Dynamic competition between large-scale functional networks differentiates fear conditioning and extinction in humans

Parsing neural circuits of fear learning and extinction across basic and clinical neuroscience: Towards better translation

Over the past decades, studies of fear learning and extinction have advanced our understanding of the neurobiology of threat and safety learning. Animal studies can provide mechanistic/causal insights into human brain regions and their functional connectivity involved in fear learning and extinction. Findings in humans, conversely, may further enrich our understanding of neural circuits in animals by providing macroscopic insights at the level of brain-wide networks. Nevertheless, there is still much room for improvement in translation between basic and clinical research on fear learning and extinction. Through the lens of neural circuits, in this article, we aim to review the current knowledge of fear learning and extinction in both animals and humans, and to propose strategies to fill in the current knowledge gap for the purpose of enhancing clinical benefits.

Fear conditioning prompts sparser representations of conditioned threat in primary visual cortex

Repeated exposure to threatening stimuli alters sensory responses. We investigated the underlying neural mechanism by re-analyzing previously published simultaneous electroencephalogram-functional magnetic resonance imaging (EEG-fMRI) data from humans viewing oriented gratings during Pavlovian fear conditioning. In acquisition, one grating (CS+) was paired with a noxious noise, the unconditioned stimulus (US). The other grating (CS-) was never paired with the US. In habituation, which preceded acquisition, and in extinction, the same two gratings were presented without US. Using fMRI multivoxel patterns in primary visual cortex during habituation as reference, we found that during acquisition, aversive learning selectively prompted systematic changes in multivoxel patterns evoked by CS+. Specifically, CS+ evoked voxel patterns in V1 became sparser as aversive learning progressed, and the sparsified pattern appeared to be preserved in extinction. Concomitant with the voxel pattern changes, occipital alpha oscillations were increasingly more desynchronized during CS+ (but not CS-) trials. Across acquisition trials, the rate of change in CS+-related alpha desynchronization was correlated with the rate of change in multivoxel pattern representations of CS+. Furthermore, alpha oscillations co-varied with blood-oxygen-level-dependent (BOLD) data in the ventral attention network, but not with BOLD in the amygdala. Thus, fear conditioning prompts persistent sparsification of voxel patterns evoked by threat, likely mediated by attention-related mechanisms

L-DOPA and consolidation of fear extinction learning among women with posttraumatic stress disorder

This study tested whether L-DOPA delivered during the consolidation window following fear extinction learning reduces subsequent fear responding among women with PTSD. Adult women diagnosed with PTSD completed a contextual fear acquisition and extinction task during fMRI and then immediately received either placebo (n = 34), 100/25 mg L-DOPA/carbidopa (n = 28), or 200/50 mg L-DOPA/carbidopa (n = 29). Participants completed a resting-state scan before the task and again 45 min following drug ingestion to characterize effects of L-DOPA on extinction memory neural reactivation patterns during consolidation. Twenty-four hours later, participants returned for tests of context renewal, extinction recall, and reinstatement during fMRI with concurrent skin conductance responding (SCR) assessment. Both active drug groups demonstrated increased reactivation of extinction encoding in the amygdala during the post-task resting-state scan. For SCR data, both drug groups exhibited decreased Day 2 reinstatement across all stimuli compared to placebo, and there was some evidence for decreased context renewal to the fear stimulus in the 100 mg group compared to placebo. For imaging data, both drug groups demonstrated decreased Day 2 reinstatement across stimuli in a bilateral insula network compared to placebo. There was no evidence in SCR or neural activity that L-DOPA improved extinction recall. Reactivation of extinction encodings in the amygdala during consolidation on Day 1 predicted Day 2 activation of the insula network. These results support a role for dopamine during the consolidation window in boosting reactivation of amygdala extinction encodings and reducing reinstatement, but not improving extinction recall, in women with PTSD.

Brain functional connectome-based prediction of individual decision impulsivity

Extensive neuroimaging research has attempted to identify neural correlates and predictors of decision impulsivity. However, the nature and extent of decision impulsivity-brain association have varied substantially across studies, likely due to small sample sizes, limited image quality, different imaging measurement selections, and non-specific methodologies. The objective of this study was to develop a reliable predictive model of decision impulsivity-brain relationship in a large sample by applying connectome-based predictive modeling (CPM), a recently developed machine learning approach, to whole-brain functional connectivity data ("neural fingerprints"). For 809 healthy young participants from the Human Connectome Project, high-quality resting-state functional MRI data were utilized to construct brain functional connectome and delay discounting test was used to assess decision impulsivity. Then, CPM with leave-one-out cross-validation was conducted to predict individual decision impulsivity from whole-brain functional connectivity. We found that CPM successfully and reliably predicted the delay discounting scores in novel individuals. Moreover, different feature selection thresholds, parcellation strategies and cross-validation approaches did not significantly influence the prediction results. At the neural level, we observed that the decision impulsivity-associated functional networks included brain regions within default-mode, subcortical, somato-motor, dorsal attention, and visual systems, suggesting that decision impulsivity emerges from highly integrated connections involving multiple intrinsic networks. Our findings not only may expand existing knowledge regarding the neural mechanism of decision impulsivity, but also may present a workable route towards translation of brain imaging findings into real-world economic decision-making.

Stria terminalis, amygdala, and temporoparietal junction networks facilitate efficient emotion processing under expectations

Rapid emotion processing is an ecologically essential ability for survival in social environments in which threatening or advantageous encounters dynamically and rapidly occur. Efficient emotion recognition is subserved by different processes, depending on one's expectations; however, the underlying functional and structural circuitry is still poorly understood. In this study, we delineate brain networks that subserve fast recognition of emotion in situations either congruent or incongruent with prior expectations. For this purpose, we used multimodal neuroimaging and investigated performance on a dynamic emotion perception task. We show that the extended amygdala structural and functional networks relate to speed of emotion processing under threatening conditions. Specifically, increased microstructure of the right stria terminalis, an amygdala white-matter pathway, was related to faster detection of emotion during actual presentation of anger or after cueing anger. Moreover, functional connectivity of right amygdala with limbic regions was related to faster detection of anger congruent with cue, suggesting selective attention to threat. On the contrary, we found that faster detection of anger incongruent with cue engaged the ventral attention "reorienting" network. Faster detection of happiness, in either expectancy context, engaged a widespread frontotemporal-subcortical functional network. These findings shed light on the functional and structural circuitries that facilitate speed of emotion recognition and, for the first time, elucidate a role for the stria terminalis in human emotion processing.

Coupling and segregation of large-scale brain networks predict individual differences in delay discounting

Decision-making about rewards, which requires us to choose between different time points, generally refers to intertemporal choice. Converging evidence suggests that some of the brain networks recruited in the delay discounting task have been well characterized for intertemporal choice. However, little is known about how the connectivity patterns of these large-scale brain networks are associated with delay discounting. Here, we use a resting-state functional connectivity MRI (rs-fcMRI) and a graph theoretical analysis to address this question. We found that the delay discounting rates showed a positive correlation with the functional network connectivity (FNC) between the cingulo-opercular network (CON) and the default mode network (DMN), while they showed a negative correlation with the FNC of both the CON-SAN (salience network) and the SAN-FPN (fronto-parietal network). Our results showed the association of both coupling and segregating processes with large-scale brain networks in delay discounting. Thus, the present study highlights the pivotal role of the functional connectivity patterns of intrinsic large-scale brain networks in delay discounting and extends our perspective on the neural mechanism of delay discounting.