Objective and efficient inference for couplings in neuronal networks

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

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Yu Terada, Tomoyuki Obuchi, Takuya Isomura, Yoshiyuki Kabashima


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.