Mattia Rigotti
BME PhD Proposal Presentation

Date: 2023-09-15
Time: 2:30pm ET
Location / Meeting Link: HSRB-II N600 / https://emory.zoom.us/j/93792014426?pwd=RVRQZVZYb2FQYVRLZHAyMmp2RjdGQT09

Committee Members:
Chethan Pandarinath, PhD (advisor); Nicholas Au Yong, MD, PhD; Jonathan Kao, PhD; Garrett Stanley, PhD; Anqi Wu, PhD

Title: Leveraging movement goal encoding from the human motor cortex for high performance brain-computer interface control

Abstract:
There are over 10,000 new cases of tetraplegia every year in the US, a condition that severely impairs a person’s ability to move their limbs and greatly reduces their quality of life. Intracortical brain-computer interfaces (iBCIs) are a promising avenue that allow individuals with tetraplegia to regain movement capabilities, by recording neural activity from implants in their brain and translating these signals into intended actions. Despite significant advances over the years, iBCI control performance still falls short compared to that of able-bodied behavior. A reason for this is that standard iBCI control paradigms rely on decoding instantaneous behavioral variables from neural activity, which is a noisy process. This limits control performance, since users must continuously correct for decoder errors. In this proposal, I aim to improve iBCI performance through a novel control paradigm that instead predicts the goal position of a user’s intended movements. I will first evaluate how neural activity within the human motor cortex encodes parameters characterizing the goal position of intended movements (Aim 1). I will then implement a control paradigm that leverages movement goal encoding for fast and accurate online iBCI control (Aim 2). Additionally, to assist in future efforts for designing iBCI controllers that decode variables other than instantaneous behavioral variables, I will develop a tool that generates synthetic neural activity simulating recordings from human iBCI participants (Aim 3). Altogether, I expect this proposal will provide valuable insight on movement goal encoding within the human motor cortex, as well as make iBCIs more viable as a method for restoring movement capabilities to individuals with tetraplegia