"Master" Neurons Induced by Operant Conditioning in Rat Motor Cortex during a Brain-Machine Interface Task

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.

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Faculty Opinions recommendation of Inducing γ oscillations and precise spike synchrony by operant conditioning via brain-machine interface.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.717975905.793476129 ◽

2013 ◽

Author(s):

Alfons Schnitzler ◽

Joachim Lange

Keyword(s):

Operant Conditioning ◽

Brain Machine Interface ◽

Spike Synchrony ◽

Machine Interface

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Reward Modulates Local Field Potentials, Spiking Activity and Spike-Field Coherence in the Primary Motor Cortex

10.1101/471151 ◽

2018 ◽

Cited By ~ 4

Author(s):

Junmo An ◽

Taruna Yadav ◽

John P. Hessburg ◽

Joseph T. Francis

Keyword(s):

Motor Cortex ◽

Primary Motor Cortex ◽

Brain Machine Interface ◽

Field Potentials ◽

Alpha Oscillations ◽

Firing Rates ◽

Neural Spiking ◽

Machine Interface ◽

Field Coherence ◽

Spike Firing

ABSTRACTReward modulation of the primary motor cortex (M1) could be exploited in developing an autonomously updating brain-machine interface (BMI) based on a reinforcement learning architecture. In order to understand the multifaceted effects of reward on M1 activity, we investigated how neural spiking, oscillatory activities and their functional interactions are modulated by conditioned stimuli related reward expectation. To do so, local field potentials (LFPs) and singleunit/multi-unit activities were recorded simultaneously and bilaterally from M1 cortices while five non-human primates performed cued center-out reaching or grip force tasks either manually using their right arm/hand or observed passively. We found that reward expectation influenced the strength of alpha (8-14 Hz) power, alpha-gamma comodulation, alpha spike-field coherence, and firing rates in general in M1. Furthermore, we found that an increase in alpha-band power was correlated with a decrease in neural spiking activity, that firing rates were highest at the trough of the alpha-band cycle and lowest at the peak of its cycle. These findings imply that alpha oscillations modulated by reward expectation have an influence on spike firing rate and spike timing during both reaching and grasping tasks in M1. These LFP, spike, and spike-field interactions could be used to follow the M1 neural state in order to enhance BMI decoding (An et al., 2018; Zhao et al., 2018).Significance StatementKnowing the subjective value of performed or observed actions is valuable feedback that can be used to improve the performance of an autonomously updating brain-machine interface (BMI). Reward-related information in the primary motor cortex (M1) may be crucial for more stable and robust BMI decoding (Zhao et al., 2018). Here, we present how expectation of reward during motor tasks, or simple observation, is represented by increased spike firing rates in conjunction with decreased alpha (8-14 Hz) oscillatory power, alpha-gamma comodulation, and alpha spike-field coherence, as compared to non-rewarding trials. Moreover, a phasic relation between alpha oscillations and firing rates was observed where firing rates were found to be lowest and highest at the peak and trough of alpha oscillations, respectively.

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