Mean Field Approach for Configuring Population Dynamics on a Biohybrid Neuromorphic System

Johannes Partzsch; Christian Mayr; Massimiliano Giulioni; Marko Noack; Stefan Hänzsche; Stefan Scholze; Sebastian Höppner; Paolo Del Giudice; Rene Schüffny

arXiv · 1904.10389

Mean Field Approach for Configuring Population Dynamics on a Biohybrid Neuromorphic System

Johannes Partzsch·Christian Mayr·Massimiliano Giulioni·Marko Noack·Stefan Hänzsche·Stefan Scholze·Sebastian Höppner·Paolo Del Giudice·Rene Schüffny

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Abstract

Real-time coupling of cell cultures to neuromorphic circuits necessitates a neuromorphic network that replicates biological behaviour both on a per-neuron and on a population basis, with a network size comparable to the culture. We present a large neuromorphic system composed of 9 chips, with overall 2880 neurons and 144M conductance-based synapses. As they are realized in a robust switched-capacitor fashion, individual neurons and synapses can be configured to replicate with high fidelity a wide range of biologically realistic behaviour. In contrast to other exploration/heuristics-based approaches, we employ a theory-guided mesoscopic approach to configure the overall network to a range of bursting behaviours, thus replicating the statistics of our targeted in-vitro network. The mesoscopic approach has implications beyond our proposed biohybrid, as it allows a targeted exploration of the behavioural space, which is a non-trivial task especially in large, recurrent networks.

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Johannes Partzsch, Christian Mayr, Massimiliano Giulioni, Marko Noack, Stefan Hänzsche, Stefan Scholze, Sebastian Höppner, Paolo Del Giudice, Rene Schüffny. 2019-04-23. Mean Field Approach for Configuring Population Dynamics on a Biohybrid Neuromorphic System. https://arxiv.org/abs/1904.10389

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