Our neuroscience research investigates the neural basis of movement preparation and generation using a combination of electro- / opto-physiological (e.g., chronic electrode-array recordings and optogenetic stimulation), behavioral, computational and theoretical techniques (e.g., dynamical systems, dimensionality reduction, single-trial neural analyses). For example, how do neurons in premotor (PMd) and primary motor (M1) cortex plan and guide reaching arm movements?, which focuses on more translational systems and computational neuroscience and neuroengineering.
Our neuroengineering research investigates the design of high-performance and robust intra-cortical neural prostheses. These systems translate neural activity from the brain into control signals for prosthetic devices, which can assist people with paralysis by restoring lost motor functions. This work includes statistical signal processing, machine learning, and real-time system modeling and implementation. For example, how can we design motor prostheses with performance rivaling the natural arm, or communication prostheses rivaling the throughput of spoken language.
Our translational research including an FDA pilot clinical trial (BrainGate2) is conducted as part of the NPTL
. For example, how do pre-clinical laboratory designs actually work with people with paralysis in real-world settings?
Figure 1. Various neural measurement and perturbation techniques, mathematical analysis methods and real-time closed-loop brain-computer interface (BCI) systems approaches advanced in order to better understand how populations of cortical neurons coordinate and cooperate to prepare, generate and control movement. (a) NeuroPixel electrode array (with 960 electrodes, 384 simultaneously recordable) probe and multiplexing electronics (HHMI & IMEC). (b) Voltage vs. time traces from 184 (of 384) electodes from a NeuroPixel probe in an awake-behaving rhesus monkey, showing how neurons' action potentials are seen on multiple electrodes which facilitates high-quality spike sorting. (c) Optogenetics in rhesus monkeys for increasing or decreasing activity in specific neurons. (d) 2-photon (GCaMP6f) optical recordings from reaching rhesus monkeys, with reach directional tuning (2D color wheel shows reach direction) of example neurons overlaid in color. (e) These methods (and Utah arrays and U/V/S linear probes) allow information to be read out and written into the rhesus monkey brain. (f) In both monkeys and in people, the number of action potentials in a short time period, across all measured neurons, constitutes a neural state and can be plotted in a neuron firing-rate space or, more generally, in a lower-dimensional space such as PCA, GPFA or dPCA. (g) This neural state evolves in time and forms a neural trajectory. (h) The neural population dynamics, formed by the underlying neural network circuitry, can be expressed as a neural flow field. The neural flow field express the system dynamics which can be modeled as a linear dynamical system (LDS) or non-linear dynamical system such as a recurrent neural network (RNN). Neural states remain in a muscle-null space while preparing a reach, and then enter muscle-potent space to generate the movement These movement dynamics have a substantial time-limited rotatory component. (i) The initial conditions influence the neural trajectory. (j) A neural state starts at some initial-condition location, and then moves as dictated by the neural flow field (assuming no inputs). (k) If the initial-condition location is perturbed, by changing the task or by electrical or optical stimulation, a different (perturbed) neural trajectory results. (l) If the input to the dynamical system is changed, then the dynamics are changed, and cause the same initial-condition location to follow different neural trajectories. (m) A Utah electrode array (Blackrock Microsystems Inc.), used in rhesus monkeys and in human clinical trials. (n) Top to bottom: action potential (spike) rasters from one delayed-reach trial, spike clustering in PCA (or similar) space and sorting, and one example voltage vs. time trace. (o) Two electrode array locations marked on a scaled-down 3D printed brain based on imaging from participant T5, with signals related to many/most body parts and to speech production. (p) Illustration of a BCI that measures neural activity, translates this neural activity into movement control signals using a variety of statistical-signal processing decoding algorithms, and uses these control signals to guide robotic/prosthetic arms and hands, electrically stimulate paralyzed musculature, and guide computer cursors and click signals on general-purpose computer interfaces .
"Brain in Violet" by Dr. Greg Dunn. Please consider helping support the Arts & Humanities (at individual, university, city, state & federal levels) so they (SHTEAM) may grow together with STEM.