ePoster

BEHAVIORAL AND NEURONAL NETWORK CHANGES DURING THE MANIFESTATION OF DEPRESSION - A LONGITUDINAL STUDY

Patricia Przibyllaand 1 co-author

University Medical Center Mainz

FENS Forum 2026 (2026)
Barcelona, Spain
Board PS07-10AM-253

Presentation

Date TBA

Board: PS07-10AM-253

Poster preview

BEHAVIORAL AND NEURONAL NETWORK CHANGES DURING THE MANIFESTATION OF DEPRESSION - A LONGITUDINAL STUDY poster preview

Event Information

Poster Board

PS07-10AM-253

Abstract

Major depressive disorder is one of the most frequently occurring mental disorders in humans. An estimated 5% of adults worldwide experience at least one depressive episode in their lifetime. Main symptoms of this mental illness include anhedonia, depressed mood, weight loss, change of sleep patterns and movements as well as changes in sensory perception. However, how and when these symptoms develop and how the behavioral and perceptual changes map onto changes in cortical network activity as a depression manifests, is poorly understood.
The chronic social defeat (CSD) stress model is a widely established paradigm to induce a depression-like phenotype in mice. We monitor the manifestation of the CSD evoked depressive-like phenotype daily by collecting a wide range of behavioral variables. These include weight, coat state, nesting, motor activity, sleep, body temperature, thermal sensitivity and social interactions. Using two-photon calcium imaging, we record the activity of hundreds of cortical neurons daily in head-fixed behaving mice before, during and after mice undergo the CSD stress. We then align the occurring behavioral symptoms to the neuronal activity on a single-subject level as well as across mice. Our investigations show that behavioral changes occur successively over the time course of the CSD stress and recovery extends well beyond the stress. Furthermore, we observe gradual changes of neural network activity during the manifestation of the depressive-like state that scale with the severity of the symptoms. Linking behavioral and neuronal network changes may help to further our understanding of the disease and develop more targeted interventions.

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