Assaultive violence exposure during childhood is a significant risk factor for posttraumatic stress disorder (PTSD). The purpose of the present study was to characterize the relationships of assault and PTSD severity with the organization of large-scale networks identified during emotion processing. Adolescent girls aged 12–16 with (N=15) and without (N=15) histories of assault underwent fMRI while engaged in a task that presented images of fearful or neutral facial expressions. Independent component analysis (ICA) identified a frontocingulate network, a frontoparietal network, and a default mode network. Assault exposure was associated with significantly greater activation of the frontocingulate network for fear versus neutral faces. Within the frontocingulate network, PTSD severity was associated with weakened functional connectivity between the left amygdala and the perigenual anterior cingulate. Within the frontoparietal network, assaulted girls demonstrated weakened connectivity of the premotor cortex with the right middle frontal gyrus. Within the default mode network, assault exposure and PTSD severity were associated with strengthening functional connectivity of the parahippocampus with the medial and lateral PFC, respectively. Individual differences in functional connections within the frontocingulate network and frontoparietal network among the assaulted group were strongly associated with caregiver-rated family disengagement. These results demonstrate associations between assault and PTSD symptoms on the functional organization of large-scale frontoparietal, frontocingulate, and default mode networks during emotion processing. The relationship with caregiver-rated family disengagement suggests the impact of family support on the neural processing correlates of assault and PTSD symptoms.

Background: Repeated exposure to the traumatic memory (RETM) is a common component of treatments for posttraumatic stress disorder (PTSD). This treatment is based on a fear extinction model; however, the degree to which this treatment actually engages and modifies neural networks mediating fear extinction is unknown. Therefore, the purpose of the current exploratory study was to define the dynamic changes in neural processing networks while participants completed a novel adaptation of RETM.

Interoception is theorized to be an important process mediating substance use disorders, and the insular cortex is recognized as a core neural region supporting interoception. The purpose of this study was to compare the integration of the insular cortex into prefrontal-related resting-state networks between individuals with cocaine dependence and healthy controls. 41 participants with cocaine dependence and 19 control participants underwent a resting-state 3T fMRI scan. Individuals with cocaine dependence demonstrated altered functional connectivity of the insular cortex, predominantly the right insular cortex, with all eight prefrontal-related resting-state networks identified through Independent Component Analysis (ICA). A conjunction analysis demonstrated that the right insular cortex was the neural region with the highest number of common group differences across the networks. There was no evidence that insular cortex connectivity commonly differed between groups for non-prefrontal-related networks. Further, seed-based functional connectivity analyses extended the network analyses and indicated that cocaine dependence was associated with greater connectivity of the right insula with the dorsomedial PFC, inferior frontal gyrus, and bilateral dlPFC. These data support the hypothesis that cocaine dependence is related to altered functional interactions of the insular cortex with prefrontal networks. The results suggest possible neural mechanisms by which the insular cortex and interoceptive information influence cognitive control and decision-making processes presumably mediated by prefrontal networks in the cocaine dependence process.

Trauma-Focused Cognitive-Behavioral Therapy (TF-CBT) is the gold standard treatment for pediatric PTSD. Nonetheless, clinical outcomes in TF-CBT are highly variable, indicating a need to identify reliable predictors that allow forecasting treatment response. Here, we test the hypothesis that functional neuroimaging correlates of emotion processing predict PTSD symptom reduction during Trauma-Focused Cognitive-Behavioral Therapy (TF-CBT) among adolescent girls with PTSD. Thirty-four adolescent girls with PTSD related to physical or sexual assault were enrolled in TF-CBT, delivered in an approximately 12 session format, in an open trial. Prior to treatment, they were engaged in an implicit threat processing task during 3T fMRI, during which they viewed faces depicting fearful or neutral expressions. Among adolescent girls completing TF-CBT (n=23), slopes of PTSD symptom trajectories during TF-CBT were significantly related to pre-treatment degree of bilateral amygdala activation while viewing fearful vs neutral images. Adolescents with less symptom reduction were characterized by greater amygdala activation to both threat and neutral images (i.e., less threat-safety discrimination), whereas adolescents with greater symptom reduction were characterized by amygdala activation only to threat images. These clinical outcome relationships with pre-treatment bilateral amygdala activation remained when controlling for possible confounding demographic or clinical variables (e.g., concurrent psychotropic medication, comorbid diagnoses). While limited by a lack of a control group, these preliminary results suggest that pre-treatment amygdala reactivity to fear stimuli, a component of neurocircuitry models of PTSD, positively predicts symptom reduction during TF-CBT among * To whom correspondence should be directed: Brain Imaging Research Center, Psychiatric Research Institute, University of Arkansas for Medical Sciences, 4301 W. Markham, #554, Little Rock, AR 72205, jcisler@uams.edu, phone: (501) 526-8343. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Financial DisclosuresAll authors report no financial conflicts of interest. ContributionsBen Sigel and Teresa Kramer were involved in study design, interpretation, and manuscript writing. Karin Vanderzee and Joy Pemberton were data collection, interpretation, and manuscript writing. Sonet Smitherman was involved in study design, data collection, and analysis. Clint Kilts was involved in study design, interpretation, and manuscript writing. Josh Cisler was involved in study design, analysis, interpretation, and manuscript writin...

Cocaine dependence is defined by a loss of inhibitory control over drug use behaviors, mirrored by measurable impairments in laboratory tasks of inhibitory control. The current study tested the hypothesis that deficits in multiple sub-processes of behavioral control are associated with reliable neural processing alterations that define cocaine addiction. While undergoing fMRI, 38 cocaine-dependent men and 27 healthy control men performed a stop-signal task of motor inhibition. An independent component analysis (ICA) on fMRI time courses identified task-related neural networks attributed to motor, visual, cognitive and affective processes. The statistical associations of these components with five different stop-signal task conditions were selected for use in a linear discriminant analysis to define a classifier for cocaine addiction from a subsample of 26 cocaine-dependent men and 18 controls. Leave-one-out cross validation accurately classified 89.5% (39/44; chance accuracy = 26/44 = 59.1%) of subjects (with 84.6% (22/26) sensitivity and 94.4% (17/18) specificity. The remaining 12 cocaine-dependent and 9 control men formed an independent test sample, for which accuracy of the classifier was 81.9% (17/21; chance accuracy = 12/21 = 57.1%) with 75% (9/12) sensitivity and 88.9% (8/9) specificity. The cocaine addiction classification score was significantly correlated with a measure of impulsiveness as well as the duration of cocaine use for cocaine-dependent men. The results of this study support the ability of a pattern of multiple neural network alterations associated with inhibitory motor control to define a binary classifier for cocaine addiction.