Imaging a Computational Process in the Visual Cortex. - Keisuke Toyama 001; Manabu Tanifuji (Neural Networks, 1996)

ICA for Noisy Neurobiological Data. - Shiro Ikeda; Keisuke Toyama 001 (IJCNN (4), 2000)

Independent component analysis for noisy data – MEG data analysis. - Shiro Ikeda; Keisuke Toyama 001 (Neural Networks, 2000)

Hierarchical Bayesian estimation for MEG inverse problem. - Masa-aki Sato; Taku Yoshioka; Shigeki Kajihara; Keisuke Toyama 001; Naokazu Goda; Kenji Doya; Mitsuo Kawato (NeuroImage, 2004)

Evaluation of hierarchical Bayesian method through retinotopic brain activities reconstruction from fMRI and MEG signals. - Taku Yoshioka; Keisuke Toyama 001; Mitsuo Kawato; Okito Yamashita; Shigeaki Nishina; Noriko Yamagishi; Masa-aki Sato (NeuroImage, 2008)

A hierarchical Bayesian method to resolve an inverse problem of MEG contaminated with eye movement artifacts. - Yusuke Fujiwara; Okito Yamashita; Dai Kawawaki; Kenji Doya; Mitsuo Kawato; Keisuke Toyama 001; Masa-aki Sato (NeuroImage, 2009)

Relating Neuronal Firing Patterns to Functional Differentiation of Cerebral Cortex. - Shigeru Shinomoto; Hideaki Kim; Takeaki Shimokawa; Nanae Matsuno; Shintaro Funahashi; Keisetsu Shima; Ichiro Fujita; Hiroshi Tamura; Taijiro Doi; Kenji Kawano; Naoko Inaba; Kikuro Fukushima; et al. (PLoS Comput. Biol., 2009)

Solution to the inverse problem of estimating gap-junctional and inhibitory conductance in inferior olive neurons from spike trains by network model simulation. - Miho Onizuka; Huu Hoang; Mitsuo Kawato; Isao T. Tokuda; Nicolas Schweighofer; Yuichi Katori; Kazuyuki Aihara; Eric J. Lang; Keisuke Toyama 001 (Neural Networks, 2013)

Segmental Bayesian estimation of gap-junctional and inhibitory conductance of inferior olive neurons from spike trains with complicated dynamics. - Huu Hoang; Okito Yamashita; Isao T. Tokuda; Masa-aki Sato; Mitsuo Kawato; Keisuke Toyama 001 (Frontiers Comput. Neurosci., 2015)

Electrical coupling controls dimensionality and chaotic firing of inferior olive neurons. - Huu Hoang; Eric J. Lang; Yoshito Hirata; Isao T. Tokuda; Kazuyuki Aihara; Keisuke Toyama 001; Mitsuo Kawato; Nicolas Schweighofer (PLoS Comput. Biol., 2020)

Predictive reward-prediction errors of climbing fiber inputs integrate modular reinforcement learning with supervised learning. - Huu Hoang; Shinichiro Tsutsumi; Masanori Matsuzaki; Masanobu Kano; Keisuke Toyama 001; Kazuo Kitamura; Mitsuo Kawato (PLoS Comput. Biol., 2025)