Supracategorical fear information revealed by aversively conditioning multiple categories

Threat induction biases processing of emotional expressions

Threats can derive from our physical or social surroundings and bias the way we perceive and interpret a given situation. They can be signaled by peers through facial expressions, as expressed anger or fear can represent the source of perceived threat. The current study seeks to investigate enhanced attentional state and defensive reflexes associated with contextual threat induced through aversive sounds presented in an emotion recognition paradigm. In a sample of 120 healthy participants, response and gaze behavior revealed differences in perceiving emotional facial expressions between threat and safety conditions: Responses were slower under threat and less accurate. Happy and neutral facial expressions were classified correctly more often in a safety context and misclassified more often as fearful under threat. This unidirectional misclassification suggests that threat applies a negative filter to the perception of neutral and positive information. Eye movements were initiated later under threat, but fixation changes were more frequent and dwell times shorter compared to a safety context. These findings demonstrate that such experimental paradigms are capable of providing insight into how context alters emotion processing at cognitive, physiological, and behavioral levels. Such alterations may derive from evolutionary adaptations necessary for biasing cognitive processing to survive disadvantageous situations. This perspective sets up new testable hypotheses regarding how such levels of explanation may be dysfunctional in patient populations.

Pattern analysis of neuroimaging data reveals novel insights on threat learning and extinction in humans

Several decades of rodent neurobiology research have identified a network of brain regions that support Pavlovian threat conditioning and extinction, focused predominately on the amygdala, hippocampus, and medial prefrontal cortex (mPFC). Surprisingly, functional magnetic resonance imaging (fMRI) studies have shown inconsistent evidence for these regions while humans undergo threat conditioning and extinction. In this review, we suggest that translational neuroimaging efforts have been hindered by reliance on traditional univariate analysis of fMRI. Whereas univariate analyses average activity across voxels in a given region, multivariate pattern analyses (MVPA) leverage the information present in spatial patterns of activity. MVPA therefore provides a more sensitive analysis tool to translate rodent neurobiology to human neuroimaging. We review human fMRI studies using MVPA that successfully bridge rodent models of amygdala, hippocampus, and mPFC function during Pavlovian learning. We also highlight clinical applications of these information-sensitive multivariate analyses. In sum, we advocate that the field should consider adopting a variety of multivariate approaches to help bridge cutting-edge research on the neuroscience of threat and anxiety.

Individualizing Representational Similarity Analysis

Representational similarity analysis (RSA) is a popular multivariate analysis technique in cognitive neuroscience that uses functional neuroimaging to investigate the informational content encoded in brain activity. As RSA is increasingly being used to investigate more clinically-geared questions, the focus of such translational studies turns toward the importance of individual differences and their optimization within the experimental design. In this perspective, we focus on two design aspects: applying individual vs. averaged behavioral dissimilarity matrices to multiple participants' neuroimaging data and ensuring the congruency between tasks when measuring behavioral and neural representational spaces. Incorporating these methods permits the detection of individual differences in representational spaces and yields a better-defined transfer of information from representational spaces onto multivoxel patterns. Such design adaptations are prerequisites for optimal translation of RSA to the field of precision psychiatry.