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Detecting causality based on state space reconstruction from interspike intervals for neural spike trains

Kazuya Sawada*

Yutaka Shimada†

Tohru Ikeguchi‡

  • Department of Information and Computer Technology, Faculty of Engineering, Tokyo University of Science, Niijuku 6–3–1, Katsushika-ku, Tokyo 125–8585, Japan

  • Department of Information and Computer Sciences, Graduate School of Science and Engineering, Saitama University, 255 Shimo-Okubo, Sakura-ku, Saitama-shi, Saitama 338–8570, Japan

  • Department of Information and Computer Technology, Faculty of Engineering, Tokyo University of Science, Niijuku 6–3–1, Katsushika-ku, Tokyo 125—8585, Japan

  • *Contact author: sawada@hisenkei.net
  • †Contact author: yshimada@mail.saitama-u.ac.jp
  • ‡Contact author: tohru@rs.tus.ac.jp

Reconstruction of interpretable causal network dynamics from time series data

Xiangyun Gao, Xiaotian Sun, Tao Wu, Sufang An, Feng An, Siyang Leng, Hongyu Wei, Yupeng Zhang, Norbert Marwan, and Jürgen Kurths

Physics Reports 1203 1 (2027)

Inter-Spike Interval statistics of a chaotic spiking neuron with Piecewise Constant dynamics: Theoretical and experimental approaches

Yuta Morimitsu and Tadashi Tsubone

NOLTA 17 1225 (2026)

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