factors Related to Passive Social Withdrawal and Active Social Avoidance in Schizophrenia.

ABSTRACT: Social withdrawal in schizophrenia may be a result of "passive" motivation (reduced drive to engage) or "active" motivation (increased drive to avoid). We conducted a cross-sectional, between-subjects study using self-report measures and social cognition tasks to evaluate the relationships between motivational subtypes, social abilities, and social functioning in schizophrenia spectrum (n = 52, ages 19-34). Regression models showed significant differences in passive and active withdrawal. Passive, but not active, motivation predicted social functioning as measured by a clinical interview. This suggests that motivation, especially passive type, plays an important role in social withdrawal in schizophrenia. However, on a self-report measure of social functioning, neither passive nor active motivation predicted outcomes, suggesting a potential disconnect between observer versus self-report measures when assessing social motivation. Furthermore, performance on tasks of social abilities did not predict motivation, which supports the idea that motivation is distinct from social ability and should be specifically addressed in treatment.

Dynamic functional network reconfiguration underlying the pathophysiology of schizophrenia and autism spectrum disorder.

The dynamics of the human brain span multiple spatial scales, from connectivity associated with a specific region/network to the global organization, each representing different brain mechanisms. Yet brain reconfigurations at different spatial scales are seldom explored and whether they are associated with the neural aspects of brain disorders is far from understood. In this study, we introduced a dynamic measure called step-wise functional network reconfiguration (sFNR) to characterize how brain configuration rewires at different spatial scales. We applied sFNR to two independent datasets, one includes 160 healthy controls (HCs) and 151 patients with schizophrenia (SZ) and the other one includes 314 HCs and 255 individuals with autism spectrum disorder (ASD). We found that both SZ and ASD have increased whole-brain sFNR and sFNR between cerebellar and subcortical/sensorimotor domains. At the ICN level, the abnormalities in SZ are mainly located in ICNs within subcortical, sensory, and cerebellar domains, while the abnormalities in ASD are more widespread across domains. Interestingly, the overlap SZ-ASD abnormality in sFNR between cerebellar and sensorimotor domains was correlated with the reasoning-problem-solving performance in SZ (r = -.1652, p = .0058) as well as the Autism Diagnostic Observation Schedule in ASD (r = .1853, p = .0077). Our findings suggest that dynamic reconfiguration deficits may represent a key intersecting point for SZ and ASD. The investigation of brain dynamics at different spatial scales can provide comprehensive insights into the functional reconfiguration, which might advance our knowledge of cognitive decline and other pathophysiology in brain disorders.

Moving Beyond the Negative: Contributions of Positive and Negative Affect on Quality of Life in Patients With Generalized Anxiety Disorder.

Individuals with generalized anxiety disorder (GAD) report poorer quality of life (QOL) than do nonanxious controls. Further, although positive affect (PA) and negative affect (NA) have been shown to predict QOL, no previous literature has tested this relationship in the context of individuals with GAD. In the present study, we evaluated the unique and interactive contributions of PA and NA on QOL within a sample of individuals diagnosed with GAD (N = 50). Specifically, a hierarchical regression was conducted to evaluate the unique contributions of PA, NA, and their interaction on QOL, over and above symptoms of depression. PA and depression symptoms were both significant predictors of QOL, whereas neither the main effect for NA nor the PA × NA interaction was statistically significant. Results suggest that, for those with GAD, PA uniquely contributes to QOL. Strategies to upregulate PA may be a useful treatment target for increasing QOL in individuals with GAD.

Inferring pathobiology from structural MRI in schizophrenia and bipolar disorder: Modeling head motion and neuroanatomical specificity.

Despite over 400 peer-reviewed structural MRI publications documenting neuroanatomic abnormalities in bipolar disorder and schizophrenia, the confounding effects of head motion and the regional specificity of these defects are unclear. Using a large cohort of individuals scanned on the same research dedicated MRI with broadly similar protocols, we observe reduced cortical thickness indices in both illnesses, though less pronounced in bipolar disorder. While schizophrenia (n = 226) was associated with wide-spread surface area reductions, bipolar disorder (n = 227) and healthy comparison subjects (n = 370) did not differ. We replicate earlier reports that head motion (estimated from time-series data) influences surface area and cortical thickness measurements and demonstrate that motion influences a portion, but not all, of the observed between-group structural differences. Although the effect sizes for these differences were small to medium, when global indices were covaried during vertex-level analyses, between-group effects became nonsignificant. This analysis raises doubts about the regional specificity of structural brain changes, possible in contrast to functional changes, in affective and psychotic illnesses as measured with current imaging technology. Given that both schizophrenia and bipolar disorder showed cortical thickness reductions, but only schizophrenia showed surface area changes, and assuming these measures are influenced by at least partially unique sets of biological factors, then our results could indicate some degree of specificity between bipolar disorder and schizophrenia. Hum Brain Mapp 38:3757-3770, 2017. © 2017 Wiley Periodicals, Inc.

