Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.10.27.358390v1?rss=1 Authors: Wagner, M. S., Bartol, T. M., Sejnowski, T. J., Cauwenberghs, G. Abstract: Progress in computational neuroscience towards 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 the 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 on very large scale, and offers near-equivalence in input-output dynamics while preserving biologically interpretable tunable parameters. Copy rights belong to original authors. Visit the link for more info