ePoster

VOLTAGE-IMAGING OF MOUSE DORSAL CORTEX DURING A WATER REACHING TASK REVEALS FAST SUBNETWORK AND OSCILLATORY DYNAMICS

Yunmiao Wangand 3 co-authors

Emory University

FENS Forum 2026 (2026)
Barcelona, Spain
Board PS02-07PM-540

Presentation

Date TBA

Board: PS02-07PM-540

Poster preview

VOLTAGE-IMAGING OF MOUSE DORSAL CORTEX DURING A WATER REACHING TASK REVEALS FAST SUBNETWORK AND OSCILLATORY DYNAMICS poster preview

Event Information

Poster Board

PS02-07PM-540

Abstract

Wide-field Voltage imaging in mice allows capturing fast dynamics of cortical cell populations across the entire surface of dorsal cortex during behavior. We expressed a JEDI-1P voltage sensor in excitatory neurons using an EMX1-cre line and postnatal day 1 intracerebroventricular vector injections of AAV.PHP.eB-EF1a-DIO-JEDI-1P-Kv2.1-WPR vector that restricted expression to excitatory cell bodies. We co-injected an AAV9-hsyn-mCherry vector in order to have a data preprocessing pipeline available where hemodynamic and movement artifacts could be regressed out using the mCherry signal. Pan-cortical voltage-imaging focused on layer 2/3 cell bodies was obtained in the adult mice after undergoing training in a cued forelimb water reaching task. Multiple sessions of imaging with 50-150 trials per session were obtained in 7 mice. Using temporal independent component analysis (tICA) we could reveal specific fast temporal dynamics in several overlapping cortical networks that were aligned to sensory cues, reward delivery, or reaching movements. Networks could also be defined through shared oscillatory dynamics. Prominent oscillations were found at around 8 Hz that were related to a task-disengaged quiescent state, and gamma oscillations at 40-60 Hz there spanned a bilateral cortical network related to reward processing. We also found that imaged activity in selected regions of interest could be used to decode the presented cues, or predict reaching behavior. Overall a picture emerged of highly integrated cortex-wide sensorimotor task processing with specific temporal dynamics in overlapping subnetworks.

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