Neuroimaging data sharing on the neuroinformatics database platform.

We describe the Neuroinformatics Database (NiDB), an open-source database platform for archiving, analysis, and sharing of neuroimaging data. Data from the multi-site projects Autism Brain Imaging Data Exchange (ABIDE), Bipolar-Schizophrenia Network on Intermediate Phenotypes parts one and two (B-SNIP1, B-SNIP2), and Monetary Incentive Delay task (MID) are available for download from the public instance of NiDB, with more projects sharing data as it becomes available. As demonstrated by making several large datasets available, NiDB is an extensible platform appropriately suited to archive and distribute shared neuroimaging data.

Neuroimaging measures of error-processing: Extracting reliable signals from event-related potentials and functional magnetic resonance imaging.

Error-related brain activity has become an increasingly important focus of cognitive neuroscience research utilizing both event-related potentials (ERPs) and functional magnetic resonance imaging (fMRI). Given the significant time and resources required to collect these data, it is important for researchers to plan their experiments such that stable estimates of error-related processes can be achieved efficiently. Reliability of error-related brain measures will vary as a function of the number of error trials and the number of participants included in the averages. Unfortunately, systematic investigations of the number of events and participants required to achieve stability in error-related processing are sparse, and none have addressed variability in sample size. Our goal here is to provide data compiled from a large sample of healthy participants (n=180) performing a Go/NoGo task, resampled iteratively to demonstrate the relative stability of measures of error-related brain activity given a range of sample sizes and event numbers included in the averages. We examine ERP measures of error-related negativity (ERN/Ne) and error positivity (Pe), as well as event-related fMRI measures locked to False Alarms. We find that achieving stable estimates of ERP measures required four to six error trials and approximately 30 participants; fMRI measures required six to eight trials and approximately 40 participants. Fewer trials and participants were required for measures where additional data reduction techniques (i.e., principal component analysis and independent component analysis) were implemented. Ranges of reliability statistics for various sample sizes and numbers of trials are provided. We intend this to be a useful resource for those planning or evaluating ERP or fMRI investigations with tasks designed to measure error-processing.

Repetitive transcranial magnetic stimulation for generalised anxiety disorder: a pilot randomised, double-blind, sham-controlled trial.

BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) holds promise for treating generalised anxiety disorder (GAD) but has only been studied in uncontrolled research. AIMS: This is the first randomised controlled trial (clinicaltrials.gov: NCT01659736) to investigate the efficacy and neural correlates of rTMS in GAD. METHOD: Twenty five participants (active n = 13; sham, n = 12) enrolled. rTMS was targeted at the right dorsolateral prefrontal cortex (DLPFC, 1 Hz, 90% resting motor threshold). RESULTS: Response and remission rates were higher in the active v. sham groups and there were significant group × time interactions for anxiety, worry and depressive symptoms, favouring active v. sham. In addition, right DLPFC activation during a decision-making gambling task increased at post-treatment for active rTMS only, and changes in neuroactivation correlated significantly with changes in worry symptoms. CONCLUSIONS: Findings provide preliminary evidence that rTMS may improve GAD symptoms in association with modifying neural activity in the stimulation site.

Specific default mode subnetworks support mentalizing as revealed through opposing network recruitment by social and semantic FMRI tasks.

The ability to attribute mental states to others, or "mentalizing," is posited to involve specific subnetworks within the overall default mode network (DMN), but this question needs clarification. To determine which default mode (DM) subnetworks are engaged by mentalizing processes, we assessed task-related recruitment of DM subnetworks. Spatial independent component analysis (sICA) applied to fMRI data using relatively high-order model (75 components). Healthy participants (n = 53, ages 17-60) performed two fMRI tasks: an interactive game involving mentalizing (Domino), a semantic memory task (SORT), and a resting state fMRI scan. sICA of the two tasks split the DMN into 10 subnetworks located in three core regions: medial prefrontal cortex (mPFC; five subnetworks), posterior cingulate/precuneus (PCC/PrC; three subnetworks), and bilateral temporoparietal junction (TPJ). Mentalizing events increased recruitment in five of 10 DM subnetworks, located in all three core DMN regions. In addition, three of these five DM subnetworks, one dmPFC subnetwork, one PCC/PrC subnetwork, and the right TPJ subnetwork, showed reduced recruitment by semantic memory task events. The opposing modulation by the two tasks suggests that these three DM subnetworks are specifically engaged in mentalizing. Our findings, therefore, suggest the unique involvement of mentalizing processes in only three of 10 DM subnetworks, and support the importance of the dmPFC, PCC/PrC, and right TPJ in mentalizing as described in prior studies.

