Project Summary Classical aversive conditioning is a well-established laboratory model for studying acquisition and extinction of defensive responses. In experimental animals, as well as in humans, research to date has been mainly focused on the role of limbic structures (e.g., the amygdala) in these responses. Recent evidence has begun to stress the important contribution by the brain’s sensory and attention control systems in maintaining the neural representations of conditioned responses and in facilitating their extinction. The proposed research breaks new ground by combining novel neuroimaging techniques with advanced computational methods to examine the brain’s visual and attention processes underlying fear acquisition and extinction in humans. Major advances will be made along three specific aims. In Aim 1, we characterize the brain network dynamics of visuocortical threat bias formation, extinction, and recall in a two-day learning paradigm. In Aim 2, we establish and test a computational model of threat bias generalization. In Aim 3, we examine the relation between individual differences in generalization and recall of conditioned visuocortical threat biases and individual differences in heightened autonomic reactivity to conditioned threat, a potential biomarker for assessing the predisposition to developing the disorders of fear and anxiety. It is expected that accomplishing these research aims will address two NIMH strategic priorities: defining the circuitry and brain networks underlying complex behaviors (Objective 1) and identifying and validating new targets for treatment that are derived from the understanding of disease mechanisms (Objective 3). It is further expected that this project will enable a paradigm shift in research on dysfunctional attention to threat from one that focuses primarily on limbic-prefrontal circuits to one that emphasizes the interactions among sensory, attention, executive control and limbic systems.

Project Narrative The learning and un-learning of a fear response through conditioning and extinction learning is a process that is of interest not only for basic neuroscience research, but also for clinical intervention and diagnostic procedures in a variety of psychiatric disorders. In the present proposal, building on strong preliminary data that suggest a pivotal role of visual and attention systems, along with limbic structures, in aversive learning, we seek to use simultaneous EEG-fMRI, combined with computational modeling and advanced analytical techniques including machine learning, to characterize—in time and space—the dynamics and communication within and among the brain’s visual, attention and limbic networks during the acquisition and extinction of conditioned fear in healthy populations. Furthermore, testing of the proposed computational model on a community sample stratified by their cardiac reactivity to threat will advance our understanding of the model’s capability to differentiate individual differences in threat response, and lay the foundation for identifying new biomarkers and treatment targets for disorders of fear, anxiety, and post-traumatic stress.