期刊
NEUROIMAGE
卷 114, 期 -, 页码 338-355出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2015.04.008
关键词
Macaque; Motor cortex; Kinetics; Grasping; Local field potentials; Movement planning
资金
- German Federal Ministry of Education and Research (BMBF) [01GQ0830]
- Imperial College London
- IBRO InEurope Short Stay Grant program
- RIKEN-CNRS Collaborative Research Agreement
- ANR GRASP (France)
- BrainScaleS (EU) [269912]
- Helmoltz portfolio theme Supercomputing and modeling for the human brain (SMHB)
- U.S. National Institute of Neurological Disorders and Stroke (NINDS) [NS057389]
- Brown University
Reach and grasp kinematics are known to be encoded in the spiking activity of neuronal ensembles and in local field potentials (LFPs) recorded from primate motor cortex during movement planning and execution. However, little is known, especially in LFPs, about the encoding of kinetic parameters, such as forces exerted on the object during the same actions. We implanted two monkeys with microelectrode arrays in the motor cortical areas MI and PMd to investigate encoding of grasp-related parameters in motor cortical LFPs during planning and execution of reach-and-grasp movements. We identified three components of the LFP that modulated during grasps corresponding to low (0.3-7 Hz), intermediate(similar to 10-similar to 40 Hz) and high (similar to 80-250 Hz) frequency bands. We show that all three components can be used to classify not only grip types but also object loads during planning and execution of a grasping movement. In addition, we demonstrate that all three components recorded during planning or execution can be used to continuously decode finger pressure forces and hand position related to the grasping movement. Low and high frequency components provide similar classification and decoding accuracies, which were substantially higher than those obtained from the intermediate frequency component. Our results demonstrate that intended reach and grasp kinetic parameters are encoded in multiple LFP bands during both movement planning and execution. These findings also suggest that the LFP is a reliable signal for the control of parameters related to object load and applied pressure forces in brain-machine interfaces. (C) 2015 Elsevier Inc. All rights reserved.
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