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Related Experiment Video

Updated: May 14, 2026

Multiscale Investigations of Cortical Processing by Integrating Laminar Polytrodes and Optogenetics with Micro Electrocorticography in Rodents

Multiscale Investigations of Cortical Processing by Integrating Laminar Polytrodes and Optogenetics with Micro Electrocorticography in Rodents

Published on: May 23, 2025

Cortical adaptation to a chronic micro-electrocorticographic brain computer interface.

Adam G Rouse¹, Jordan J Williams, Jesse J Wheeler

¹Department of Biomedical Engineering, Washington University, St. Louis, Missouri 63130, USA.

The Journal of Neuroscience : the Official Journal of the Society for Neuroscience

|January 25, 2013

Summary

This summary is machine-generated.

This study shows that brain-computer interface (BCI) technology can be controlled using neural signals from the motor cortex. Monkeys learned to control a cursor, with motor cortex signals proving more effective for BCI control.

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Published on: November 19, 2017

Area of Science:

Neuroscience
Biomedical Engineering
Signal Processing

Background:

Brain-computer interface (BCI) systems translate neural activity into commands for external devices.
Real-time decoding of neural signals is crucial for effective BCI operation.
Understanding the neural correlates of BCI control is essential for improving performance.

Purpose of the Study:

To investigate the contribution of primary motor (M1) and dorsal premotor (PMd) cortex to BCI control.
To analyze the role of gamma-band amplitude in real-time BCI performance.
To determine if BCI control involves active cortical modulation.

Main Methods:

Chronic epidural micro-electrocorticography was used in three macaque monkeys.
Differential gamma-band amplitude (75-105 Hz) from M1 and PMd electrodes was recorded.
A one-dimensional BCI device was controlled in a closed-loop manner using these signals.

Main Results:

Macaque monkeys rapidly learned to control a computer cursor's velocity within days.
M1 provided stronger control signals for BCI task success compared to PMd.
Gamma-band power during active BCI control exceeded resting brain activity levels.

Conclusions:

Both M1 and PMd contribute to BCI control, with M1 showing stronger modulation.
Active BCI control is associated with increased cortical activation, indicated by elevated gamma-band power.
This study highlights the potential of using specific neural signals for intuitive BCI operation.