Behavioral Strategy Shapes Activation of the Vip-Sst Disinhibitory Circuit in Visual Cortex
Overview
Authors
Affiliations
In complex environments, animals can adopt diverse strategies to find rewards. How distinct strategies differentially engage brain circuits is not well understood. Here, we investigate this question, focusing on the cortical Vip-Sst disinhibitory circuit between vasoactive intestinal peptide-postive (Vip) interneurons and somatostatin-positive (Sst) interneurons. We characterize the behavioral strategies used by mice during a visual change detection task. Using a dynamic logistic regression model, we find that individual mice use mixtures of a visual comparison strategy and a statistical timing strategy. Separately, mice also have periods of task engagement and disengagement. Two-photon calcium imaging shows large strategy-dependent differences in neural activity in excitatory, Sst inhibitory, and Vip inhibitory cells in response to both image changes and image omissions. In contrast, task engagement has limited effects on neural population activity. We find that the diversity of neural correlates of strategy can be understood parsimoniously as the increased activation of the Vip-Sst disinhibitory circuit during the visual comparison strategy, which facilitates task-appropriate responses.
Deciphering neuronal variability across states reveals dynamic sensory encoding.
Akella S, Ledochowitsch P, Siegle J, Belski H, Denman D, Buice M Nat Commun. 2025; 16(1):1768.
PMID: 39971911 PMC: 11839951. DOI: 10.1038/s41467-025-56733-w.
Basolateral amygdala oscillations enable fear learning in a biophysical model.
Cattani A, Arnold D, McCarthy M, Kopell N Elife. 2024; 12.
PMID: 39590510 PMC: 11594530. DOI: 10.7554/eLife.89519.
Coordinated changes in a cortical circuit sculpt effects of novelty on neural dynamics.
Ito S, Piet A, Bennett C, Durand S, Belski H, Garrett M Cell Rep. 2024; 43(9):114763.
PMID: 39288028 PMC: 11563561. DOI: 10.1016/j.celrep.2024.114763.
Basolateral amygdala oscillations enable fear learning in a biophysical model.
Cattani A, Arnold D, McCarthy M, Kopell N bioRxiv. 2023; .
PMID: 37163011 PMC: 10168360. DOI: 10.1101/2023.04.28.538604.