Assistant Professor of Neurology
Adeen Flinker received a BA in Computer Science from Technion, Israel Institute of Technology, a PhD in Neuroscience from the University of California at Berkeley and he completed his post-doctoral research at New York University. He joined the New York University School of Medicine as an Assistant Professor of Neurology in 2017. He has appointments with the NYU Neuroscience Institute, NYU Biomedical Engineering and NYU Cognition and Perception.
The lab's research focuses on the electrophysiology of speech perception and production. He leverages behavioral, non-invasive and invasive electrophysiology in humans to tackle basic questions in the perception and production of speech and language. While most human research methodologies are limited to non-invasive techniques such as EEG (Electroencephalography) and fMRI (functional Magnetic Resonance Imaging) the Flinker lab focuses on collaborative research with rare neurosurgical patients undergoing treatment for refractory epilepsy. These patients are implanted with intracranial electrode grids placed directly on the surface of the brain for a one-week period in order to monitor and localize epileptogenic activity. While the electrode placement is driven solely by clinical necessity, during lulls in clinical care there is a unique opportunity to conduct cognitive tasks with patients in the hospital while Electrocorticographic (ECoG) signals are being collected directly from cortex. These neural signals provide an aggregate measure of neural excitability with combined temporal and spatial resolution. The focus of the research in the lab is to employ various experimental, machine learning and signal processing approaches to elucidate speech networks based on neural signals recorded directly from human cortex. Our goal is to further our understanding of how the human cortex supports speech perception and production while providing better tools for clinicians to map function prior to surgery.
Research Interests: Speech, Language, Machine Learning, Neurophysiology