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Investigating Pain-Related Avoidance Behavior using a Robotic Arm-Reaching Paradigm
Published on: October 3, 2020
The Neural Basis of Avoidance Learning and Its Relation to Safety Processing
Lieselotte Claes1,2, Patrick A F Laing3, Trevor Steward4,5
1Department of Psychiatry, The University of Melbourne, Parkville, Victoria 3010, Australia lclaes@student.unimelb.edu.au habj@unimelb.edu.au.
Abstract:
Persistent avoidance plays a major role in maintaining anxiety disorders. The few studies that have explored the neural basis of avoidance have predominantly examined established avoidance behaviors rather than the learning processes that establish avoidance responses. We aimed to characterize the temporal dynamics and neural mechanisms of avoidance learning using a novel paradigm combined with 7 tesla fMRI in 82 healthy participants (37 male and 45 female). Participants were first conditioned to two threat stimuli and a compound safety stimulus. Next, they were trained to avoid one threat stimulus while the other remained unavoidable. Behavioral data confirmed accurate learning of task contingencies. Successful avoidance was associated with prominent activation of the ventromedial prefrontal cortex (vmPFC), posterior cingulate cortex (PCC), and ventrolateral prefrontal cortex compared with unsuccessful avoidance, with additional nucleus accumbens and orbitofrontal cortex engagement when compared with safety learning (P FDR whole-brain corrected). Critically, early compared with late avoidance learning was distinctly associated with activation of midbrain-striatal circuits, including the periaqueductal gray (PAG), mediodorsal thalamus, substantia nigra, and anterior insular cortex-regions associated with threat processing and learning-related signaling. These findings suggest that initial avoidance learning relies on subcortical threat-responsive and learning-related circuits, whereas established avoidance responses engage cortical safety-processing regions. This dissociation parallels recent findings in safety learning and provides novel mechanistic insights for interventions targeting maladaptive avoidance patterns.
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