Matt Willsey grew up in Greenwood, Indiana. He attended MIT, where he received B.S. and M.Eng degrees in Electrical Engineering with a research focus in digital signal processing. He attended medical school at Baylor College of Medicine in Houston. He completed his neurosurgery residency at the University of Michigan in 2022. Matt completed the enfolded CAST-approved fellowship in Stereotactic and Functional Neurosurgery and completed a PhD in Biomedical Engineering during his 2-year protected research time with an additional year long leave-of-absence. His clinical interests include deep brain stimulation, epilepsy, pain, and spine. His dissertation research with Drs. Parag Patil and Cynthia Chestek focuses on restorative neuroengineering, including intraoperative modulation of sensorimotor pathways, the effects of anesthetics on cortical signal flow, and brain-machine interface neuroprosthetics.
Clinical Instructor, Neurosurgery
Residency: University of Michigan Dept of Neurosurgery (2022) MI
PhD, University of Michigan, Biomedical Engineering (2020)
Fellowship: University of Michigan Dept of Neurosurgery (2019) MI
Medical Education: Baylor College of Medicine (2014) TX
A low-power band of neuronal spiking activity dominated by local single units improves the performance of brain-machine interfaces.
Nature biomedical engineering
The large power requirement of current brain-machine interfaces is a major hindrance to their clinical translation. In basic behavioural tasks, the downsampled magnitude of the 300-1,000 Hz band of spiking activity can predict movement similarly to the threshold crossing rate (TCR) at 30 kilo-samples per second. However, the relationship between such a spiking-band power (SBP) and neural activity remains unclear, as does the capability of using the SBP to decode complicated behaviour. By using simulations of recordings of neural activity, here we show that the SBP is dominated by local single-unit spikes with spatial specificity comparable to or better than that of the TCR, and that the SBP correlates better with the firing rates of lower signal-to-noise-ratio units than the TCR. With non-human primates, in an online task involving the one-dimensional decoding of the movement of finger groups and in an offline two-dimensional cursor-control task, the SBP performed equally well or better than the TCR. The SBP may enhance the decoding performance of neural interfaces while enabling substantial cuts in power consumption.
View details for DOI 10.1038/s41551-020-0591-0
View details for PubMedID 32719512