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This content will become publicly available on November 29, 2022

Title: Markov Chain Abstractions of Electrochemical Reaction-Diffusion in Synaptic Transmission for Neuromorphic Computing
Progress in computational neuroscience toward understanding brain function is challenged both by the complexity of molecular-scale electrochemical interactions at the level of individual neurons and synapses and the dimensionality of network dynamics across the brain covering a vast range of spatial and temporal scales. Our work abstracts an existing highly detailed, biophysically realistic 3D reaction-diffusion model of a chemical synapse to a compact internal state space representation that maps onto parallel neuromorphic hardware for efficient emulation at a very large scale and offers near-equivalence in input-output dynamics while preserving biologically interpretable tunable parameters.
Authors:
; ; ;
Award ID(s):
2019745
Publication Date:
NSF-PAR ID:
10326452
Journal Name:
Frontiers in Neuroscience
Volume:
15
ISSN:
1662-453X
Sponsoring Org:
National Science Foundation
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