ePoster

LEARNING AND RELEARNING DEFICITS IN A MOUSE MODEL OF DEPRESSION

Namra Chaudharyand 2 co-authors

Universite Paris Saclay

FENS Forum 2026 (2026)
Barcelona, Spain
Board PS02-07PM-087

Presentation

Date TBA

Board: PS02-07PM-087

Poster preview

LEARNING AND RELEARNING DEFICITS IN A MOUSE MODEL OF DEPRESSION poster preview

Event Information

Poster Board

PS02-07PM-087

Abstract

Major depressive disorder (MDD) is a common psychiatric condition. It is often associated with cognitive disturbances which may contribute to treatment resistance. Among these disturbances, we hypothesized that stress, a known predisposing factor for depression, may drive deficits in memory encoding (learning) and updating (cognitive inflexibility or relearning).
To validate this hypothesis, we first assessed emotional dysfunction and learning deficits after 28 days of chronic corticosterone (CORT) supplementation in drinking water in an initial cohort of mice. Decision-making was assessed in a separate cohort through a probabilistic reinforcement discrimination (PRD) task, both prior and throughout the same CORT treatment. Both cohorts were subsequently phenotyped for anxio-depressive behaviors and evaluated for learning (novel object recognition, NOR) and “relearning” when possible (Radial arm maze; RAM).
Both cohorts displayed anxio-depressive behaviours. In the PRD cohort, CORT-treated mice exhibited greater preference for the most rewarding option in this test, resulting from the rigid reliance on acquired preference at the expense of deceptive experiences of reinforcement. Similar cognitive inflexibility was mirrored using RAM, where mice struggled to re-locate food when the baited arm was changed. Interestingly, mice successfully learned to initially locate the food. Preserved learning ability was similarly observed in the NOR test. Impairments in learning emerged only in CORT-treated mice lacking prior PRD experience. Our results interestingly dissociate learning from relearning deficits, suggesting that chronic stress alters relearning potentially independently of it impact on learning. This framework will help to identify neural structural biomarkers underlying the dissociation between learning and relearning.

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