Poster Presentation

Contributed Talk Session: Tuesday, August 4, 10:15 – 11:15 am, Skirball Theater
Poster D in Poster Session D: Wednesday, August 5, 2:00 – 3:45 pm, Kimmel Center, Shorin & Rosenthal Rooms

From Impulsivity to Engagement: Latent Behavioral States Reveal Distinct Decision Strategies in Rats

Aya Akhmetzhanova¹, Adam Goldring², Timothy Hanks², Rishidev Chaudhuri¹; ¹University of California, Davis, ²UC Davis

Presenter: Aya Akhmetzhanova

Behavioral variability in perceptual decision-making is often treated as noise, yet it may reflect meaningful fluctuations in internal cognitive state. We asked whether latent behavioral states could explain trial-to-trial variability in both behavior and neural population dynamics. In our work, we propose that latent behavioral states drive variability in perceptual decisions and simultaneously modulate neural dynamics across decision-related brain regions. To test this, rats were trained on an auditory decision-making task in which they reported increases in the click rate of a Poisson-generated stimulus. Fitting the Generalized Linear Model-Hidden Markov Model (GLM-HMM) model revealed two latent states that best captured behavioral variability across animals (Ashwood et al., 2021; Linderman et al., 2020). In an impulsive state, animals responded rapidly, producing frequent false alarms with little dependence on stimulus strength. In an engaged state, false alarm rates were markedly reduced, enabling stimulus-dependent correct detections. Large-scale Neuropixels recordings revealed no meaningful signature of behavioral state in mean firing rates or within-region correlations. Yet state identity was decoded from population activity trial-by-trial with high accuracy. Our findings provide a mechanistic link between internal engagement, neural population dynamics, and decision variability—challenging the assumption that engagement simply scales overall neural activity. Instead, latent behavioral states reflect discrete internal strategies encoded in population-level firing patterns.

Topic Area: Decision-Making, Cognitive Control & Event Cognition