NPTL

We conduct neuroscience, neuroengineering and translational research to better understand how the brain controls movement and to design medical systems to assist people with paralysis. These medical systems are referred to as brain-computer interfaces (BCIs), brain-machine interfaces (BMIs) and intracortical neural prostheses. The Neural Prosthetics Translational Lab (NPTL) is co-directed by Prof. Jaimie Henderson and Assistant Prof. Frank Willett. NPTL continues to carry on the legacy of Krishna Shenoy, who passed away in 2023.

Our modeling and computational work benefits from collaborations with Associate Prof. Shaul Druckmann (Department of Neurobiology, Stanford), Assistant Prof. Scott Linderman (Department of Statistics, Stanford) and Adjunct Prof. David Sussillo (Director, CTRL-Labs West Coast, a division of Reality Labs / Meta Platforms). Our work is done as part of various NIH BRAIN, NINDS and NIDCD awards, a Simons Foundation Collaboration on the Global Brain (SCGB) program and the BrainGate2 clinical trial. 

Neuroscience    We investigate the neural basis of movement and language using Utah microelectrode arrays and computational and theoretical methods (e.g., dimensionality reduction, dynamical systems, single-trial neural trajectory analysis, recurrent neural networks, deep neural networks). Questions include:

1. How are movement representations distributed across human motor cortex? Our recent findings show unexpected patterns, including the representation of all body parts at any single location in motor cortex. 

2. How do neurons in motor cortex generate arm, hand and finger movements? Including attempted movements made by people with paralysis, which form the foundation for new classes of BCIs. For example, as reported in Willett et al. (2021) Nature, an Attempted Handwriting BCI (see concept sketch below).

3. How do neurons in motor cortex and inferior frontal gyrus (“Broca's area”) prepare and generate speech movements? Including attempted speech movements, which form the foundation for new classes of BCIs. For example, as reported in Willett*, Kunz*, Fan* et al. (2023) Nature, an Attempted Speech BCI (see concept sketch below)

Neuroengineering     We investigate the design of high-performance and highly-robust BCIs. This work includes statistical signal processing, machine learning and real-time system design. Questions include how to automatically recalibrate neural decoders in the face of changing neural signals (Fan et al. 2023), and how to more accurately decode neural activity into words (Willett et al. 2024).

Translational     We investigate BCI clinical translation and highly-related human neuroscience questions through the multi-site clinical trial that we are a part of (Timeline on BrainGate2, NCT00912041 on clinicaltrials.gov). Questions include how best to bring neuroscience discoveries into clinically-viable BCIs to help people with paralysis in real-world settings (i.e., translation), and how to design BCIs that meet the needs of users (including our recent work on restoring high degree of freedom digital control). 

Here is a brief PBS News Hour video by Cat Wise and Judy Woodruff describing our Computer Cursor BCI that translates neural activity from the motor cortex of volunteer clinical trial participants into control signals to guide an on-screen cursor in two dimensions as well as a click signal, which is used to make selections (e.g., select a key on a keyboard). We reported this system in Pandarinath*, Nuyujukian*, et al. eLife 2017.

Another brief video, by Megan Rosen at HHMI, describes how an Attempted Handwriting BCI translates neural activity from the motor cortex of volunteer clinical trial participants into the most probable English letter (26) or special character (5) in order to type words and sentences thereby restoring the ability to communicate. Note that any word can be typed and, therefore, this is an open vocabulary system. We reported this system in Willett et al. Nature 2021.

Finally, our recent work on a Speech BCI, reported in Willett et al. Nature 2023, was recently featured on the Today Show.