NIH R01 · 2025
Quantifying neural signatures of multi-step avoidance behavior in anxiety
Anxiety and related disorders are common and impairing; in particular, avoidance is a highly detrimental component of anxiety that is poorly understood. To better understand and treat avoidance, a theory of avoidance that can account for experimental findings and translate across species is needed. This application proposes to use an interdisciplinary approach to combine neural and behavioral data to validate a novel computational model of avoidance, to test differences in avoidance behavior in people with clinically impairing anxiety and avoidance using this model, and to test whether model-predicted behavior is correlated with and has a causal influence on real-world avoidance behavior.…
From the public funding record at NIH RePORTER. Describes the funded project, not the reviews below.