Manabu Honda

This study uses a homeostatic reinforcement learning model to simulate how altered interoception affects reward processing and appetite in depression subtypes.

This paper introduces a self-supervised deep learning method for resting-state fMRI analysis, showing improved schizophrenia diagnosis compared to conventional methods.

The paper investigates how humans self-regulate cortical oscillations during brain-computer interface tasks, finding that basal ganglia-cortical connectivity plays a key role in this process.

This paper applies a 3D convolutional autoencoder to structural brain MRI data from schizophrenia and healthy subjects to extract disease-related features without diagnostic labels.