The neurobiology of emotion regulation in posttraumatic stress disorder: Amygdala downregulation via real-time fMRI neurofeedback

Abstract

Amygdala dysregulation has been shown to be central to the pathophysiology of posttraumatic stress disorder (PTSD) representing a critical treatment target. Here, amygdala downregulation was targeted using real-time fMRI neurofeedback (rt-fMRI-nf) in patients with PTSD, allowing us to examine further the regulation of emotional states during symptom provocation. Patients (n = 10) completed three sessions of rt-fMRI-nf with the instruction to downregulate activation in the amygdala, while viewing personalized trauma words. Amygdala downregulation was assessed by contrasting (a) regulate trials, with (b) viewing trauma words and not attempting to regulate. Training was followed by one transfer run not involving neurofeedback. Generalized psychophysiological interaction (gPPI) and dynamic causal modeling (DCM) analyses were also computed to explore task-based functional connectivity and causal structure, respectively. It was found that PTSD patients were able to successfully downregulate both right and left amygdala activation, showing sustained effects within the transfer run. Increased activation in the dorsolateral and ventrolateral prefrontal cortex (PFC), regions related to emotion regulation, was observed during regulate as compared with view conditions. Importantly, activation in the PFC, rostral anterior cingulate cortex, and the insula, were negatively correlated to PTSD dissociative symptoms in the transfer run. Increased functional connectivity between the amygdala- and both the dorsolateral and dorsomedial PFC was found during regulate, as compared with view conditions during neurofeedback training. Finally, our DCM analysis exploring directional structure suggested that amygdala downregulation involves both top-down and bottom-up information flow with regard to observed PFC-amygdala connectivity. This is the first demonstration of successful downregulation of the amygdala using rt-fMRI-nf in PTSD, which was critically sustained in a subsequent transfer run without neurofeedback, and corresponded to increased connectivity with prefrontal regions involved in emotion regulation during the intervention. Hum Brain Mapp 38:541-560, 2017. © 2016 Wiley Periodicals, Inc.

Keywords: amygdala; brain connectivity; emotion; fMRI neurofeedback; posttraumatic stress disorder.

© 2016 Wiley Periodicals, Inc.

Figures

Figure 1

Real‐time fMRI amygdala neurofeedback experimental design. Participants were only instructed to downregulate neurofeedback thermometer bars, corresponding to amygdala activation, on regulate trials. Condition duration was 24 s, with 2 s of instructions prior. Personalized trauma words were presented in the scanner for regulate and view conditions, while neutral words were presented for the neutral conditions only. [Color figure can be viewed at http://wileyonlinelibrary.com.]

Figure 2

(a) Right amygdala parameter estimates corresponding to amygdala activation during neurofeedback runs for the view (solid green line) and regulate (solid red line) conditions. (b) Left amygdala parameter estimates corresponding to amygdala activation during neurofeedback runs for the view (solid green line) and regulate (solid red line) conditions. (c) Bilateral amygdala parameter estimates corresponding to activation during the transfer run without neurofeedback for the view (solid green line) and regulate (solid red line) conditions. Shaded red and green regions adjacent to the solid lines indicate standard error of the mean. Statistical thresholds corresponds to a‐priori paired sample t‐tests, comparing amygdala activation during view versus regulate across the whole condition, and for the last two thirds of the condition. Each of these respective t‐tests are indicated by the black bars on the bottom of each graph. Asterisks indicate Bonferroni corrected statistical thresholds for paired sample t‐tests. Abbreviations: NFB, neurofeedback. [Color figure can be viewed at http://wileyonlinelibrary.com.]

Figure 3

(a) One‐way ANOVA examining the main effect of run across neurofeedback training runs for regulate as compared view conditions (FDR‐cluster‐corrected P < 0.05, k = 10). (b) One‐way ANOVA examining the main effect of run across neurofeedback training runs and the transfer run for regulate as compared with view conditions (FDR‐cluster‐corrected P < 0.05, k = 10). (c) Follow‐up t‐tests examining greater activation for regulate as compared with view conditions, for neurofeedback training run 3 as compared with run 1 (FDR‐cluster‐corrected P < 0.05, k = 10). Coordinates indicate x, y, z, in MNI space displayed in MRIcron software. Abbreviations: NFB, neurofeedback; dlPFC, dorsolateral prefrontal cortex; vlPFC, ventrolateral prefrontal cortex. [Color figure can be viewed at http://wileyonlinelibrary.com.]

Figure 4

Brain regions whose activation were negatively correlated to PTSD symptoms of dissociation during the transfer run, for the regulate as compared with view condition (FDR‐cluster‐corrected P < 0.05, k = 10). Coordinates indicate x, y, z, in MNI space displayed in MRIcron software. Abbreviations: dlPFC, dorsolateral prefrontal cortex; dmPFC, dorsomedial prefrontal cortex; vlPFC, ventrolateral prefrontal cortex; ACC, anterior cingulate cortex. [Color figure can be viewed at http://wileyonlinelibrary.com.]

Figure 5

(a) Increased task based functional connectivity during the neurofeedback regulate condition for the left amygdala. (b) Increased task based functional connectivity during the neurofeedback regulate condition for the right amygdala. (FDR‐cluster‐corrected P < 0.05, k = 10). Coordinates indicate x, y, z, in MNI space displayed in MRIcron software. Abbreviations: dlPFC, dorsolateral prefrontal cortex; dmPFC, dorsomedial prefrontal cortex; ACC, anterior cingulate cortex. [Color figure can be viewed at http://wileyonlinelibrary.com.]

Figure 6

Upper portion of figure indicates the nine models tested in the dynamic causal modeling analysis. Model number 9 was the best fitting model with respect to Bayesian model selection for all analyses examined. The nine models were derived from different combinations of signal input (either in the amygdala [amy], in the prefrontal cortex [PFC], or in both) and causal information flow (either from the amygdala to the PFC, from the PFC to the amygdala, or both). Models 1–9 are displayed with arrows indicating intrinsic information flow between the amygdala and PFC, and modulating input from the conditions (“regulate,” “view”) on the network nodes and connections. Referencing the bottom half of the figure, graphs on the top indicate the family level inference. Models were grouped in families based on their driving inputs (1) models with both amygdala and PFC driving inputs (models 1–3), (2) models with amygdala driving inputs only (models 4–6), and (3) models with PFC driving inputs only (models 7–9). The graphs on the lower half indicate the random effects analysis examining individual models not grouped into families. The exceedance probability (xP) of each model/family of models is displayed in vertical bars. Displayed are the exceedance probabilities for the family level inference (top) and individual model random effects analysis (bottom) for (a) the left amygdala‐right dlPFC connection, (b) the left amygdala‐left dmPFC connection, and (c) the right amygdala‐right dmPFC connection. [Color figure can be viewed at http://wileyonlinelibrary.com.]