Amygdala fMRI-A Critical Appraisal of the Extant Literature.

Even before the advent of fMRI, the amygdala occupied a central space in the affective neurosciences. Yet this amygdala-centred view on emotion processing gained even wider acceptance after the inception of fMRI in the early 1990s, a landmark that triggered a goldrush of fMRI studies targeting the amygdala in vivo. Initially, this amygdala fMRI research was mostly confined to task-activation studies measuring the magnitude of the amygdala's response to emotional stimuli. Later, interest began to shift more towards the study of the amygdala's resting-state functional connectivity and task-based psychophysiological interactions. Later still, the test-retest reliability of amygdala fMRI came under closer scrutiny, while at the same time, amygdala-based real-time fMRI neurofeedback gained widespread popularity. Each of these major subdomains of amygdala fMRI research has left its marks on the field of affective neuroscience at large. The purpose of this review is to provide a critical assessment of this literature. By integrating the insights garnered by these research branches, we aim to answer the question: What part (if any) can amygdala fMRI still play within the current landscape of affective neuroscience? Our findings show that serious questions can be raised with regard to both the reliability and validity of amygdala fMRI. These conclusions force us to cast doubt on the continued viability of amygdala fMRI as a core pilar of the affective neurosciences.

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.

Pattern classification based on the amygdala does not predict an individual's response to emotional stimuli.

Functional magnetic resonance imaging (fMRI) studies have often recorded robust univariate group effects in the amygdala of subjects exposed to emotional stimuli. Yet it is unclear to what extent this effect also holds true when multi-voxel pattern analysis (MVPA) is applied at the level of the individual participant. Here we sought to answer this question. To this end, we combined fMRI data from two prior studies (N = 112). For each participant, a linear support vector machine was trained to decode the valence of emotional pictures (negative, neutral, positive) based on brain activity patterns in either the amygdala (primary region-of-interest analysis) or the whole-brain (secondary exploratory analysis). The accuracy score of the amygdala-based pattern classifications was statistically significant for only a handful of participants (4.5%) with a mean and standard deviation of 37% ± 5% across all subjects (range: 28-58%; chance-level: 33%). In contrast, the accuracy score of the whole-brain pattern classifications was statistically significant in roughly half of the participants (50.9%), and had an across-subjects mean and standard deviation of 49% ± 6% (range: 33-62%). The current results suggest that the information conveyed by the emotional pictures was encoded by spatially distributed parts of the brain, rather than by the amygdala alone, and may be of particular relevance to studies that seek to target the amygdala in the treatment of emotion regulation problems, for example via real-time fMRI neurofeedback training.

Spontaneous brain activity, graph metrics, and head motion related to prospective post-traumatic stress disorder trauma-focused therapy response.

Introduction: Trauma-focused psychotherapy for post-traumatic stress disorder (PTSD) is effective in about half of all patients. Investigating biological systems related to prospective treatment response is important to gain insight in mechanisms predisposing patients for successful intervention. We studied if spontaneous brain activity, brain network characteristics and head motion during the resting state are associated with future treatment success. Methods: Functional magnetic resonance imaging scans were acquired from 46 veterans with PTSD around the start of treatment. Psychotherapy consisted of trauma-focused cognitive behavioral therapy (tf-CBT), eye movement desensitization and reprocessing (EMDR), or a combination thereof. After intervention, 24 patients were classified as treatment responders and 22 as treatment resistant. Differences between groups in spontaneous brain activity were evaluated using amplitude of low-frequency fluctuations (ALFF), while global and regional brain network characteristics were assessed using a minimum spanning tree (MST) approach. In addition, in-scanner head motion was assessed. Results: No differences in spontaneous brain activity and global network characteristics were observed between the responder and non-responder group. The right inferior parietal lobule, right putamen and left superior parietal lobule had a more central position in the network in the responder group compared to the non-responder group, while the right dorsolateral prefrontal cortex (DLPFC), right inferior frontal gyrus and left inferior temporal gyrus had a less central position. In addition, responders showed less head motion. Discussion: These results show that areas involved in executive functioning, attentional and action processes, learning, and visual-object processing, are related to prospective PTSD treatment response in veterans. In addition, these findings suggest that involuntary micromovements may be related to future treatment success.

Trauma and posttraumatic stress disorder modulate polygenic predictors of hippocampal and amygdala volume.

