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Noninvasively recorded high-gamma signals improve synchrony of force feedback in a novel neurorehabilitation brain-machine interface for brain injury.
Flint, Robert D; Li, Yongcheng; Wang, Po T; Vaidya, Mukta; Barry, Alex; Ghassemi, Mohammad; Tomic, Goran; Brkic, Nenad; Ripley, David; Liu, Charles; Kamper, Derek; Do, An H; Slutzky, Marc W.
  • Flint RD; Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States of America.
  • Li Y; Department of Neurology, University of California Irvine, Irvine, CA, United States of America.
  • Wang PT; Department of Biomedical Engineering, University of California Irvine, Irvine, CA, United States of America.
  • Vaidya M; Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States of America.
  • Barry A; Shirley Ryan AbilityLab, Chicago, IL, United States of America.
  • Ghassemi M; Department of Biomedical Engineering, North Carolina State University, Raleigh, NC, United States of America.
  • Tomic G; Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States of America.
  • Brkic N; Shirley Ryan AbilityLab, Chicago, IL, United States of America.
  • Ripley D; Shirley Ryan AbilityLab, Chicago, IL, United States of America.
  • Liu C; Department of Neurosurgery, University of California Irvine, Irvine, CA, United States of America.
  • Kamper D; Department of Biomedical Engineering, North Carolina State University, Raleigh, NC, United States of America.
  • Do AH; Department of Neurology, University of California Irvine, Irvine, CA, United States of America.
  • Slutzky MW; Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States of America.
J Neural Eng ; 19(3)2022 06 01.
Article en En | MEDLINE | ID: mdl-35576911
ABSTRACT
Objective.Brain injury is the leading cause of long-term disability worldwide, often resulting in impaired hand function. Brain-machine interfaces (BMIs) offer a potential way to improve hand function. BMIs often target replacing lost function, but may also be employed in neurorehabilitation (nrBMI) by facilitating neural plasticity and functional recovery. Here, we report a novel nrBMI capable of acquiring high-γ(70-115 Hz) information through a unique post-traumatic brain injury (TBI) hemicraniectomy window model, and delivering sensory feedback that is synchronized with, and proportional to, intended grasp force.Approach. We developed the nrBMI to use electroencephalogram recorded over a hemicraniectomy (hEEG) in individuals with TBI. The nrBMI empowered users to exert continuous, proportional control of applied force, and provided continuous force feedback. We report the results of an initial testing group of three human participants with TBI, along with a control group of three skull- and motor-intact volunteers.Main results. All participants controlled the nrBMI successfully, with high initial success rates (2 of 6 participants) or performance that improved over time (4 of 6 participants). We observed high-γmodulation with force intent in hEEG but not skull-intact EEG. Most significantly, we found that high-γcontrol significantly improved the timing synchronization between neural modulation onset and nrBMI output/haptic feedback (compared to low-frequency nrBMI control).Significance. These proof-of-concept results show that high-γnrBMIs can be used by individuals with impaired ability to control force (without immediately resorting to invasive signals like electrocorticography). Of note, the nrBMI includes a parameter to change the fraction of control shared between decoded intent and volitional force, to adjust for recovery progress. The improved synchrony between neural modulations and force control for high-γsignals is potentially important for maximizing the ability of nrBMIs to induce plasticity in neural circuits. Inducing plasticity is critical to functional recovery after brain injury.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Lesiones Encefálicas / Interfaces Cerebro-Computador / Rehabilitación Neurológica Límite: Humans Idioma: En Año: 2022 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Lesiones Encefálicas / Interfaces Cerebro-Computador / Rehabilitación Neurológica Límite: Humans Idioma: En Año: 2022 Tipo del documento: Article