Dissecting structural connectivity of the left and right inferior frontal cortex in children who stutter.

Inferior frontal cortex pars opercularis (IFCop) features a distinct cerebral dominance and vast functional heterogeneity. Left and right IFCop are implicated in developmental stuttering. Weak left IFCop connections and divergent connectivity of hyperactive right IFCop regions have been related to impeded speech. Here, we reanalyzed diffusion magnetic resonance imaging data from 83 children (41 stuttering). We generated connection probability maps of functionally segregated area 44 parcels and calculated hemisphere-wise analyses of variance. Children who stutter showed reduced connectivity of executive, rostral-motor, and caudal-motor corticostriatal projections from the left IFCop. We discuss this finding in the context of tracing studies from the macaque area 44, which leads to the need to reconsider current models of speech motor control. Unlike the left, the right IFCop revealed increased connectivity of the inferior posterior ventral parcel and decreased connectivity of the posterior dorsal parcel with the anterior insula, particularly in stuttering boys. This divergent connectivity pattern in young children adds to the debate on potential core deficits in stuttering and challenges the theory that right hemisphere differences might exclusively indicate compensatory changes that evolve from lifelong exposure. Instead, early right prefrontal connectivity differences may reflect additional brain signatures of aberrant cognition-emotion-action influencing speech motor control.

Differentiated nomological networks of internalizing, externalizing, and the general factor of psychopathology ('p factor') in emerging adolescence in the ABCD study.

BACKGROUND: Structural models of psychopathology consistently identify internalizing (INT) and externalizing (EXT) specific factors as well as a superordinate factor that captures their shared variance, the p factor. Questions remain, however, about the meaning of these data-driven dimensions and the interpretability and distinguishability of the larger nomological networks in which they are embedded. METHODS: The sample consisted of 10 645 youth aged 9-10 years participating in the multisite Adolescent Brain and Cognitive Development (ABCD) Study. p, INT, and EXT were modeled using the parent-rated Child Behavior Checklist (CBCL). Patterns of associations were examined with variables drawn from diverse domains including demographics, psychopathology, temperament, family history of substance use and psychopathology, school and family environment, and cognitive ability, using instruments based on youth-, parent-, and teacher-report, and behavioral task performance. RESULTS: p exhibited a broad pattern of statistically significant associations with risk variables across all domains assessed, including temperament, neurocognition, and social adversity. The specific factors exhibited more domain-specific patterns of associations, with INT exhibiting greater fear/distress and EXT exhibiting greater impulsivity. CONCLUSIONS: In this largest study of hierarchical models of psychopathology to date, we found that p, INT, and EXT exhibit well-differentiated nomological networks that are interpretable in terms of neurocognition, impulsivity, fear/distress, and social adversity. These networks were, in contrast, obscured when relying on the a priori Internalizing and Externalizing dimensions of the CBCL scales. Our findings add to the evidence for the validity of p, INT, and EXT as theoretically and empirically meaningful broad psychopathology liabilities.

Boost in Test-Retest Reliability in Resting State fMRI with Predictive Modeling.

Recent studies found low test-retest reliability in functional magnetic resonance imaging (fMRI), raising serious concerns among researchers, but these studies mostly focused on the reliability of individual fMRI features (e.g., individual connections in resting state connectivity maps). Meanwhile, neuroimaging researchers increasingly employ multivariate predictive models that aggregate information across a large number of features to predict outcomes of interest, but the test-retest reliability of predicted outcomes of these models has not previously been systematically studied. Here we apply 10 predictive modeling methods to resting state connectivity maps from the Human Connectome Project dataset to predict 61 outcome variables. Compared with mean reliability of individual resting state connections, we find mean reliability of the predicted outcomes of predictive models is substantially higher for all 10 modeling methods assessed. Moreover, improvement was consistently observed across all scanning and processing choices (i.e., scan lengths, censoring thresholds, volume- vs. surface-based processing). For the most reliable methods, the reliability of predicted outcomes was mostly, though not exclusively, in the "good" range (above 0.60). Finally, we identified three mechanisms that help to explain why predicted outcomes of predictive models have higher reliability than individual imaging features. We conclude that researchers can potentially achieve higher test-retest reliability by making greater use of predictive models.

Prediction of neurocognition in youth from resting state fMRI.

