PI: Shawn Kelly, Engineering Research Accelerator
Co-PI(s): Pulkit Grover, Jeff Weldon, Marlene Behrman, Michael Tarr
Electrical and Computer Engineering, Psychology

High‐resolution dynamic recording of neural activity can help millions of Americans suffering from neurological diseases and injuries improve their function, mobility, independence, and overall quality‐of‐life. In addition, such high‐resolution recording can pave the way for new discoveries in brain monitoring, such as in concussion detection, disease detection, and early detection of child developmental disorders.  It is widely believed that Electroencephalography (EEG)—which measures “brain waves” in a noninvasive, inexpensive, and safe manner using electrodes applied to the scalp surface—cannot yield high‐resolution imaging of the brain activity. Challenging this belief, our research team brought together concepts from information theory, fundamental physics, and neuroscience to show that the classical theoretical results are misleading, and could be severely pessimistic on the potential of high‐density EEG systems. This leads to the hypothesis that increasing the number and/or density of electrodes can dramatically improve EEG’s imaging resolution, which we are able to verify through preliminary experiments. Our overall goal is to create the “Neural Web” (shown in the figure at right), a wearable, wireless, high‐density EEG system that can not only simplify clinical diagnostics and reduce health care costs, but also enable research into new methods of non‐invasive brain‐machine interfaces. Specifically, the research proposed here will create the  recording system, optimize the electrode design, and create the wireless communication system, capable of relaying all of the recorded data from the high‐density EEG to a base station, allowing the user to move freely.