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

Published

Journal Article

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.

Full Text

Duke Authors

Cited Authors

  • Vaidya, M; Balasubramanian, K; Southerland, J; Badreldin, I; Eleryan, A; Shattuck, K; Gururangan, S; Slutzky, M; Osborne, L; Fagg, A; Oweiss, K; Hatsopoulos, NG

Published Date

  • April 1, 2018

Published In

Volume / Issue

  • 119 / 4

Start / End Page

  • 1291 - 1304

PubMed ID

  • 29357477

Pubmed Central ID

  • 29357477

Electronic International Standard Serial Number (EISSN)

  • 1522-1598

Digital Object Identifier (DOI)

  • 10.1152/jn.00982.2016

Language

  • eng

Conference Location

  • United States