Imbalanced neural responsivity to risk and reward indicates stress vulnerability in humans.

Trauma-related psychopathology has been associated with an intense emotional reaction to stressful event. Emotional responses have evolved to signal the presence of risks to be avoided or of rewards to be approached in the environment. Thus, individuals' sensitivity to signals of risk and reward may affect the level of stress vulnerability. Stress, however, can modify these sensitivities as well. In the current functional magnetic resonance imaging (fMRI) study, we prospectively probed the neural correlates of such sensitivities in 24 healthy soldiers by using an interactive game that encompasses risky and rewarding intervals both pre-exposure and post-exposure to stressful military service. As expected, risky and rewarding intervals elicited selective responses in the amygdala and nucleus accumbens (Nacc), respectively. Furthermore, increased post-traumatic stress disorder symptoms post-exposure (i.e., stress vulnerability) corresponded to greater amygdala's response to risk both pre-exposure and post-exposure and to decreased NAcc response to reward only post-exposure. By combining these regional responsivities post-exposure, we accurately identified all the most vulnerable soldiers. Imbalanced neural responsivity to risk and reward following exposure to stress may therefore constitute a marker for stress vulnerability. Such identification of vulnerability biomarkers can aid future diagnostic and therapeutic efforts by allowing early detection of vulnerability as well as follow up on patient's treatment progression.

Subscales of alexithymia show unique pathways through reappraisal and suppression to anxiety, depression and stress.

The goal of this work was to explore associations of constituent factors of alexithymia on mental health and potential mediating effects of emotion regulation strategies, specifically suppression and reappraisal. Data were collected through the crowd-sourcing platform Amazon Mechanical Turk (MTURK). Three hundred seventy-seven individuals completed questionnaires related to distress (Depression Anxiety Stress Scales [DASS]), emotion regulation (Emotion Regulation Questionnaire [ERQ]) and Alexithymia (Bermond-Vorst Alexithymia Questionnaire [BVAQ]). Three mediation models were constructed for depression, anxiety and stress, with BVAQ subscales (verbalizing, identifying, emotionalizing, fantasizing, and analyzing) as predictors and ERQ subscales (suppression and reappraisal) as mediators. Results indicated 37.3 % variance in depression, 25.2 % variance in anxiety, and 35.3 % variance in stress was explained by each model. Direct associations revealed emotionalizing and fantasizing were negatively associated with depression, anxiety, and stress, while verbalizing was additionally associated with depression, identifying was additionally associated with anxiety, and all four BVAQ subscales were associated with stress. BVAQ subscales demonstrated negative associations with reappraisal and positive associations with suppression that mediated anxiety and depression. However, suppression did not mediate relationships between BVAQ subscales with stress. Findings support the importance of examining multiple factors of alexithymia and associations with emotion regulation strategies and distress.

Disentangling negative and positive symptoms in schizophrenia and autism spectrum disorder.

Autism spectrum disorder (ASD) and schizophrenia (SZ) share traits, especially in social skills and negative symptoms, and to a lesser degree positive symptoms. Differential diagnosis can be challenging and discerning expressive and experiential negative symptoms may provide knowledge with potential diagnostic and functional relevance that can guide treatment. Two exploratory factor analyses (EFA) were conducted to reveal the underlying dimensions of negative and positive symptoms using the Positive and Negative Syndrome Scale (PANSS), the Scale for the Assessment of Positive Symptoms & Negative Symptoms (SAPS/SANS) and the Autism Diagnostic Observation Schedule-Generic (ADOS-G). Three factors emerged from the negative symptom EFA (70.5 % variance): NF1) Expressive Negative; NF2) Experiential Negative; and NF3) Preoccupation, Absorption & Expressive Affective Flattening. Three positive factors emerged (68.6 % variance): PF1) Hallucinations-Delusions; PF2) Grandiosity; and PF3) Thought Disorder-ADOS positive Symptoms. SZ showed higher PF1 scores, and ASD had higher PF3 scores. No differences between groups were observed in the negative factors. Across groups, all negative factors were inversely associated with quality of life. Only NF1 and NF2 and PF1 were detrimentally related to social functioning. A discriminant function analysis using all factors classified correctly 84.4 % of participants, with PF1, NF1 followed by NF2 being the best predictors of diagnosis. Expressive negative followed by Experiential negative symptoms are of diagnostic value independent of and beyond SZ-related positive symptoms and are related with detrimental functioning. Findings confirm the need to distinctively target negative symptoms, and specific SZ-related and ASD-related positive symptoms, and especially the use of several assessment tools for diagnostic classification.

