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Main Authors: Chen, Kevin S., Yang, Ying-Jen
Format: Preprint
Published: 2024
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Online Access:https://arxiv.org/abs/2405.15206
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author Chen, Kevin S.
Yang, Ying-Jen
author_facet Chen, Kevin S.
Yang, Ying-Jen
contents The characterization of network and biophysical properties from neural spiking activity is an important goal in neuroscience. A framework that provides unbiased inference on causal synaptic interaction and single neural properties has been missing. Here we applied the stochastic dynamics extension of Maximum Entropy -- the Maximum Caliber Principle -- to infer the transition rates of network states. Effective synaptic coupling strength and neuronal response functions for various network motifs can then be computed. The inferred minimal model also enables leading-order reconstruction of inter-spike interval distribution. Our method is tested with numerical simulated spiking networks and applied to data from salamander retina.
format Preprint
id arxiv_https___arxiv_org_abs_2405_15206
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Maximum Caliber Infers Effective Coupling and Response from Spiking Networks
Chen, Kevin S.
Yang, Ying-Jen
Neurons and Cognition
Biological Physics
The characterization of network and biophysical properties from neural spiking activity is an important goal in neuroscience. A framework that provides unbiased inference on causal synaptic interaction and single neural properties has been missing. Here we applied the stochastic dynamics extension of Maximum Entropy -- the Maximum Caliber Principle -- to infer the transition rates of network states. Effective synaptic coupling strength and neuronal response functions for various network motifs can then be computed. The inferred minimal model also enables leading-order reconstruction of inter-spike interval distribution. Our method is tested with numerical simulated spiking networks and applied to data from salamander retina.
title Maximum Caliber Infers Effective Coupling and Response from Spiking Networks
topic Neurons and Cognition
Biological Physics
url https://arxiv.org/abs/2405.15206