ePoster, Bernstein Conference 2024
Short-Distance Connections Enhance Neural Network Dynamics
- Goethe University, Frankfurt, Germany
- DOI 10.12751/nncn.bc2024.236 (opens in a new tab)
- Computational Neuroscience, Biophysics and
Poster
Poster audio
Abstract
Physical constraints in the brain result in most connections being short and distance-dependent. Despite this, how can short-distance connections facilitate long-distance signal transfer?
In our study, we explore networks with balanced excitation and inhibition, demonstrating that short-distance connections increase the number of common presynaptic inputs through spatial clustering. This topological feature enhances the correlations of neural responses. Strengthened recurrent correlations can lead to bursting states, which amplify postsynaptic neuron activity and support the propagation of signals over long distances within the network.
These findings suggest that, while short distance-dependent connections in cortical networks may arise from cost constraints, they also play a crucial role in facilitating global signal propagation. This enhances our understanding of how brain network structures contribute to their functional capabilities.
Keywords: Short-Distance Connections, Burst Activity, Signal Propagation
Topics
- short-distance connections, search World Wide
- balanced excitation and inhibition, search World Wide
- spatial clustering, search World Wide
- common presynaptic inputs, search World Wide
- recurrent correlations, search World Wide
- bursting states, search World Wide
- postsynaptic neuron activity, search World Wide
- cortical networks, search World Wide
Details
- Citation
- Mohmmad Sharif Hussainyar, Dong Li, Claus Hilgetag (2024). Short-Distance Connections Enhance Neural Network Dynamics. Bernstein Conference 2024. https://doi.org/10.12751/nncn.bc2024.236 (opens in a new tab)