Intrinsic neural timescales in autism spectrum disorder and schizophrenia. A replication and direct comparison study.

Intrinsic neural timescales (INT) reflect the duration for which brain areas store information. A posterior-anterior hierarchy of increasingly longer INT has been revealed in both typically developed individuals (TD), as well as persons diagnosed with autism spectrum disorder (ASD) and schizophrenia (SZ), though INT are, overall, shorter in both patient groups. In the present study, we aimed to replicate previously reported group differences by comparing INT of TD to ASD and SZ. We partially replicated the previously reported result, showing reduced INT in the left lateral occipital gyrus and the right post-central gyrus in SZ compared to TD. We also directly compared the INT of the two patient groups and found that these same two areas show significantly reduced INT in SZ compared to ASD. Previously reported correlations between INT and symptom severity were not replicated in the current project. Our findings serve to circumscribe the brain areas that can potentially play a determinant role in observed sensory peculiarities in ASD and SZ.

Personality as a mediator of autistic traits and internalizing symptoms in two community samples.

BACKGROUND: Autism spectrum disorder (ASD) is characterized by deficits in social functioning and is comorbid with internalizing disorders and symptoms. While personality is associated with these symptoms and social functioning in non-ASD samples, its role mediating the relationship between ASD traits and internalizing symptoms is not clear. METHODS: We studied the mediating effect of personality on the correlations between ASD traits and internalizing symptoms (i.e., depression, anxiety, stress) in two samples. Additionally, we explored the moderating effect of gender. Analyses were applied to a small (Study 1; N = 101) undergraduate sample. A broader sample recruited via an online crowdsourcing platform (Study 2; N = 371) was used to validate the results. RESULTS: Study 1's mediation analyses revealed that neuroticism was the only significant mediator. Study 2 replicated these results by finding extraversion to be an additional mediator for anxiety and extraversion, openness, and agreeableness as additional mediators for stress. Moderation analyses revealed that gender was never a significant moderator. CONCLUSIONS: These results support the effects of personality on the relationship between autism traits and internalizing symptoms. Future research should explore these effects in clinical samples to better understand the role of personality in symptomatology and the need to address it as part of intervention.

Autistic Traits Moderate Reappraisal Success for Depression and Anxiety Symptoms.

Cognitive reappraisal is associated with reduced emotional distress; however, little is known about the nature of this relationship in autism. This study tested whether autistic traits moderate reappraisal success (i.e., the negative correlation between reappraisal use and emotional symptom severity). Emotional symptoms were assessed using measures of depression, anxiety, and stress. It was hypothesized that more severe autistic traits would be associated with weaker reappraisal success across all scales. Data were collected from 377 adults using an on-line survey. Structural equation models found moderation effects for depression and anxiety, but not stress. Contrary to hypotheses, more severe autistic traits were associated with stronger reappraisal success. These preliminary results support including reappraisal in emotion regulation treatments for individuals with autistic traits.

Predictors of social functioning and quality of life in schizophrenia and autism spectrum disorder.

Schizophrenia (SZ) and Autism Spectrum Disorder (ASD) show overlap in social cognitive and functioning impairments. Proposed predictors of social functioning (SF) and quality of life (QL) have been symptom severity, IQ and social cognition. Empathy has rarely been compared between ASD and SZ and its predictive power on functional outcomes is unclear. We investigated general, affective, and cognitive empathy in 46 SZ, 30 ASD and 51 healthy controls (HC) and examined their relationship to SF and QL in addition to IQ and symptoms. SZ and ASD shared deficits in general and cognitive empathy, and personal distress, but only SZ showed deficits in affective empathy. Both groups showed lower performance-based empathy scores and only ASD showed slower responses compared to HC. Negative symptoms predicted QL in both groups, the more negative symptoms the worse QL (ASD t=-3.22; SZ t= -3.43; p<0.01), and only in ASD, IQ predicted QL, the higher the IQ the higher QL (t = 2.1; p<0.05). In ASD only, negative symptoms predicted SF, the greater negative symptoms the worse SF (t=-3.45; p<0.01), and communication deficits predicted SF, the higher deficits, the higher SF (t = 2.9; p<0.01). Negative symptoms but not empathy were the shared predictors of functioning across ASD and SZ.