Difficulties with higher-order cognitive functions in youth are a potentially important vulnerability factor for the emergence of problematic behaviors and a range of psychopathologies. This study examined 2013 9-10 year olds in the first data release from the Adolescent Brain Cognitive Development 21-site consortium study in order to identify resting state functional connectivity patterns that predict individual-differences in three domains of higher-order cognitive functions: General Ability, Speed/Flexibility, and Learning/Memory. For General Ability scores in particular, we observed consistent cross-site generalizability, with statistically significant predictions in 14 out of 15 held-out sites. These results survived several tests for robustness including replication in split-half analysis and in a low head motion subsample. We additionally found that connectivity patterns involving task control networks and default mode network were prominently implicated in predicting differences in General Ability across participants. These findings demonstrate that resting state connectivity can be leveraged to produce generalizable markers of neurocognitive functioning. Additionally, they highlight the importance of task control-default mode network interconnections as a major locus of individual differences in cognitive functioning in early adolescence.

Toward a "treadmill test" for cognition: Improved prediction of general cognitive ability from the task activated brain.

General cognitive ability (GCA) refers to a trait-like ability that contributes to performance across diverse cognitive tasks. Identifying brain-based markers of GCA has been a longstanding goal of cognitive and clinical neuroscience. Recently, predictive modeling methods have emerged that build whole-brain, distributed neural signatures for phenotypes of interest. In this study, we employ a predictive modeling approach to predict GCA based on fMRI task activation patterns during the N-back working memory task as well as six other tasks in the Human Connectome Project dataset (n = 967), encompassing 15 task contrasts in total. We found tasks are a highly effective basis for prediction of GCA: The 2-back versus 0-back contrast achieved a 0.50 correlation with GCA scores in 10-fold cross-validation, and 13 out of 15 task contrasts afforded statistically significant prediction of GCA. Additionally, we found that task contrasts that produce greater frontoparietal activation and default mode network deactivation-a brain activation pattern associated with executive processing and higher cognitive demand-are more effective in the prediction of GCA. These results suggest a picture analogous to treadmill testing for cardiac function: Placing the brain in a more cognitively demanding task state significantly improves brain-based prediction of GCA.

Associations between resting-state functional connectivity and treatment response in a randomized clinical trial for posttraumatic stress disorder.

BACKGROUND: Alterations in resting-state functional connectivity (rsFC) have been reported in posttraumatic stress disorder (PTSD). Here, we examined pre- and post-treatment rsFC during a randomized clinical trial to characterize alterations and examine predictors of treatment response. METHODS: Sixty-four combat veterans with PTSD were randomly assigned to prolonged exposure (PE) plus placebo, sertraline plus enhanced medication management, or PE plus sertraline. Symptom assessment and resting-state functional magnetic resonance imaging (fMRI) scans occurred before and after treatment. Twenty-nine trauma-exposed combat veterans without PTSD served as a control group at intake. Seed-based and region of interest (ROI)-to-ROI connectivities, as well as an exploratory connectome-based approach were used to analyze rsFC patterns. Based on previously reported findings, analyses focused on Salience Network (SN) and Default-Mode Network (DMN). RESULTS: At intake, patients with PTSD showed greater DMN-dorsal attention network (DAN) connectivity (between ventromedial prefrontal cortex and superior parietal lobule; family-wise error corrected p = .011), greater SN-DAN connectivity (between insula and middle frontal gyrus; corrected p = .003), and a negative correlation between re-experiencing symptoms and within-DMN connectivity (between posterior cingulate cortex (PCC) and middle temporal gyrus; corrected p < .001). We also found preliminary evidence for associations between rsFC and treatment response. Specifically, high responders (≥50% PTSD symptom improvement), compared with low responders, had greater SN-DMN segregation (i.e., less pre-treatment amygdala-PCC connectivity; p = .011) and lower pre-treatment global centrality (p = .042). CONCLUSIONS: Our findings suggest neural abnormalities in PTSD and may inform future research examining neural biomarkers of PTSD treatment response.

Lag in maturation of the brain's intrinsic functional architecture in attention-deficit/hyperactivity disorder.

