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J Neurophysiol. 2018 Apr 1;119(4):1291-1304. doi: 10.1152/jn.00982.2016. Epub 2017 Dec 13.

Emergent coordination underlying learning to reach to grasp with a brain-machine interface.

Author information

1
Committee on Computational Neuroscience, University of Chicago , Chicago, Illinois.
2
Department of Neurology, Northwestern University Feinberg School of Medicine , Chicago, Illinois.
3
Department of Organismal Biology & Anatomy, University of Chicago , Chicago, Illinois.
4
School of Computer Science, University of Oklahoma , Norman, Oklahoma.
5
Department of Electrical & Computer Engineering, University of Florida , Gainesville, Florida.
6
Department of Neuroscience, Michigan State University , East Lansing, Michigan.
7
Initiative in Cognitive Science, University of Massachusetts , Amherst, Massachusetts.
8
Department of Neurobiology, Duke University , Durham, North Carolina.
9
Department of Neuroscience, McKnight Brain Institute, University of Florida , Gainesville, Florida.
10
Department of Biomedical Engineering, University of Florida , Gainesville, Florida.

Abstract

The development of coordinated reach-to-grasp movement has been well studied in infants and children. However, the role of motor cortex during this development is unclear because it is difficult to study in humans. We took the approach of using a brain-machine interface (BMI) paradigm in rhesus macaques with prior therapeutic amputations to examine the emergence of novel, coordinated reach to grasp. Previous research has shown that after amputation, the cortical area previously involved in the control of the lost limb undergoes reorganization, but prior BMI work has largely relied on finding neurons that already encode specific movement-related information. In this study, we taught macaques to cortically control a robotic arm and hand through operant conditioning, using neurons that were not explicitly reach or grasp related. Over the course of training, stereotypical patterns emerged and stabilized in the cross-covariance between the reaching and grasping velocity profiles, between pairs of neurons involved in controlling reach and grasp, and to a comparable, but lesser, extent between other stable neurons in the network. In fact, we found evidence of this structured coordination between pairs composed of all combinations of neurons decoding reach or grasp and other stable neurons in the network. The degree of and participation in coordination was highly correlated across all pair types. Our approach provides a unique model for studying the development of novel, coordinated reach-to-grasp movement at the behavioral and cortical levels. NEW & NOTEWORTHY Given that motor cortex undergoes reorganization after amputation, our work focuses on training nonhuman primates with chronic amputations to use neurons that are not reach or grasp related to control a robotic arm to reach to grasp through the use of operant conditioning, mimicking early development. We studied the development of a novel, coordinated behavior at the behavioral and cortical level, and the neural plasticity in M1 associated with learning to use a brain-machine interface.

KEYWORDS:

brain-machine interfaces; learning; neural coordination; primary motor cortex; reach to grasp

PMID:
29357477
PMCID:
PMC5966743
[Available on 2019-04-01]
DOI:
10.1152/jn.00982.2016

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