Markov chain abstractions of electrochemical reaction-diffusion in synaptic transmission for neuromorphic computing

Abstract

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.

Margot Wagner

Postdoctoral Researcher

Interested in the use of data science and AI in mental health and using neuroscience to inspire next generation AI tools.