Attention-deficit/hyperactivity disorder (ADHD) is among the most common psychiatric disorders of childhood, and there is great interest in understanding its neurobiological basis. A prominent neurodevelopmental hypothesis proposes that ADHD involves a lag in brain maturation. Previous work has found support for this hypothesis, but examinations have been limited to structural features of the brain (e.g., gray matter volume or cortical thickness). More recently, a growing body of work demonstrates that the brain is functionally organized into a number of large-scale networks, and the connections within and between these networks exhibit characteristic patterns of maturation. In this study, we investigated whether individuals with ADHD (age 7.2-21.8 y) exhibit a lag in maturation of the brain's developing functional architecture. Using connectomic methods applied to a large, multisite dataset of resting state scans, we quantified the effect of maturation and the effect of ADHD at more than 400,000 connections throughout the cortex. We found significant and specific maturational lag in connections within default mode network (DMN) and in DMN interconnections with two task positive networks (TPNs): frontoparietal network and ventral attention network. In particular, lag was observed within the midline core of the DMN, as well as in DMN connections with right lateralized prefrontal regions (in frontoparietal network) and anterior insula (in ventral attention network). Current models of the pathophysiology of attention dysfunction in ADHD emphasize altered DMN-TPN interactions. Our finding of maturational lag specifically in connections within and between these networks suggests a developmental etiology for the deficits proposed in these models.

The typical development of posterior medial frontal cortex function and connectivity during task control demands in youth 8-19years old.

To characterize the development of neural substrate for interference processing and task control, this study examined both linear and non-linear effects of age on activation and connectivity during an interference task designed to engage the posterior medial frontal cortex (pMFC). Seventy-two youth, ages 8-19years, performed the Multi-Source Interference Task (MSIT) during functional magnetic resonance imaging (fMRI). With increasing age, overall performance across high-interference incongruent and low-interference congruent trials became faster and more accurate. Effects of age on activation to interference- (incongruent versus congruent conditions), error- (errors versus correct trials during the incongruent condition) and overall task-processing (incongruent plus congruent conditions, relative to implicit baseline) were tested in whole-brain voxel-wise analyses. Age differentially impacted activation to overall task processing in discrete sub-regions of the pMFC: activation in the pre-supplementary motor area (pre-SMA) decreased with age, whereas activation in the dorsal anterior cingulate cortex (dACC) followed a non-linear (i.e., U-shaped) pattern in relation to age. In addition, connectivity of pre-SMA with anterior insula/frontal operculum (AI/FO) increased with age. These findings suggest differential development of pre-SMA and dACC sub-regions within the pMFC. Moreover, as children age, decreases in pre-SMA activation may couple with increases in pre-SMA-AI/FO connectivity to support gains in processing speed in response to demands for task control.

White matter neuroanatomical differences in young children who stutter.

The ability to express thoughts through fluent speech production is a most human faculty, one that is often taken for granted. Stuttering, which disrupts the smooth flow of speech, affects 5% of preschool-age children and 1% of the general population, and can lead to significant communication difficulties and negative psychosocial consequences throughout one's lifetime. Despite the fact that symptom onset typically occurs during early childhood, few studies have yet examined the possible neural bases of developmental stuttering during childhood. Here we present a diffusion tensor imaging study that examined white matter measures reflecting neuroanatomical connectivity (fractional anisotropy) in 77 children [40 controls (20 females), 37 who stutter (16 females)] between 3 and 10 years of age. We asked whether previously reported anomalous white matter measures in adults and older children who stutter that were found primarily in major left hemisphere tracts (e.g. superior longitudinal fasciculus) are also present in younger children who stutter. All children exhibited normal speech, language, and cognitive development as assessed through a battery of assessments. The two groups were matched in chronological age and socioeconomic status. Voxel-wise whole brain comparisons using tract-based spatial statistics and region of interest analyses of fractional anisotropy were conducted to examine white matter changes associated with stuttering status, age, sex, and stuttering severity. Children who stutter exhibited significantly reduced fractional anisotropy relative to controls in white matter tracts that interconnect auditory and motor structures, corpus callosum, and in tracts interconnecting cortical and subcortical areas. In contrast to control subjects, fractional anisotropy changes with age were either stagnant or showed dissociated development among major perisylvian brain areas in children who stutter. These results provide first glimpses into the neuroanatomical bases of early childhood stuttering, and possible white matter developmental changes that may lead to recovery versus persistent stuttering. The white matter changes point to possible structural connectivity deficits in children who stutter, in interrelated neural circuits that enable skilled movement control through efficient sensorimotor integration and timing of movements.

Cannabinoid modulation of prefrontal-limbic activation during fear extinction learning and recall in humans.

