Hippocampal-cingulate dynamics in the human brain link reinforcement-learning and memory.

Authors

Salman E Qasim, Fedor Panov, Lizbeth Nunez, Ariane E Rhone, Hiroto Kawasaki, Christopher Kovach, Christopher Garcia, Brian Dlouhy, Xiaosi Gu, Ignacio Saez

Published in

bioRxiv : the preprint server for biology. Sep 12, 2026. Epub Sep 12, 2026.

Abstract

Reinforcement learning (RL) models describe how reward computations shape our choices, but whether the same computations also shape memory in the human brain is unclear. To address this question, we combined multi-areal intracranial recordings with computational modeling of reward and memory in neurosurgical patients. Patients played a gambling task in which decisions yielded monetary rewards tied to trial-unique images, followed immediately by a recognition test for those images. Model-derived positive reward prediction errors (RPEs) predicted later memory for each image. During feedback, multivariate high-frequency activity revealed the spatiotemporal evolution of RPE representations across distributed prefrontal cortex. During subsequent recognition, however, only anterior cingulate cortex (ACC) transiently reinstated RPE representations, and successful recognition specifically associated with hippocampal reinstatement of these ACC representations. Hippocampal-cingulate theta synchrony scaled with RPE during recognition, alongside hippocampal theta decoding of upcoming memory choices. Thus, the RL computations that guide decision-making also shape memory through hippocampal-cingulate circuit dynamics in the human brain.

PMID:
42818771
Bibliographic data and abstract were imported from PubMed on 01 Oct 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.