We investigate ADRD, including Alzheimer’s disease and Lew Body dementia, by integrating neuroimaging (MRI, fMRI, DTI, PET) and electrophysiology (MEG and EEG) data with AI-driven machine learning to reveal novel insights into disease mechanisms and progression.
Using a multi-modal approach that integrates MEG, and intracranial EEG (sEEG & ECoG), we investigate the brain regions and networks involved in language processing to gain deeper insights into this complex cognitive function.
An active area of the iBRAIN lab is to use brain connectivity analysis, graph theory, and machine learning in the diagnosis and prognosis of epilepsy and other neurological conditions.
Our brain-computer interface (BC) for language decoding leverages advanced deep learning techniques, particularly large language models (LLMs) to translate neural activity into meaningful language outputs.
