Back

Fronto-striatal projections regulate approach-avoidance conflict

Loewke, A. C.; Minerva, A. R.; Nelson, A. B.; Kreitzer, A. C.; Gunaydin, L. A.

2020-03-06 neuroscience
10.1101/2020.03.05.979708 bioRxiv
Show abstract

The dorsomedial prefrontal cortex (dmPFC) has been linked to approach-avoidance behavior and decision-making under conflict, key neural computations thought to be altered in anxiety disorders. However, the heterogeneity of efferent prefrontal projections has obscured identification of the specific top-down neural pathways regulating these anxiety-related behaviors. While the dmPFC-amygdala circuit has long been implicated in controlling reflexive fear responses, recent work suggests that this circuit is less important for avoidance behavior. We hypothesized that dmPFC neurons projecting to the dorsomedial striatum (DMS) represent a subset of prefrontal neurons that robustly encode and drive approach-avoidance behavior. Using fiber photometry recording during the elevated zero maze (EZM) task, we show heightened neural activity in prefrontal and fronto-striatal projection neurons, but not fronto-amydalar projection neurons, during exploration of the anxiogenic open arms of the maze. Additionally, through pathway-specific optogenetics we demonstrate that this fronto-striatal projection preferentially excites postsynaptic D1 receptor-expressing medium spiny neurons in the DMS and bidirectionally controls avoidance behavior. We conclude that this striatal-projecting subpopulation of prefrontal neurons regulates approach-avoidance conflict, supporting a model for prefrontal control of defensive behavior in which the dmPFC-amygdala projection controls reflexive fear behavior and the dmPFC-striatum projection controls anxious avoidance behavior. Our findings identify this fronto-striatal circuit as a valuable therapeutic target for developing interventions to alleviate excessive avoidance behavior in anxiety disorders.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.