Abstract Background Anxiety produced by environmental threats can impair goal-directed processing and is associated with a range of psychiatric disorders, particularly when aversive events occur ...unpredictably. The prefrontal cortex (PFC) is thought to implement controls that minimize performance disruptions from threat-induced anxiety and goal distraction by modulating activity in regions involved in threat detection, such as the amygdala. The inferior frontal gyrus (IFG), orbitofrontal cortex (OFC), and ventromedial PFC (vmPFC) have been linked to the regulation of anxiety during threat exposure. We developed a paradigm to determine if threat-induced anxiety would enhance functional connectivity between the amygdala and IFG, OFC, and vmPFC. Methods Healthy adults performed a computer-gaming style task involving capturing prey and evading predators to optimize monetary rewards while exposed to the threat of unpredictable shock. Psychophysiological recording ( n = 26) and functional magnetic resonance imaging scanning ( n = 17) were collected during the task in separate cohorts. Task-specific changes in functional connectivity with the amygdala were examined using psychophysiological interaction analysis. Results Threat exposure resulted in greater arousal measured by increased skin conductance but did not influence performance (i.e., monetary losses or rewards). Greater functional connectivity between the right amygdala and bilateral IFG, OFC, vmPFC, anterior cingulate cortex, and frontopolar cortex was associated with threat exposure. Conclusions Exposure to unpredictable threat modulates amygdala-PFC functional connectivity that may help maintain performance when experiencing anxiety induced by threat. Our paradigm is well-suited to explore the neural underpinnings of the anxiety response to unpredictable threat in patients with various anxiety disorders.
Many studies report smaller hippocampal and amygdala volumes in posttraumatic stress disorder (PTSD), but findings have not always been consistent. Here, we present the results of a large-scale ...neuroimaging consortium study on PTSD conducted by the Psychiatric Genomics Consortium (PGC)–Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) PTSD Working Group.
We analyzed neuroimaging and clinical data from 1868 subjects (794 PTSD patients) contributed by 16 cohorts, representing the largest neuroimaging study of PTSD to date. We assessed the volumes of eight subcortical structures (nucleus accumbens, amygdala, caudate, hippocampus, pallidum, putamen, thalamus, and lateral ventricle). We used a standardized image-analysis and quality-control pipeline established by the ENIGMA consortium.
In a meta-analysis of all samples, we found significantly smaller hippocampi in subjects with current PTSD compared with trauma-exposed control subjects (Cohen’s d = −0.17, p = .00054), and smaller amygdalae (d = −0.11, p = .025), although the amygdala finding did not survive a significance level that was Bonferroni corrected for multiple subcortical region comparisons (p < .0063).
Our study is not subject to the biases of meta-analyses of published data, and it represents an important milestone in an ongoing collaborative effort to examine the neurobiological underpinnings of PTSD and the brain’s response to trauma.
Posttraumatic stress disorder (PTSD) is considered a disorder of recovery where individuals fail to learn and retain extinction of the traumatic fear response. In maltreated youth, PTSD is common, ...chronic, and associated with comorbidity. Studies of extinction-related structural volumes (amygdala, hippocampus, anterior cingulate cortex (ACC), and ventral medial prefrontal cortex (vmPFC)) and this stress diathesis, in maltreated youth were not previously investigated. In this cross-sectional study, neuroanatomical volumes associated with extinction in maltreated youth with PTSD (N=31), without PTSD (N=32), and in non-maltreated healthy volunteers (n=57) were examined using magnetic resonance imaging. Groups were sociodemographically similar. Participants underwent extensive assessments for strict inclusion/exclusion criteria and DSM-IV disorders. Maltreated youth with PTSD demonstrated decreased right vmPFC volumes compared with both maltreated youth without PTSD and non-maltreated controls. Maltreated youth without PTSD demonstrated larger left amygdala and right hippocampal volumes compared with maltreated youth with PTSD and non-maltreated control youth. PTSD symptoms inversely correlated with right and left hippocampal and left amygdala volumes. Confirmatory masked voxel base morphometry analyses demonstrated greater medial orbitofrontal cortex gray matter intensity in controls than maltreated youth with PTSD. Volumetric results were not influenced by psychopathology or maltreatment variables. We identified volumetric differences in extinction-related structures between maltreated youth with PTSD from those without PTSD. Alterations of the vmPFC may be one mechanism that mediates the pathway from PTSD to comorbidity. Further longitudinal work is needed to determine neurobiological factors related to chronic and persistent PTSD, and to PTSD resilience despite maltreatment.
