Affective brain-computer interfaces require models that can integrate EEG information across frequency bands and brain regions while remaining interpretable. This work proposes an explainable multi-frequency and multi-region fusion network (MFMR-FN) …
This study investigates whether resting-state EEG signatures can predict the treatment efficacy of transcranial alternating current stimulation (tACS) for refractory auditory hallucinations in schizophrenia. Resting-state EEG data from patients were …
This project develops interpretable EEG fusion models that integrate multi-frequency and multi-region brain connectivity patterns for affective brain-computer interfaces.
This project investigates resting-state EEG signatures that can predict tACS treatment response for refractory auditory hallucinations in schizophrenia.
In this project, we used the fNIRS method to collect the resting state data of MDD, SCZ, and HC for the PFC region.