Ying Joey Zhou

The paper introduces a data-driven framework to model oscillatory neural networks with condition-dependent coupling laws, identifying directed pathways in working memory attention dynamics using MEG data.

The paper shows that human working memory representations in cortex are probabilistic, with neural variance encoding memory uncertainty and predicting behavior.

The paper investigates how distinct alpha brain networks influence perceptual decision-making by analyzing MEG data during a visual detection task, finding that the visual alpha network modulates sensitivity while the sensorimotor alpha network modulates criterion.

This study investigates sequential working memory using MEG data, finding that neural subspaces organize memory during retention but not during encoding, while no sequential replay was observed.

The paper investigates how brain rhythms in the 1-30 Hz range influence information processing during a working-memory task using MEG data from human participants.

This study investigates whether attention and working memory share neural mechanisms by showing that brain activity patterns during external and internal selection are interchangeable.

This study shows that pre-stimulus alpha-band activity in occipital-parietal regions enhances perceptual sensitivity and information content in visual detection tasks.