Pre-extinction administration of Δ9-tetrahydrocannibinol (THC) facilitates recall of extinction in healthy humans, and evidence from animal studies suggest that this likely occurs via enhancement of the cannabinoid system within the ventromedial prefrontal cortex (vmPFC) and hippocampus (HIPP), brain structures critical to fear extinction. However, the effect of cannabinoids on the underlying neural circuitry of extinction memory recall in humans has not been demonstrated. We conducted a functional magnetic resonance imaging (fMRI) study using a randomized, double-blind, placebo-controlled, between-subjects design (N=14/group) coupled with a standard Pavlovian fear extinction paradigm and an acute pharmacological challenge with oral dronabinol (synthetic THC) in healthy adult volunteers. We examined the effects of THC on vmPFC and HIPP activation when tested for recall of extinction learning 24 h after extinction learning. Compared to subjects who received placebo, participants who received THC showed increased vmPFC and HIPP activation to a previously extinguished conditioned stimulus (CS+E) during extinction memory recall. This study provides the first evidence that pre-extinction administration of THC modulates prefrontal-limbic circuits during fear extinction in humans and prompts future investigation to test if cannabinoid agonists can rescue or correct the impaired behavioral and neural function during extinction recall in patients with PTSD. Ultimately, the cannabinoid system may serve as a promising target for innovative intervention strategies (e.g. pharmacological enhancement of exposure-based therapy) in PTSD and other fear learning-related disorders.

Altered activation of the rostral anterior cingulate cortex in the context of emotional face distractors in children and adolescents with anxiety disorders.

BACKGROUND: Pediatric and adult anxiety disorder patients exhibit attention bias to threat and difficulty disengaging attention away from threat. Cognitive frameworks suggest that these patterns are associated with hyperactivation of regions associated with detecting threat, such as the amygdala, and hypoactivation of regions associated with regulating attention, including the lateral prefrontal cortex and rostral anterior cingulate cortex (rACC). The aim of the present study was to examine the neural correlates of these processes in children and adolescents with anxiety disorders. METHODS: Participants with an anxiety disorder 7 to 19 years old (n = 34) and typically developing controls (n = 35) underwent fMRI scanning. During scanning, they completed a task with conditions that manipulated whether participants were instructed to match emotional faces (direct emotion processing) or match shapes in the context of emotional face distractors (attentional control). RESULTS: Results revealed a significant difference in rACC activation during shape versus face matching, with controls evidencing greater rACC activation relative to patients. CONCLUSIONS: This study identifies abnormalities in rACC activation as a potential neural mediator associated with pediatric anxiety disorders, which can inform frameworks for understanding their development and treatment.

Focal and aberrant prefrontal engagement during emotion regulation in veterans with posttraumatic stress disorder.

BACKGROUND: Collectively, functional neuroimaging studies implicate frontal-limbic dysfunction in the pathophysiology of posttraumatic stress disorder (PTSD), as reflected by altered amygdala reactivity and deficient prefrontal responses. These neural patterns are often elicited by social signals of threat (fearful/angry faces) and traumatic reminders (combat sounds, script-driven imagery). Although PTSD can be conceptualized as a disorder of emotion dysregulation, few studies to date have directly investigated the neural correlates of volitional attempts at regulating negative affect in PTSD. METHODS: Using functional magnetic resonance imaging and a well-validated task involving cognitive regulation of negative affect via reappraisal and known to engage prefrontal cortical regions, the authors compared brain activation in veterans with PTSD (n = 21) and without PTSD (n = 21, combat-exposed controls/CEC), following military combat trauma experience during deployments in Afghanistan or Iraq. The primary outcome measure was brain activation during cognitive reappraisal (i.e., decrease negative affect) as compared to passive viewing (i.e., maintain negative affect) of emotionally evocative content of aversive images RESULTS: The subjects in both groups reported similar successful reduction in negative affect following reappraisal. The PTSD group engaged the dorsolateral prefrontal cortex (dlPFC) during cognitive reappraisal, albeit to a lesser extent than the CEC group. Although the amygdala was engaged in both groups during passive viewing of aversive images, neither group exhibited attenuation of amygdala activation during cognitive reappraisal. CONCLUSIONS: Veterans with combat-related PTSD showed less recruitment of the dlPFC involved in cognitive reappraisal, suggesting focal and aberrant neural activation during volitional, self-regulation of negative affective states.

