Send to

Choose Destination
eNeuro. 2019 Jun 6. pii: ENEURO.0178-19.2019. doi: 10.1523/ENEURO.0178-19.2019. [Epub ahead of print]

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

Author information

Department of Biomedical Engineering, University of Houston, Houston, TX, USA.
Department of Physiology and Pharmacology, Robert F Furchgott Center for Neural and Behavioral Science, State University of New York Downstate Medical Center, Brooklyn, NY, USA.
Department of Biomedical Engineering, University of Houston, Houston, TX, USA


Reward modulation of the primary motor cortex (M1) could be exploited in developing an autonomously updating brain-computer interface (BCI) based on a reinforcement learning (RL) architecture. For an autonomously updating RL based BCI system, we would need a reward prediction error, or a state-value representation from the user's neural activity, which the RL-BCI agent could use to update its BCI-decoder. 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 single-unit/multiunit activities were recorded simultaneously and bilaterally from M1 cortices while four 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 BCI decoding (An et al., 2018; Zhao et al., 2018).Significance Statement Knowing the subjective value of performed or observed actions is valuable feedback that could be used to improve the performance of an autonomously updating brain-computer interface (BCI). Reward-related information in the primary motor cortex (M1) may be crucial for more stable and robust BCI 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 nonrewarding 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.


Brain machine interface; alpha power; mirror neurons; primary motor cortex; pulsed inhibition; reward

Free full text

Conflict of interest statement

The authors declare no conflict of interests.

Supplemental Content

Full text links

Icon for HighWire
Loading ...
Support Center