Effects of weather and season on human brain volume.

We present an exploratory cross-sectional analysis of the effect of season and weather on Freesurfer-derived brain volumes from a sample of 3,279 healthy individuals collected on two MRI scanners in Hartford, CT, USA over a 15 year period. Weather and seasonal effects were analyzed using a single linear regression model with age, sex, motion, scan sequence, time-of-day, month of the year, and the deviation from average barometric pressure, air temperature, and humidity, as covariates. FDR correction for multiple comparisons was applied to groups of non-overlapping ROIs. Significant negative relationships were found between the left- and right- cerebellum cortex and pressure (t = -2.25, p = 0.049; t = -2.771, p = 0.017). Significant positive relationships were found between left- and right- cerebellum cortex and white matter between the comparisons of January/June and January/September. Significant negative relationships were found between several subcortical ROIs for the summer months compared to January. An opposing effect was observed between the supra- and infra-tentorium, with opposite effect directions in winter and summer. Cohen's d effect sizes from monthly comparisons were similar to those reported in recent psychiatric big-data publications, raising the possibility that seasonal changes and weather may be confounds in large cohort studies. Additionally, changes in brain volume due to natural environmental variation have not been reported before and may have implications for weather-related and seasonal ailments.

Cortical and subcortical brain structure in generalized anxiety disorder: findings from 28 research sites in the ENIGMA-Anxiety Working Group.

The goal of this study was to compare brain structure between individuals with generalized anxiety disorder (GAD) and healthy controls. Previous studies have generated inconsistent findings, possibly due to small sample sizes, or clinical/analytic heterogeneity. To address these concerns, we combined data from 28 research sites worldwide through the ENIGMA-Anxiety Working Group, using a single, pre-registered mega-analysis. Structural magnetic resonance imaging data from children and adults (5-90 years) were processed using FreeSurfer. The main analysis included the regional and vertex-wise cortical thickness, cortical surface area, and subcortical volume as dependent variables, and GAD, age, age-squared, sex, and their interactions as independent variables. Nuisance variables included IQ, years of education, medication use, comorbidities, and global brain measures. The main analysis (1020 individuals with GAD and 2999 healthy controls) included random slopes per site and random intercepts per scanner. A secondary analysis (1112 individuals with GAD and 3282 healthy controls) included fixed slopes and random intercepts per scanner with the same variables. The main analysis showed no effect of GAD on brain structure, nor interactions involving GAD, age, or sex. The secondary analysis showed increased volume in the right ventral diencephalon in male individuals with GAD compared to male healthy controls, whereas female individuals with GAD did not differ from female healthy controls. This mega-analysis combining worldwide data showed that differences in brain structure related to GAD are small, possibly reflecting heterogeneity or those structural alterations are not a major component of its pathophysiology.

Abnormal functional connectivity of default mode sub-networks in autism spectrum disorder patients.

Autism spectrum disorders (ASDs) are characterized by deficits in social and communication processes. Recent data suggest that altered functional connectivity (FC), i.e. synchronous brain activity, might contribute to these deficits. Of specific interest is the FC integrity of the default mode network (DMN), a network active during passive resting states and cognitive processes related to social deficits seen in ASD, e.g. Theory of Mind. We investigated the role of altered FC of default mode sub-networks (DM-SNs) in 16 patients with high-functioning ASD compared to 16 matched healthy controls of short resting fMRI scans using independent component analysis (ICA). ICA is a multivariate data-driven approach that identifies temporally coherent networks, providing a natural measure of FC. Results show that compared to controls, patients showed decreased FC between the precuneus and medial prefrontal cortex/anterior cingulate cortex, DMN core areas, and other DM-SNs areas. FC magnitude in these regions inversely correlated with the severity of patients' social and communication deficits as measured by the Autism Diagnostic Observational Schedule and the Social Responsiveness Scale. Importantly, supplemental analyses suggest that these results were independent of treatment status. These results support the hypothesis that DM-SNs under-connectivity contributes to the core deficits seen in ASD. Moreover, these data provide further support for the use of data-driven analysis with resting-state data for illuminating neural systems that differ between groups. This approach seems especially well suited for populations where compliance with and performance of active tasks might be a challenge, as it requires minimal cooperation.