The volume of subcortical structures represents a reliable, quantitative, and objective phenotype that captures genetic effects, environmental effects such as trauma, and disease effects such as posttraumatic stress disorder (PTSD). Trauma and PTSD represent potent exposures that may interact with genetic markers to influence brain structure and function. Genetic variants, associated with subcortical volumes in two large normative discovery samples, were used to compute polygenic scores (PGS) for the volume of seven subcortical structures. These were applied to a target sample enriched for childhood trauma and PTSD. Subcortical volume PGS from the discovery sample were strongly associated in our trauma/PTSD enriched sample (n = 7580) with respective subcortical volumes of the hippocampus (p = 1.10 × 10-20), thalamus (p = 7.46 × 10-10), caudate (p = 1.97 × 10-18), putamen (p = 1.7 × 10-12), and nucleus accumbens (p = 1.99 × 10-7). We found a significant association between the hippocampal volume PGS and hippocampal volume in control subjects from our sample, but was absent in individuals with PTSD (GxE; (beta = -0.10, p = 0.027)). This significant GxE (PGS × PTSD) relationship persisted (p < 1 × 10-19) in four out of five threshold peaks (0.024, 0.133, 0.487, 0.730, and 0.889) used to calculate hippocampal volume PGSs. We detected similar GxE (G × ChildTrauma) relationships in the amygdala for exposure to childhood trauma (rs4702973; p = 2.16 × 10-7) or PTSD (rs10861272; p = 1.78 × 10-6) in the CHST11 gene. The hippocampus and amygdala are pivotal brain structures in mediating PTSD symptomatology. Trauma exposure and PTSD modulate the effect of polygenic markers on hippocampal volume (GxE) and the amygdala volume PGS is associated with PTSD risk, which supports the role of amygdala volume as a risk factor for PTSD.

Voxel-based morphometry and cortical thickness in combat veterans suffering from impulsive aggression.

BACKGROUND: Problems with impulsive aggression occur in many forms of psychiatric dysfunction, and are a common complaint among combat veterans. The present study sought to examine the neuroanatomical correlates of combat-related impulsive aggression. METHODS: T1-weighted magnetic resonance images were acquired from 29 male veterans with impulsive aggression and 30 non-aggressive combat controls. Subcortical volumetry was conducted with the amygdala and hippocampus and their main constituent subdivisions as regions-of-interest (ROIs) (basolateral, centromedial amygdala; head, body, tail of hippocampus). Cortical thickness measurements were extracted for the dorsolateral prefrontal cortex, orbitofrontal cortex, and anterior cingulate cortex. Within-group correlations with psychometric measures were also explored. RESULTS: No significant group differences in cortical thickness or subcortical grey matter volumes were observed for any of the ROIs. Also, no significant correlations with any of the psychometric measures were recorded. Exploratory whole-brain analysis of cortical thickness revealed a significant group × anxiety interaction effect in a cluster located in the left lingual gyrus. CONCLUSIONS: The current findings indicate that problems with impulsive aggression may not be directly associated with alterations in cortical thickness or amygdalar/hippocampal (sub)volumes. The observed interplay between impulsive aggression problems and anxiety-related symptoms is consistent with prior work showing the two phenomena may share the same underlying (neural) mechanisms.

The Predictive Value of Early-Life Trauma, Psychopathy, and the Testosterone-Cortisol Ratio for Impulsive Aggression Problems in Veterans.

BACKGROUND: In this study, we examined whether early-life trauma, psychopathy, and the testosterone/cortisol ratio predicted impulsive aggression problems in veterans. METHOD: A sample of 49 male veterans with impulsive aggression problems and 51 nonaggressive veterans were included in the study. Logistic regression analysis was performed with early-life trauma, primary and secondary psychopathy, and testosterone/cortisol ratio as continuous predictor variables; impulsive aggression status was entered as a binary outcome measure. Correlation analyses were conducted to examine pairwise relations among the predictors. RESULTS: Results indicated that early-life trauma and secondary psychopathy, but not the testosterone/cortisol ratio or primary psychopathy, were significant predictors of impulsive aggression status. CONCLUSIONS: The current results indicate that early-life trauma and secondary psychopathy are risk factors for impulsive aggression problems among veterans. Future studies are needed to determine the exact causal relations among the variables examined here.

Resting-state functional connectivity in combat veterans suffering from impulsive aggression.

Impulsive aggression is common among military personnel after deployment and may arise because of impaired top-down regulation of the amygdala by prefrontal regions. This study sought to further explore this hypothesis via resting-state functional connectivity analyses in impulsively aggressive combat veterans. Male combat veterans with (n = 28) and without (n = 30) impulsive aggression problems underwent resting-state functional magnetic resonance imaging. Functional connectivity analyses were conducted with the following seed-regions: basolateral amygdala (BLA), centromedial amygdala, anterior cingulate cortex (ACC), and anterior insular cortex (AIC). Regions-of-interest analyses focused on the orbitofrontal cortex and periaqueductal gray, and yielded no significant results. In exploratory cluster analyses, we observed reduced functional connectivity between the (bilateral) BLA and left dorsolateral prefrontal cortex in the impulsive aggression group, relative to combat controls. This finding indicates that combat-related impulsive aggression may be marked by weakened functional connectivity between the amygdala and prefrontal regions, already in the absence of explicit emotional stimuli. Group differences in functional connectivity were also observed between the (bilateral) ACC and left cuneus, which may be related to heightened vigilance to potentially threatening visual cues, as well as between the left AIC and right temporal pole, possibly related to negative memory association in impulsive aggression.