The Periaqueductal Gray Selectively Supports Reversal Learning During a Flexible Discrimination Task in Mice

Flexible, goal-directed behavior depends on the ability to update value representations in response to changing contingencies. This ability depends on distributed brain networks, calling for use of whole-brain imaging. Widely used in human research, the challenge of functional fMRI in rodents has only recently been properly addressed, opening the door to whole-brain imaging of behaving mice. Here, we used functional MRI in mice performing a go/no-go odor discrimination task, we compared neural activity during initial cue-reward learning (acquisition) and subsequent contingency reversal. Trial-by-trial estimates of state-action values from a model-free reinforcement-learning algorithm allowed us to dissociate acquisition from reversal-related signals, revealing that ventral striatal responses tracked expected value during acquisition, whereas reversal learning additionally recruited the periaqueductal gray (PAG), a midbrain structure classically linked to threat processing and aversive learning. PAG activity closely followed model-derived signatures of reversal learning, implicating it in the suppression of previously rewarded actions and in updating behavior in the absence of explicit punishment. These findings reveal a previously unrecognized computational role for the PAG in value-based decision-making and cognitive flexibility, and substantiate task-fMRI as a powerful tool to study the rodent brain at a mesoscale resolution.

Authors

Institutions

Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-01-19
DOI
https://doi.org/10.64898/2026.01.19.700312
Primary Topic
Neural and Behavioral Psychology Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Periaqueductal Gray Selectively Supports Reversal Learning During a Flexible Discrimination Task in Mice

Raphael T. Gerraty, Jonathan Nicholas, Eyal Bergmann, Daniela Lichtman et al.
bioRxiv (Cold Spring Harbor Laboratory)
Neural and Behavioral Psychology Studies
article

The Periaqueductal Gray Selectively Supports Reversal Learning During a Flexible Discrimination Task in Mice

Raphael T. Gerraty, Jonathan Nicholas, Eyal Bergmann, Daniela Lichtman, Itamar Kahn
article en

Abstract

Flexible, goal-directed behavior depends on the ability to update value representations in response to changing contingencies. This ability depends on distributed brain networks, calling for use of whole-brain imaging. Widely used in human research, the challenge of functional fMRI in rodents has only recently been properly addressed, opening the door to whole-brain imaging of behaving mice. Here, we used functional MRI in mice performing a go/no-go odor discrimination task, we compared neural activity during initial cue-reward learning (acquisition) and subsequent contingency reversal. Trial-by-trial estimates of state-action values from a model-free reinforcement-learning algorithm allowed us to dissociate acquisition from reversal-related signals, revealing that ventral striatal responses tracked expected value during acquisition, whereas reversal learning additionally recruited the periaqueductal gray (PAG), a midbrain structure classically linked to threat processing and aversive learning. PAG activity closely followed model-derived signatures of reversal learning, implicating it in the suppression of previously rewarded actions and in updating behavior in the absence of explicit punishment. These findings reveal a previously unrecognized computational role for the PAG in value-based decision-making and cognitive flexibility, and substantiate task-fMRI as a powerful tool to study the rodent brain at a mesoscale resolution.

bioRxiv (Cold Spring Harbor Laboratory)
Technion – Israel Institute of Technology (IL), New York University (US), Columbia University (US)
Reduced inequalities
Openalex Percentile: Top 82%
Neural and Behavioral Psychology Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.