Dynamic changes in amygdala activation and functional connectivity in children and adolescents with anxiety disorders.

Anxiety disorders are associated with abnormalities in amygdala function and prefrontal cortex-amygdala connectivity. The majority of functional magnetic resonance imaging studies have examined mean group differences in amygdala activation or connectivity in children and adolescents with anxiety disorders relative to controls, but emerging evidence suggests that abnormalities in amygdala function are dependent on the timing of the task and may vary across the course of a scanning session. The goal of the present study was to extend our knowledge of the dynamics of amygdala dysfunction by examining whether changes in amygdala activation and connectivity over scanning differ in pediatric anxiety disorder patients relative to typically developing controls during an emotion processing task. Examining changes in activation over time allows for a comparison of how brain function differs during initial exposure to novel stimuli versus more prolonged exposure. Participants included 34 anxiety disorder patients and 19 controls 7 to 19 years old. Participants performed an emotional face-matching task during functional magnetic resonance imaging scanning, and the task was divided into thirds in order to examine change in activation over time. Results demonstrated that patients exhibited an abnormal pattern of amygdala activation characterized by an initially heightened amygdala response relative to controls at the beginning of scanning, followed by significant decreases in activation over time. In addition, controls evidenced greater context-modulated prefrontal cortex-amygdala connectivity during the beginning of scanning relative to patients. These results indicate that differences in emotion processing between the groups vary from initial exposure to novel stimuli relative to more prolonged exposure. Implications are discussed regarding how this pattern of neural activation may relate to altered early-occurring or anticipatory emotion-regulation strategies and maladaptive later-occurring strategies in children and adolescents with anxiety disorders.

Flexible adaptation of task-positive brain networks predicts efficiency of evidence accumulation.

Efficiency of evidence accumulation (EEA), an individual's ability to selectively gather goal-relevant information to make adaptive choices, is thought to be a key neurocomputational mechanism associated with cognitive functioning and transdiagnostic risk for psychopathology. However, the neural basis of individual differences in EEA is poorly understood, especially regarding the role of largescale brain network dynamics. We leverage data from 5198 participants from the Human Connectome Project and Adolescent Brain Cognitive Development Study to demonstrate a strong association between EEA and flexible adaptation to cognitive demand in the "task-positive" frontoparietal and dorsal attention networks. Notably, individuals with higher EEA displayed divergent task-positive network activation across n-back task conditions: higher activation under high cognitive demand (2-back) and lower activation under low demand (0-back). These findings suggest that brain networks' flexible adaptation to cognitive demands is a key neural underpinning of EEA.

Data-driven, generalizable prediction of adolescent sleep disturbances in the multisite Adolescent Brain Cognitive Development Study.

STUDY OBJECTIVES: Sleep disturbances are common in adolescence and associated with a host of negative outcomes. Here, we assess associations between multifaceted sleep disturbances and a broad set of psychological, cognitive, and demographic variables using a data-driven approach, canonical correlation analysis (CCA). METHODS: Baseline data from 9093 participants from the Adolescent Brain Cognitive Development (ABCD) Study were examined using CCA, a multivariate statistical approach that identifies many-to-many associations between two sets of variables by finding combinations for each set of variables that maximize their correlation. We combined CCA with leave-one-site-out cross-validation across ABCD sites to examine the robustness of results and generalizability to new participants. The statistical significance of canonical correlations was determined by non-parametric permutation tests that accounted for twin, family, and site structure. To assess the stability of the associations identified at baseline, CCA was repeated using 2-year follow-up data from 4247 ABCD Study participants. RESULTS: Two significant sets of associations were identified: (1) difficulty initiating and maintaining sleep and excessive daytime somnolence were strongly linked to nearly all domains of psychopathology (r2 = 0.36, p < .0001); (2) sleep breathing disorders were linked to BMI and African American/black race (r2 = 0.08, p < .0001). These associations generalized to unseen participants at all 22 ABCD sites and were replicated using 2-year follow-up data. CONCLUSIONS: These findings underscore interwoven links between sleep disturbances in early adolescence and psychological, social, and demographic factors.

Socioeconomic resources in youth are linked to divergent patterns of network integration/segregation across the brain's transmodal axis.

