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Neural encoding & decoding of rapid, dexterous motor sequences to help people with disabilities

By investigating the natural motor control system and brain-computer interface (BCI) designs concurrently it is possible to gain new and different insights on both (top row). Electrode arrays are neurosurgically placed in motor-related cortical areas and various behavioral tasks are used to measure and interpret neural activity (2nd row, left to right). Many different BCIs, also termed brain-machine interfaces (BMIs) are possible, including full-body functional electrical stimulation (FES) or (soft) exoskeletons, attempted-handwriting BCIs, speech BCIs and 2D cursor point-and-click BCIs (3rd row, left to right). As an example of the close relationship between computational and systems neuroscience and BCI design, it is possible to understand how motor cortical neural populations encode upcoming movement segments (staight and curved) and relate them to letter writing, and then use this knowledge to decode attempted handwritting letters in order to provide high-performance BCIs (bottom row, left to right).  Illustration credit: Erika Woodrum. High-resolution version of the cover: pdf

The Stanford Neural Prosthetics Translational Laboratory (NPTL) conducts research aimed at providing clinically useful brain-machine interfaces (also termed brain-computer interfaces)  for people with paralysis, and understanding the related underlying human neuroscience (i.e., studying populations of individual neurons). Our goal is to extract signals (information) recorded from electrodes surgically implanted in the brain to provide accurate, high-speed, and robust control of assistive technologies. More specifically, we investigate neural encoding and decodig of rapid, highly-dexterous movement sequences to help people with disabilities. 

Current projects include design and validation of high-performance and highly-robust systems that:

  1. Generate text to help restore communication by decoding attempted handwriting: "Brain-to-Text BCIs" (Willett et al. Nature 2021 pdf).
  2. Generate speech to help restore communication by decoding attempted speech: "Brain-to-Speech BCIs" (Stavisky et al. eLife 2019 pdf, Stavisky et al. J Neural Eng 2020 pdf, Wilson*, Stavisky* et al. J Neural Eng 2020 pdf).
  3. Generate full body (both arms, both legs) control signals to help restore arm and leg movements: "Full-body BCIs" (Willett*, Deo* et al. Cell 2020 pdf)
  4. Control of 2D point-and-click cursors to help restore computer, tablet and phone operation: "2D point-and-click BCIs" (Pandarinath*, Nuyujukian* et al. eLife 2017 pdf; Nuyujukian et al. PLoS One 2018 pdf).
  5. Fundamental neuroscience investigations of these uniquely human, high-speed and highly-dexterous movement sequences employing single-neuron resolution ensemble recordings.
  6. Advancing analytical methods: Computation Through Dynamics (CTD; Vyas et al. Ann Rev Neurosci 2020 pdf) and Dynamical Systems Framework (DSF; Shenoy et al. Ann Rev Neurosci 2013 pdf) experiments and analyses.

Projects are supported by the National Institutes of Health (NIH) NIDCD, NINDS & BRAIN Initiative. As well as by the Simons Foundation and the Howard Hughes Medical Institue (HHMI; Investigator Krishna Shenoy).

NPTL is co-directed by Professor Jaimie Henderson, MD  (Neurosurgery and, by courtesy, Neurology) and Professor Krishna Shenoy, PhD. (EE and, by courtesy, BioE and Neurobiology; HHMI Investigator), and NPTL is part of the Wu Tsai Neurosciences Institute and Bio-X Institute.


Last modified: 
Sunday, August 15, 2021 - 20:47