Large databases of high-resolution structural MR images are being assembled to quantitatively examine the relationships between brain anatomy, disease progression, treatment regimens, and genetic ...influences upon brain structure. Quantifying brain structures in such large databases cannot be practically accomplished by expert neuroanatomists using hand-tracing. Rather, this research will depend upon automated methods that reliably and accurately segment and quantify dozens of brain regions. At present, there is little guidance available to help clinical research groups in choosing such tools. Thus, our goal was to compare the performance of two popular and fully automated tools, FSL/FIRST and FreeSurfer, to expert hand tracing in the measurement of the hippocampus and amygdala. Volumes derived from each automated measurement were compared to hand tracing for percent volume overlap, percent volume difference, across-sample correlation, and 3-D group-level shape analysis. In addition, sample size estimates for conducting between-group studies were computed for a range of effect sizes. Compared to hand tracing, hippocampal measurements with FreeSurfer exhibited greater volume overlap, smaller volume difference, and higher correlation than FIRST, and sample size estimates with FreeSurfer were closer to hand tracing. Amygdala measurement with FreeSurfer was also more highly correlated to hand tracing than FIRST, but exhibited a greater volume difference than FIRST. Both techniques had comparable volume overlap and similar sample size estimates. Compared to hand tracing, a 3-D shape analysis of the hippocampus showed FreeSurfer was more accurate than FIRST, particularly in the head and tail. However, FIRST more accurately represented the amygdala shape than FreeSurfer, which inflated its anterior and posterior surfaces.
The reproducibility crisis in neuroimaging has led to an increased demand for standardized data processing workflows. Within the ENIGMA consortium, we developed HALFpipe (Harmonized Analysis of ...Functional MRI pipeline), an open‐source, containerized, user‐friendly tool that facilitates reproducible analysis of task‐based and resting‐state fMRI data through uniform application of preprocessing, quality assessment, single‐subject feature extraction, and group‐level statistics. It provides state‐of‐the‐art preprocessing using fMRIPrep without the requirement for input data in Brain Imaging Data Structure (BIDS) format. HALFpipe extends the functionality of fMRIPrep with additional preprocessing steps, which include spatial smoothing, grand mean scaling, temporal filtering, and confound regression. HALFpipe generates an interactive quality assessment (QA) webpage to rate the quality of key preprocessing outputs and raw data in general. HALFpipe features myriad post‐processing functions at the individual subject level, including calculation of task‐based activation, seed‐based connectivity, network‐template (or dual) regression, atlas‐based functional connectivity matrices, regional homogeneity (ReHo), and fractional amplitude of low‐frequency fluctuations (fALFF), offering support to evaluate a combinatorial number of features or preprocessing settings in one run. Finally, flexible factorial models can be defined for mixed‐effects regression analysis at the group level, including multiple comparison correction. Here, we introduce the theoretical framework in which HALFpipe was developed, and present an overview of the main functions of the pipeline. HALFpipe offers the scientific community a major advance toward addressing the reproducibility crisis in neuroimaging, providing a workflow that encompasses preprocessing, post‐processing, and QA of fMRI data, while broadening core principles of data analysis for producing reproducible results. Instructions and code can be found at https://github.com/HALFpipe/HALFpipe.
HALFpipe is a user‐friendly software that facilitates reproducible analysis of fMRI data, including preprocessing, single‐subject, and group analysis. It provides state‐of‐the‐art preprocessing using fMRIPrep, but removes the necessity to convert data to the BIDS format. Common resting‐state and task‐based fMRI features can then be calculated on the fly using FSL and Nipype for statistics.
