Hayato Idei

The paper uses a hierarchical generative model to analyze brain-body interaction dynamics during interoceptive attention, finding increased latent precision in multimodal physiological signals.

This paper introduces a Bayesian recurrent neural network model that autonomously switches between goal-directed and sensory-focused behaviors to adapt to environmental changes.

This paper introduces a real-time ECoG simulator using a Variational Bayesian Recurrent Neural Network to predict and update brain states from primate data, enabling virtual drug administration and functional network analysis.