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J Neurophysiol. 2018 Jul 1;120(1):343-360. doi: 10.1152/jn.00493.2017. Epub 2018 Apr 25.

Stable long-term BCI-enabled communication in ALS and locked-in syndrome using LFP signals.

Milekovic T1,2,3, Sarma AA2,4,5, Bacher D2,4, Simeral JD2,4,5, Saab J2,4, Pandarinath C6,7,8, Sorice BL9, Blabe C6, Oakley EM9, Tringale KR9, Eskandar E10,11, Cash SS11,9, Henderson JM6,12,8, Shenoy KV7,13,14,15,8,16, Donoghue JP1,2,5, Hochberg LR2,4,5,11,9.

Author information

1
Department of Neuroscience, Brown University , Providence, Rhode Island.
2
Carney Institute for Brain Science, Brown University , Providence, Rhode Island.
3
Department of Fundamental Neuroscience, Faculty of Medicine, University of Geneva , Geneva , Switzerland.
4
School of Engineering, Brown University , Providence, Rhode Island.
5
Center for Neurorestoration and Neurotechnology, Rehabilitation Research & Development, Department of Veterans Affairs , Providence, Rhode Island.
6
Department of Neurosurgery, Stanford University , Stanford, California.
7
Department of Electrical Engineering, Stanford University , Stanford, California.
8
Stanford Neurosciences Institute, Stanford University , Stanford, California.
9
Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital , Boston, Massachusetts.
10
Department of Neurosurgery, Massachusetts General Hospital , Boston, Massachusetts.
11
Harvard Medical School , Boston, Massachusetts.
12
Department of Neurology and Neurological Sciences, Stanford University , Stanford, California.
13
Neurosciences Program, Stanford University , Stanford, California.
14
Department of Neurobiology, Stanford University , Stanford, California.
15
Department of Bioengineering, Stanford University , Stanford, California.
16
Howard Hughes Medical Institute at Stanford University , Stanford, California.

Abstract

Restoring communication for people with locked-in syndrome remains a challenging clinical problem without a reliable solution. Recent studies have shown that people with paralysis can use brain-computer interfaces (BCIs) based on intracortical spiking activity to efficiently type messages. However, due to neuronal signal instability, most intracortical BCIs have required frequent calibration and continuous assistance of skilled engineers to maintain performance. Here, an individual with locked-in syndrome due to brain stem stroke and an individual with tetraplegia secondary to amyotrophic lateral sclerosis (ALS) used a simple communication BCI based on intracortical local field potentials (LFPs) for 76 and 138 days, respectively, without recalibration and without significant loss of performance. BCI spelling rates of 3.07 and 6.88 correct characters/minute allowed the participants to type messages and write emails. Our results indicate that people with locked-in syndrome could soon use a slow but reliable LFP-based BCI for everyday communication without ongoing intervention from a technician or caregiver. NEW & NOTEWORTHY This study demonstrates, for the first time, stable repeated use of an intracortical brain-computer interface by people with tetraplegia over up to four and a half months. The approach uses local field potentials (LFPs), signals that may be more stable than neuronal action potentials, to decode participants' commands. Throughout the several months of evaluation, the decoder remained unchanged; thus no technical interventions were required to maintain consistent brain-computer interface operation.

KEYWORDS:

amyotrophic lateral sclerosis; brain-computer interface; communication; local field potentials; long-term stability; people with locked-in syndrome

PMID:
29694279
PMCID:
PMC6093965
[Available on 2019-07-01]
DOI:
10.1152/jn.00493.2017

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