The Johns Hopkins Department of Physical Medicine and Rehabilitation (PM&R), in collaboration with the Johns Hopkins University Applied Physics Laboratory and the Department of Neurology and Neurosurgery, has been awarded a grant by the Defense Advanced Research Projects Agency (DARPA) to conduct a clinical trial focused on recording and stimulating the brain of a person with tetraplegia.
Robert Nickl, Postdoctoral Research Fellow with the Department of Physical Medicine & Rehabilitation at Johns Hopkins, explains findings published in Scientific Reports, titled "Characteristics and stability of sensorimotor activity driven by isolated-muscle group activation in a human with tetraplegia".
Nickl, R.W., Anaya, M.A., Thomas, T.M. et al.
Characteristics and stability of sensorimotor activity driven by isolated-muscle group activation in a human with tetraplegia. Sci Rep 12, 10353 (2022). My research focuses on the question of how we can restore motor function in people with spinal cord injury that can no longer control their arms and hands. My work is part of a collaboration between the Department of Physical Medicine and rehabilitation and the applied physics lab at johns Hopkins where we're working on solving this problem with brain machine interfaces, or B. M. I. S. A. B. M. I works by using electorate were raised to read from a person's brain while they attempt to do or to think about an action. The B. M. I. Then decodes these thoughts and then sends these decoded thoughts directly to device, like a robotic arm bypassing the injured spinal cord, ours is the first group to use electorate are raised to read from both sides of the brain, a practical obstacle to be M. I. Uses that decoders need to be recalibrated often. So for example, if A B. M. I. User sits down to have a drink of water, they might initially be able to reach toward the cup accurately and decisively. But after several minutes they may start to miss the cup or they might not be able to hold it is steadily. So in these cases this might indicate that the decoder is no longer satisfactory and so the user may need to stop for several minutes while a new decoder is set up. So we think that this is because brain signals are constantly fluctuating and that and that we can make decoding smoother. If we can better understand the sources of instability in different brain regions. To study this, we ran a series of experiments over a few months where we asked the B. M. I. Participant to repeatedly attempt a simple risk task in pace with the metronome, we look at stability in terms of which parts of each electrode array. We're getting consistently activated and how similar the signaling was across the sensory and motor areas of both brain hemispheres. First we zoomed in on individual sites or units within each hemisphere and area, and our two main findings here were that signals originating in the hemisphere on the opposite side of the brain to the attempted movement were more stable than those originating from the same side, and that signals from sensory cortex were more stable than signals from the motor cortex from here we then zoomed out and then asked at a sectional level how the signals within each part of the brain interact with each other as an ensemble. And at this network level we found that both areas of the brain were equally stable and that this seemed to hold up over time we can think of these results in terms of an analogy with an orchestra. So you can imagine that each area of the brain is a different section. The contra lateral motor area might be the strings and the bilateral sensory might be the percussion for instance. Now, within each section, players are going to have different abilities to stay in tune or to keep a rhythm, but as a whole ensemble, um the players within a section are somehow able to gel together so that when you hear an orchestral performance, um the quality that you get on one night is going to be very similar to the quality of performance you get on another night. And so we think that decoders that work with these network wide interactions as opposed to smaller brain units, um at the level of electrodes are going to provide a smoother and more robust decoding. And this is a possibility that we're currently working on developing.