Paralysis affects millions of people worldwide with the two leading causes being stroke and spinal cord injury. Feinstein researchers are currently working to understand how to limit damage and provide a pro-regenerative environment to nerve cells after spinal cord injury. Additional studies are ongoing to identify the molecular factors necessary to successfully recover from central nervous system (CNS) injury or disease.
Bioelectronic devices are also under development to create a neural bypass to circumvent damaged neural pathways resulting from stroke, spinal cord injury, traumatic brain injury, multiple sclerosis (MS), motor neuron disease, and other conditions. It has been shown that intracortically-recorded signals can be decoded to extract information related to motion allowing paralyzed humans to control computers and assistive devices through imagined movements. Recently, further advances have been made to link decoded brain signals directly to movement in a first-in-human demonstration. Researchers are currently looking at ways to extend technology development to address not only paralysis and its comorbidities, but a wide variety of diseases and conditions, leveraging the expanding knowledge within the field of bioelectronic medicine.
Feinstein Institute Investigator Bruce T. Volpe, MD studies the use of robots in stroke recovery. See the video below.
- Developments in intervertebral disc disease research: pathophysiology, mechanobiology, and therapeutics.Weber KT, Jacobsen TD, Maidhof R, Virojanapa J, Overby C, Bloom O, Quraishi S, Levine M, Chahine NO. Curr Rev Musculoskelet Med. 2015 Mar;8(1):18-31. doi: 10.1007/s12178-014-9253-8.
- Elevated circulating levels of the pro-inflammatory cytokine macrophage migration inhibitory factor in individuals with acute spinal cord injury.Bank M, Stein A, Sison C, Glazer A, Jassal N, McCarthy D, Shatzer M, Hahn B, Chugh R, Davies P, Bloom O. Arch Phys Med Rehabil. 2015 Apr;96(4):633-44. doi: 10.1016/j.apmr.2014.10.021. Epub 2014 Nov 15.
- Nonsmooth formulation of the support vector machine for a neural decoding problem. arXiv preprint arXiv:1012.0958. Humber, C., Ito, K., & Bouton, C. (2010).
- Decoding neural activity from an intracortical implant in humans with tetraplegia.Decoding neural activity from an intracortical implant in humans with tetraplegia. In Biomedical Science & Engineering Conference, 2009. BSEC 2009. First Annual ORNL (pp. 1-1). IEEE. Bouton, C. (2009, March).
- Neural Decoding and Applications in Bioelectronic MedicineBouton C. (2015) Bioelectronic Medicine 2:20-24.
- Neural decoding: What’s on your mind?Medical Design, 39-41. Bouton, C. (2010, October).