The amygdala is a major structure that orchestrates defensive reactions to environmental threats and is implicated in hypervigilance and symptoms of heightened arousal in posttraumatic stress ...disorder (PTSD). The basolateral and centromedial amygdala (CMA) complexes are functionally heterogeneous, with distinct roles in learning and expressing fear behaviors. PTSD differences in amygdala-complex function and functional connectivity with cortical and subcortical structures remain unclear. Recent military veterans with PTSD (n=20) and matched trauma-exposed controls (n=22) underwent a resting-state fMRI scan to measure task-free synchronous blood-oxygen level dependent activity. Whole-brain voxel-wise functional connectivity of basolateral and CMA seeds was compared between groups. The PTSD group had stronger functional connectivity of the basolateral amygdala (BLA) complex with the pregenual anterior cingulate cortex (ACC), dorsomedial prefrontal cortex, and dorsal ACC than the trauma-exposed control group (p<0.05; corrected). The trauma-exposed control group had stronger functional connectivity of the BLA complex with the left inferior frontal gyrus than the PTSD group (p<0.05; corrected). The CMA complex lacked connectivity differences between groups. We found PTSD modulates BLA complex connectivity with prefrontal cortical targets implicated in cognitive control of emotional information, which are central to explanations of core PTSD symptoms. PTSD differences in resting-state connectivity of BLA complex could be biasing processes in target regions that support behaviors central to prevailing laboratory models of PTSD such as associative fear learning. Further research is needed to investigate how differences in functional connectivity of amygdala complexes affect target regions that govern behavior, cognition, and affect in PTSD.
The development of posttraumatic stress disorder (PTSD) is influenced by genetic factors. Although there have been some replicated candidates, the identification of risk variants for PTSD has lagged ...behind genetic research of other psychiatric disorders such as schizophrenia, autism, and bipolar disorder. Psychiatric genetics has moved beyond examination of specific candidate genes in favor of the genome-wide association study (GWAS) strategy of very large numbers of samples, which allows for the discovery of previously unsuspected genes and molecular pathways. The successes of genetic studies of schizophrenia and bipolar disorder have been aided by the formation of a large-scale GWAS consortium: the Psychiatric Genomics Consortium (PGC). In contrast, only a handful of GWAS of PTSD have appeared in the literature to date. Here we describe the formation of a group dedicated to large-scale study of PTSD genetics: the PGC-PTSD. The PGC-PTSD faces challenges related to the contingency on trauma exposure and the large degree of ancestral genetic diversity within and across participating studies. Using the PGC analysis pipeline supplemented by analyses tailored to address these challenges, we anticipate that our first large-scale GWAS of PTSD will comprise over 10 000 cases and 30 000 trauma-exposed controls. Following in the footsteps of our PGC forerunners, this collaboration-of a scope that is unprecedented in the field of traumatic stress-will lead the search for replicable genetic associations and new insights into the biological underpinnings of PTSD.
In this review, we discuss recent work by the ENIGMA Consortium (http://enigma.ini.usc.edu) – a global alliance of over 500 scientists spread across 200 institutions in 35 countries collectively ...analyzing brain imaging, clinical, and genetic data. Initially formed to detect genetic influences on brain measures, ENIGMA has grown to over 30 working groups studying 12 major brain diseases by pooling and comparing brain data. In some of the largest neuroimaging studies to date – of schizophrenia and major depression – ENIGMA has found replicable disease effects on the brain that are consistent worldwide, as well as factors that modulate disease effects. In partnership with other consortia including ADNI, CHARGE, IMAGEN and others11Abbreviations: ADNI, Alzheimer's Disease Neuroimaging Initiative (http://www.adni-info.org); CHARGE, the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (http://www.chargeconsortium.com); IMAGEN, IMAging GENetics Consortium (http://www.imagen-europe.com)., ENIGMA's genomic screens – now numbering over 30,000 MRI scans – have revealed at least 8 genetic loci that affect brain volumes. Downstream of gene findings, ENIGMA has revealed how these individual variants – and genetic variants in general – may affect both the brain and risk for a range of diseases. The ENIGMA consortium is discovering factors that consistently affect brain structure and function that will serve as future predictors linking individual brain scans and genomic data. It is generating vast pools of normative data on brain measures – from tens of thousands of people – that may help detect deviations from normal development or aging in specific groups of subjects. We discuss challenges and opportunities in applying these predictors to individual subjects and new cohorts, as well as lessons we have learned in ENIGMA's efforts so far.
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