T&C Chen Brain-Machine Interface Center
Richard Andersen (Director)
The T&C Chen Brain-Machine Interface Center, led by Richard Andersen, is advancing Caltech's work on a new generation of devices that can directly communicate with the brain. These neuroprosthetics enable people with paralysis to control robotic limbs and computer interfaces by simply thinking about moving. Similarly, these devices can stimulate the brain to restore the senses of touch and movement previously lost due to brain disease or injury. The Chen BMI Center not only provides the infrastructure and coordination for researchers to develop these devices, but also fosters a multi-disciplinary and comprehensive scientific environment for scientists.
Upper left, participant EGS (right) with Tyson Aflalo; lower left, participant NS (right) with Spencer Kellis; right, Richard Andersen (right) with Charles Liu.
The Chen Brain-Machine Interface (BMI) center supports researchers working on several projects that advance neuroprosthetic technology. In one FDA approved clinical study, researchers are comparing neural signals from different brain regions that contribute to planning and executing movements. These studies build on the foundational science of intention, cognition, and perception to provide new insights into human brain function that enable the next generation of neural prosthetic interfaces. In another FDA approved clinical study, researchers at the Chen BMI Center aim to replace lost sensations by electrically stimulating the brain. This "bi-directional" brain-machine interface supplements the control of a robotic limb by delivering somatosensory feedback. This artificially induced sense of touch will allow more dexterous performance for patients controlling robotic limbs or exoskeletons.
The clinical and commercial success of brain-machine interfaces requires the development of novel technologies that are safer and more effective. To this end, the Chen BMI Center also supports the engineering, development, and study of several new technologies. One such project is developing chronically-implantable chips that record and translate brain activity into assistive control signals. The integration of neural signals with state-of-the art exoskeletons and robotic limbs will expand the ways patients can benefit from assistive implants. Finally, to expand the population of people who can benefit from BMI technology, the Chen BMI center supports translational studies of new, less-invasive, high-performance technologies in animal models and humans. One project is currently exploring the feasibility of using a novel ultrasound-based neuroimaging technique to "read" movement intention signals in a minimally invasive manner.
Ueli Rutishauser (Cedars, Caltech)
Ausaf Bari (UCLA) Nader Pouratian (UCLA)
Charles Liu and Brian Lee (USC)
Dan Kramer and Luke Bashford (U of Colorado, Anschutz Medical Campus)
Center Funded Research Projects
Isabelle A. Rosenthal, Luke Bashford, Spencer Kellis, Kelsie Pejsa, Brian Lee, Charles Liu, Richard A. Andersen. "S1 represents multisensory contexts and somatotopic locations within and outside the bounds of the cortical homunculus" Cell Reports, Volume 42, Issue 4, 2023, 112312, ISSN 2211-1247, https://doi.org/10.1016/j.celrep.2023.112312.
S. K. Wandelt, S. Kellis, D. A. Bjånes, K. Pejsa, B. Lee, C. Liu, R. A. Andersen. "Decoding grasp and speech signals from the cortical grasp circuit in a tetraplegic human" 2022 Neuron 110, 1-11. https://doi.org/10.1016/j.neuron.2022.03.009
T. Aflalo, C. Zhang, B. Revechkis, E. Rosario, N. Pouratian, R. A. Andersen. "Implicit mechanisms of Intention" 2022 Current Biology 32, 1-10. https://doi.org/10.1016/j.cub.2022.03.047
Norman, S. L., D. Maresca, V. N. Christopoulos, W. S. Griggs, C. Demene, M. Tanter, M. G. Shapiro and R. A. Andersen (2021). "Single Trial Decoding of Movement Intentions Using Functional Ultrasound Neuroimaging." Neuron 109, 1–13. https://doi.org/10.1016/j.neuron.2021.03.003
Urban LS, Thornton MA, Ingraham Dixie KL, Dale EA, Zhong H, Phelps PE, Burdick JW, Edgerton VR. Formation of a novel supraspinal-spinal connectome that relearns the same motor task after complete paralysis. J Neurophysiol. 2021 Sep 1;126(3):957-966. doi: 10.1152/jn.00422.2020. Epub 2021 Aug 18.
Aflalo, T., C. Y. Zhang, E. R. Rosario, N. Pouratian, G. A. Orban and R. A. Andersen (2020). "A shared neural substrate for action verbs and observed actions in human posterior parietal cortex." Sci Adv 6(43).
B. A. Haghi, S. Kellis, S. Shah, M. Ashok, L. Bashford, D. Kramer, B. Lee, Ch. Liu, R. A. Andersen, and A. Emami, " Deep Multi-State Dynamic Recurrent Neural Networks Operating on Wavelet Based Neural Features for Robust Brain Machine Interfaces", Thirty-third Conference on Neural Information Processing Systems (NeurIPS 2019), 2019, Vancouver, Canada.
Andersen R.A. 2019. "The intention machine" , Scientific American, Vol 320, Issue 4, 25-29.
Reutskaja, E., Lindner , A., Nagel, R., Andersen, R.A., and Camerer, C.F. "Choice overload reduces neural signatures of choice set value in dorsal striatum and anterior cingulate cortex", Nature Human Behaviour (2018) doi: https://doi.org/10.1038/s41562-018-0440-2.
Armenta Salas, M., Bashford, L., Kellis, S., Jafari, M., Jo, H., Kramer, D., Shanfield, K., Pejsa,K., Lee,B., Liu, C.Y., Andersen, R.A., "Proprioceptive and cutaneous sensations in humans elicited by intracortical microstimulation", eLife (2018).
Rutishauser, U., Aﬂalo, T., Rosario, E.R., Pouratian, N., Andersen, R.A. (2018) "Single-Neuron Representation of Memory Strength and Recognition Conﬁdence in Left Human Posterior Parietal Cortex" Neuron 97(1), 209–220.