Socioeconomic resources (SER) calibrate the developing brain to the current context, which can confer or attenuate risk for psychopathology across the lifespan. Recent multivariate work indicates that SER levels powerfully relate to intrinsic functional connectivity patterns across the entire brain. Nevertheless, the neuroscientific meaning of these widespread neural differences remains poorly understood, despite its translational promise for early risk identification, targeted intervention, and policy reform. In the present study, we leverage graph theory to precisely characterize multivariate and univariate associations between SER across household and neighborhood contexts and the intrinsic functional architecture of brain regions in 5,821 youth (9-10 years) from the Adolescent Brain Cognitive Development Study. First, we establish that decomposing the brain into profiles of integration and segregation captures more than half of the multivariate association between SER and functional connectivity with greater parsimony (100-fold reduction in number of features) and interpretability. Second, we show that the topological effects of SER are not uniform across the brain; rather, higher SER levels are associated with greater integration of somatomotor and subcortical systems, but greater segregation of default mode, orbitofrontal, and cerebellar systems. Finally, we demonstrate that topological associations with SER are spatially patterned along the unimodal-transmodal gradient of brain organization. These findings provide critical interpretive context for the established and widespread associations between SER and brain organization. This study highlights both higher-order and somatomotor networks that are differentially implicated in environmental stress, disadvantage, and opportunity in youth.

Functional brain connectivity predictors of prospective substance use initiation and their environmental correlates.

Background: Early substance use initiation (SUI) places youth at substantially higher risk for later substance use disorders. Furthermore, adolescence is a critical period for the maturation of brain networks, the pace and magnitude of which are susceptible to environmental influences and may shape risk for SUI. Methods: We examined whether patterns of functional brain connectivity during rest (rsFC), measured longitudinally in pre-and-early adolescence, can predict future SUI. In an independent sub-sample, we also tested whether these patterns are associated with key environmental factors, specifically neighborhood pollution and socioeconomic dimensions. We utilized data from the Adolescent Brain Cognitive Development (ABCD) Study®. SUI was defined as first-time use of at least one full dose of alcohol, nicotine, cannabis, or other drugs. We created a control group (N = 228) of participants without SUI who were matched with the SUI group (N = 233) on age, sex, race/ethnicity, and parental income and education. Results: Multivariate analysis showed that whole-brain rsFC prior to SUI during 9-10 and 11-12 years of age successfully differentiated the prospective SUI and control groups. This rsFC signature was expressed more at older ages in both groups, suggesting a pattern of accelerated maturation in the SUI group in the years prior to SUI. In an independent sub-sample (N = 2,854) and adjusted for family socioeconomic factors, expression of this rsFC pattern was associated with higher pollution, but not neighborhood disadvantage. Conclusion: Brain functional connectivity patterns in early adolescence that are linked to accelerated maturation and environmental exposures can predict future SUI in youth.

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.

Aberrant amygdala-frontal cortex connectivity during perception of fearful faces and at rest in generalized social anxiety disorder.

BACKGROUND: Generalized social anxiety disorder (gSAD) is characterized by exaggerated amygdala reactivity to social signals of threat, but if and how the amygdala interacts with functionally and anatomically connected prefrontal cortex (PFC) remains largely unknown. Recent evidence points to aberrant amygdala connectivity to medial PFC in gSAD at rest, but it is difficult to attribute functional relevance without the context of threat processing. Here, we address this by studying amygdala-frontal cortex connectivity during viewing of fearful faces and at rest in gSAD patients. METHODS: Twenty patients with gSAD and 17 matched healthy controls (HCs) participated in functional magnetic resonance imaging of an emotional face matching task and a resting state task. Functional connectivity and psychophysiological interaction analysis were used to assess amygdala connectivity. RESULTS: Compared to HCs, gSAD patients exhibited less connectivity between amygdala and the rostral anterior cingulate cortex (ACC) and dorsolateral prefrontal cortex (DLPFC) while viewing fearful faces. gSAD patients also showed less connectivity between amygdala and rostral ACC at rest in the absence of fearful faces. DLPFC connectivity was negatively correlated with LSASFear (where LSAS is Liebowitz Social Anxiety Scale). CONCLUSIONS: Task and rest paradigms provide unique and important information about discrete and overlapping functional networks. In particular, amygdala coupling to DLPFC may be a phasic abnormality, emerging only in the presence of a social predictor of threat, whereas amygdala coupling to the rostral ACC may reflect both phasic and tonic abnormalities. These findings prompt further studies to better delineate intrinsic and externally evoked brain connectivity in anxiety and depression in relation to amygdala dysfunction.