GLM-HMM

When making decisions, animals can employ many strategies, from relying on environmental stimuli to relying on internal biases. The roles of cortical regions in shaping these decision-making strategies remain unclear, often because we lack direct access to these internal variables. Here, we investigated how optogenetic inactivation of 29 motor, sensory, or association cortical regions affects decision-making strategies in 20 mice performing a virtual T-maze task in which they were rewarded for choosing the side with more visual cues. To determine mice’s underlying strategies on any trial, we f

Psychedelics like psilocybin and ketamine have shown great potential in treating psychiatric disorders, often producing long-lasting effects after a single dose, yet their underlying neural mechanisms remain poorly understood. Since one of the most consistent features of the psychedelic experience is the alteration in perception, this study aimed to investigate how acute doses of psychedelics influence perceptual integration. We used a free-response perceptual integration task in mice, alongside brain-wide mapping of drug-responsive populations using activity-dependent gene expression and calc

A fundamental property of natural intelligence is the capacity to recognise and leverage statistical patterns in the environment to promote adaptive behaviour. This capability, often termed statistical learning (SL), enables us to construct accurate models of the world that aid in perception and decision-making, when faced with noisy and ambiguous sensory input. However, despite extensive data from human experiments and proposals from theoretical neuroscience, the neural implementation of SL remains elusive. To address this, we employed a two-alternative forced-choice (2-AFC) sound categorisat

Stochastic strategies are often advantageous in competitive environments to prevent opponents from predicting one’s actions. To study how stochastic behaviours arise, we trained head-fixed mice to play a zero-sum game, Matching Pennies, in which the optimal behaviour against a rational agent is to choose between actions with equal probability. On each trial, mice chose between two available actions: lick left or right. A computer opponent predicted each animal’s upcoming choice by searching for statistical regularities in their choice and reward history. If mice remained unpredictable against

Understanding how internally driven cognitive processes (COPs) give rise to behavior in different species is one of the key challenges in systems neuroscience. Traditionally, neuroscience has aimed to isolate individual COPs by simplifying sensory stimuli and behavioral readouts. Yet in natural behavior, several COPs can co-occur, often with overlapping neural representations. The dynamics of such superimposed COPs are yet to be understood, as well as the extent to which they generalize across species. To tackle this question, we developed a naturalistic Virtual Reality setup in which two spec

Recent work has shown that rodent decision-making relies on distinct latent or hidden states that switch on a timescale of tens to hundreds of trials [Ashwood 2021; Bolkan, Stone 2021; Weilnhammer 2021]. However, the neural basis for these states, and the contributions of different brain regions to state-dependent decision-making strategies, remains an important open problem. Here we address this challenge by performing a model-based analysis of decision-making data acquired during multi-region laser-scanning inactivation of dorsal cortex. We analyzed optogenetic inactivation data from mice pe

…a latent variable framework, the “GLM-HMM”, to hundreds of thousands of trials of mouse choice data. Our analysis reveals that mice don’t lapse. Instead, mice switch back and forth between engaged and disengaged behavior within a single session, and each mode of behavior lasts tens to hundreds of trials.