Method for analyzing time-varying statistics on point process data with multiple trials

Kantaro Fujiwara; Hideyuki Suzuki; Tohru Ikeguchi; Kazuyuki Aihara

doi:10.1587/nolta.6.38

Special Section on Complex Systems Modelling and its Transdisciplinary Applications

Method for analyzing time-varying statistics on point process data with multiple trials

Kantaro Fujiwara, Hideyuki Suzuki, Tohru Ikeguchi, Kazuyuki Aihara

著者情報

キーワード: time-series analysis, statistics, time-variability, neuroscience, neural coding

ジャーナルフリー

2015 年 6 巻 1 号 p. 38-46

DOI https://doi.org/10.1587/nolta.6.38

詳細

抄録

Many stochastic systems require multiple trials to estimate their time-varying statistics. Time-varying statistics are often estimated by employing a time window of a certain length over trials. However, no standardized method exists for estimating time-varying statistics. In this paper, we propose an analysis method for measuring time-varying statistics that can be applied to point process data with multiple trials, such as neural spike trains.

責任著者(Corresponding author)

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