Literature DB >> 16823294

The emerging world of motor neuroprosthetics: a neurosurgical perspective.

Eric C Leuthardt1, Gerwin Schalk, Daniel Moran, Jeffrey G Ojemann.   

Abstract

A MOTOR NEUROPROSTHETIC device, or brain computer interface, is a machine that can take some type of signal from the brain and convert that information into overt device control such that it reflects the intentions of the user's brain. In essence, these constructs can decode the electrophysiological signals representing motor intent. With the parallel evolution of neuroscience, engineering, and rapid computing, the era of clinical neuroprosthetics is approaching as a practical reality for people with severe motor impairment. Patients with such diseases as spinal cord injury, stroke, limb loss, and neuromuscular disorders may benefit through the implantation of these brain computer interfaces that serve to augment their ability to communicate and interact with their environment. In the upcoming years, it will be important for the neurosurgeon to understand what a brain computer interface is, its fundamental principle of operation, and what the salient surgical issues are when considering implantation. We review the current state of the field of motor neuroprosthetics research, the early clinical applications, and the essential considerations from a neurosurgical perspective for the future.

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Year:  2006        PMID: 16823294     DOI: 10.1227/01.NEU.0000221506.06947.AC

Source DB:  PubMed          Journal:  Neurosurgery        ISSN: 0148-396X            Impact factor:   4.654


  30 in total

Review 1.  The development of brain-machine interface neuroprosthetic devices.

Authors:  Parag G Patil; Dennis A Turner
Journal:  Neurotherapeutics       Date:  2008-01       Impact factor: 7.620

2.  Histological evaluation of a chronically-implanted electrocorticographic electrode grid in a non-human primate.

Authors:  Alan D Degenhart; James Eles; Richard Dum; Jessica L Mischel; Ivan Smalianchuk; Bridget Endler; Robin C Ashmore; Elizabeth C Tyler-Kabara; Nicholas G Hatsopoulos; Wei Wang; Aaron P Batista; X Tracy Cui
Journal:  J Neural Eng       Date:  2016-06-28       Impact factor: 5.379

Review 3.  Assistive technology and robotic control using motor cortex ensemble-based neural interface systems in humans with tetraplegia.

Authors:  John P Donoghue; Arto Nurmikko; Michael Black; Leigh R Hochberg
Journal:  J Physiol       Date:  2007-02-01       Impact factor: 5.182

4.  Microscale recording from human motor cortex: implications for minimally invasive electrocorticographic brain-computer interfaces.

Authors:  Eric C Leuthardt; Zac Freudenberg; David Bundy; Jarod Roland
Journal:  Neurosurg Focus       Date:  2009-07       Impact factor: 4.047

Review 5.  Evolution of brain-computer interfaces: going beyond classic motor physiology.

Authors:  Eric C Leuthardt; Gerwin Schalk; Jarod Roland; Adam Rouse; Daniel W Moran
Journal:  Neurosurg Focus       Date:  2009-07       Impact factor: 4.047

6.  Decoding movement-related cortical potentials from electrocorticography.

Authors:  Chandan G Reddy; Goutam G Reddy; Hiroto Kawasaki; Hiroyuki Oya; Lee E Miller; Matthew A Howard
Journal:  Neurosurg Focus       Date:  2009-07       Impact factor: 4.047

7.  Clinical Applications of Brain-Computer Interfaces: Current State and Future Prospects.

Authors:  Joseph N Mak; Jonathan R Wolpaw
Journal:  IEEE Rev Biomed Eng       Date:  2009

8.  Encoding of speed and direction of movement in the human supplementary motor area.

Authors:  Ariel Tankus; Yehezkel Yeshurun; Tamar Flash; Itzhak Fried
Journal:  J Neurosurg       Date:  2009-06       Impact factor: 5.115

9.  Cyber-workstation for computational neuroscience.

Authors:  Jack Digiovanna; Prapaporn Rattanatamrong; Ming Zhao; Babak Mahmoudi; Linda Hermer; Renato Figueiredo; Jose C Principe; Jose Fortes; Justin C Sanchez
Journal:  Front Neuroeng       Date:  2010-01-20

Review 10.  Cortical neuroprosthetics from a clinical perspective.

Authors:  Adelyn P Tsu; Mark J Burish; Jason GodLove; Karunesh Ganguly
Journal:  Neurobiol Dis       Date:  2015-08-05       Impact factor: 5.996

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