Objective and efficient inference for couplings in neuronal networks

Part of Advances in Neural Information Processing Systems 31 (NeurIPS 2018)

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Authors

Yu Terada, Tomoyuki Obuchi, Takuya Isomura, Yoshiyuki Kabashima

Abstract

Inferring directional couplings from the spike data of networks is desired in various scientific fields such as neuroscience. Here, we apply a recently proposed objective procedure to the spike data obtained from the Hodgkin-Huxley type models and in vitro neuronal networks cultured in a circular structure. As a result, we succeed in reconstructing synaptic connections accurately from the evoked activity as well as the spontaneous one. To obtain the results, we invent an analytic formula approximately implementing a method of screening relevant couplings. This significantly reduces the computational cost of the screening method employed in the proposed objective procedure, making it possible to treat large-size systems as in this study.