Shuntaro Aoki

This paper decodes 3D object structure from human visual cortex activity using a pretrained 3D autoencoder and shows cross-cue generalization across depth cues and object categories.

This study reconstructs visual illusory experiences from brain activity using a decoding technique and deep neural networks, showing that reconstructions match illusory percepts.

The paper introduces a brain hierarchy score to measure how brain-like deep neural networks are, finding that high-performance networks are not necessarily brain-like.

The paper decodes deep neural network features from human brain activity using fMRI data and presents a dataset showing correlations in decoding accuracy across subjects.

This study links microstructural properties of the vertical occipital fasciculus to variability in human stereoacuity using diffusion and quantitative MRI.

This study introduces sparse ordinal logistic regression (SOLR) for decoding ordinal variables from brain data, showing improved performance over existing methods.