This project studies whether and how cortical interneuron circuits can support a flexible integration of different streams of sensory information. Our hypothesis is that these circuits enable a dynamic redistribution of inhibition, which in turn enables a dynamic re-weighting of different sources of information in line with the sensory context. To explore this, we will develop computational models of interneuron circuits, which are optimised for sensory processing using tools from machine learning. This research is in collaboration with Johannes Letzkus, Julia Veit, and James Poulet, our experimental partners in the CRC, who will supply biological constraints and data to benchmark the circuit models’ behaviour.
Funded by the Deutsche Forschungsgemeinschaft
(DFG, German Research Foundation)
TRR 384/1 2024, 514483642
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