Spike-timing Dependent Plasticity and Mutual Information Maximization for a Spiking Neuron Model. - Taro Toyoizumi; Jean-Pascal Pfister; Kazuyuki Aihara; Wulfram Gerstner (NIPS, 2004)

Generalization of the Mean-Field Method for Power-Law Distributions. - Taro Toyoizumi; Kazuyuki Aihara (Int. J. Bifurc. Chaos, 2006)

Optimal Spike-Timing-Dependent Plasticity for Precise Action Potential Firing in Supervised Learning. - Jean-Pascal Pfister; Taro Toyoizumi; David Barber; Wulfram Gerstner (Neural Comput., 2006)

Bayesian Inference Explains Perception of Unity and Ventriloquism Aftereffect: Identification of Common Sources of Audiovisual Stimuli. - Yoshiyuki Sato; Taro Toyoizumi; Kazuyuki Aihara (Neural Comput., 2007)

Optimality Model of Unsupervised Spike-Timing-Dependent Plasticity: Synaptic Memory and Weight Distribution. - Taro Toyoizumi; Jean-Pascal Pfister; Kazuyuki Aihara; Wulfram Gerstner (Neural Comput., 2007)

Mean-Field Approximations for Coupled Populations of Generalized Linear Model Spiking Neurons with Markov Refractoriness. - Taro Toyoizumi; Kamiar Rahnama Rad; Liam Paninski (Neural Comput., 2009)

Burst-Time-Dependent Plasticity Robustly Guides ON/OFF Segregation in the Lateral Geniculate Nucleus. - Julijana Gjorgjieva; Taro Toyoizumi; Stephen J. Eglen (PLoS Comput. Biol., 2009)

Nearly Extensive Sequential Memory Lifetime Achieved by Coupled Nonlinear Neurons. - Taro Toyoizumi (Neural Comput., 2012)

Blind Deconvolution of Hodgkin-Huxley neuronal model. - Milad Lankarany; Wei-Ping Zhu 001; M. N. S. Swamy; Taro Toyoizumi (EMBC, 2013)

Inferring trial-to-trial excitatory and inhibitory synaptic inputs from membrane potential using Gaussian mixture Kalman filtering. - Milad Lankarany; Wei-Ping Zhu 001; M. N. S. Swamy; Taro Toyoizumi (Frontiers Comput. Neurosci., 2013)

Advanced Mean Field Theory of Restricted Boltzmann Machine. - Haiping Huang; Taro Toyoizumi (CoRR, 2015)

Untangling Brain-Wide Dynamics in Consciousness by Cross-Embedding. - Satohiro Tajima; Toru Yanagawa; Naotaka Fujii; Taro Toyoizumi (PLoS Comput. Biol., 2015)

Unsupervised feature learning from finite data by message passing: discontinuous versus continuous phase transition. - Haiping Huang; Taro Toyoizumi (CoRR, 2016)

Simultaneous Bayesian Estimation of Excitatory and Inhibitory Synaptic Conductances by Exploiting Multiple Recorded Trials. - Milad Lankarany; Jaime E. Heiss; Ilan Lampl; Taro Toyoizumi (Frontiers Comput. Neurosci., 2016)

Redundancy in active paths of deep networks: a random active path model. - Haiping Huang; Alireza Goudarzi; Taro Toyoizumi (CoRR, 2017)

Reinforced backpropagation improves test performance of deep networks: a toy-model study. - Haiping Huang; Taro Toyoizumi (CoRR, 2017)

A theory of how active behavior stabilises neural activity: Neural gain modulation by closed-loop environmental feedback. - Christopher L. Buckley; Taro Toyoizumi (PLoS Comput. Biol., 2018)

Intrinsic Spine Dynamics Are Critical for Recurrent Network Learning in Models With and Without Autism Spectrum Disorder. - James Humble; Kazuhiro Hiratsuka; Haruo Kasai; Taro Toyoizumi (Frontiers Comput. Neurosci., 2019)

An Information-theoretic Progressive Framework for Interpretation. - Zhengqi He; Taro Toyoizumi (CoRR, 2021)

Dimensionality reduction to maximize prediction generalization capability. - Takuya Isomura; Taro Toyoizumi (Nat. Mach. Intell., 2021)

Publisher Correction: Dimensionality reduction to maximize prediction generalization capability. - Takuya Isomura; Taro Toyoizumi (Nat. Mach. Intell., 2021)

On the Achievability of Blind Source Separation for High-Dimensional Nonlinear Source Mixtures. - Takuya Isomura; Taro Toyoizumi (Neural Comput., 2021)

Learning poly-synaptic paths with traveling waves. - Yoshiki Ito; Taro Toyoizumi (PLoS Comput. Biol., 2021)

Spontaneous Emerging Preference in Two-tower Language Model. - Zhengqi He; Taro Toyoizumi (CoRR, 2022)

Continual growth and a transition. - Kenji Doya; Taro Toyoizumi; DeLiang Wang (Neural Networks, 2022)

Causal Graph in Language Model Rediscovers Cortical Hierarchy in Human Narrative Processing. - Zhengqi He; Taro Toyoizumi (CoRR, 2023)

Announcement of the Neural Networks Best Paper Award. - Taro Toyoizumi; DeLiang Wang (Neural Networks, 2023)

Another bumper year. - Taro Toyoizumi; DeLiang Wang (Neural Networks, 2023)

Progressive Interpretation Synthesis: Interpreting Task Solving by Quantifying Previously Used and Unused Information. - Zhengqi He; Taro Toyoizumi (Neural Comput., 2023)

A provable control of sensitivity of neural networks through a direct parameterization of the overall bi-Lipschitzness. - Yuri Kinoshita; Taro Toyoizumi (NeurIPS, 2024)

Expansion of the editorial team. - DeLiang Wang; Mauro Forti; Tongliang Liu; Taro Toyoizumi (Neural Networks, 2024)

A surge of submissions. - Taro Toyoizumi; DeLiang Wang (Neural Networks, 2024)