Haiteng Wang

This study identifies brain-wide activation patterns during sleep rhythms using EEG and fMRI, showing thalamus and hippocampus involvement in memory processes.

This study shows that hippocampal ripples prioritize high-value, unvisited options during model-based learning by coordinating with the lateral frontopolar cortex.

The paper introduces Du-IN-v2, a pre-training framework for speech decoding from intracranial neural signals, achieving state-of-the-art performance using region-level token embeddings and discrete codex-guided mask modeling.

The paper develops a neural network model, Sleep Interpreter (SI), to decode memory replay from sleep EEG and shows it can accurately detect reactivation during sleep that correlates with memory performance.

This study uses EEG to investigate offline learning mechanisms, finding that backward replay strength correlates with trait anxiety and reward preference.