Speaker
Description
Information from the sensory periphery is conveyed to the cortex via structured projection pathways that spatially segregate stimulus features, providing a robust and efficient encoding strategy. Beyond sensory encoding, this prominent anatomical feature extends throughout the neocortex. However, the extent to which it influences cortical processing is unclear.
In this study, we combine cortical circuit modeling with network theory to demonstrate that the sharpness of topographic projections acts as a bifurcation parameter, controlling the macroscopic dynamics and representational precision across a large modular circuit of spiking neurons comprising multiple sub-networks. By shifting the balance of excitation and inhibition, topographic modularity gradually increases task performance and improves the signal-to-noise ratio across the system.
Using mean-field approximations, we gain deeper insight into the mechanisms responsible for the qualitative changes in the system's behavior and show that these depend only on the modular topographic connectivity and stimulus intensity. We show that this is a robust and generic structural feature that enables a broad range of behaviorally-relevant operating regimes: maintaining stable representations of multiple stimuli across cortical circuits; amplifying certain features while suppressing others, resembling winner-take-all circuits; and endow circuits with metastable dynamics (winnerless competition), assumed to be fundamental in a variety of tasks.
Acknowledgements
This work has received partial support from the the Initiative and Networking Fund of the Helmholtz Association, the Helmholtz Portfolio theme Supercomputing and Modeling for the Human Brain, and the Excellence Initiative of the German federal and state governments (G:(DE-82)EXS-SF-neuroIC002). In addition, the authors gratefully acknowledge the computing time granted by the JARA-HPC Vergabegremium on the supercomputer JURECA at Forschungszentrum Jülich.
| Preferred form of presentation | Talk & (optional) poster |
|---|---|
| Topic area | models and applications |
| Keywords | modularity, spiking networks, denoising, topography |
| Speaker time zone | UTC+2 |
| I agree to the copyright and license terms | Yes |
| I agree to the declaration of honor | Yes |
