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Related Experiment Video

Updated: Oct 8, 2025

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces

Published on: March 10, 2011

Exploring Cognition with Brain-Machine Interfaces.

Richard A Andersen^1,2, Tyson Aflalo¹, Luke Bashford¹

¹Division of Biology and Biological Engineering and Tianqiao & Chrissy Chen Brain-Machine Interface Center, California Institute of Technology, Pasadena, California 91125, USA;

Annual Review of Psychology

|January 4, 2022

Summary

This summary is machine-generated.

New brain signals from the posterior parietal cortex offer enhanced control for brain-machine interfaces. These cognitive signals improve movement monitoring and decision-making for more intuitive prosthetic device operation.

Keywords:

brain–machine interface cognition learning posterior parietal cortex semantics somatosensation

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Last Updated: Oct 8, 2025

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Published on: March 10, 2011

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Published on: May 8, 2021

Area of Science:

Neuroscience
Cognitive Science
Biomedical Engineering

Background:

Traditional brain-machine interfaces (BMIs) primarily decode motor commands for device control.
Motor commands arise from complex cognitive processes involving sensory integration, action planning, and movement monitoring across brain networks.

Purpose of the Study:

To review recently discovered cognitive signals in the human posterior parietal cortex (PPC).
To explore the role of these PPC signals in enhancing BMI control capabilities.

Main Methods:

Review of neuroprosthetic clinical trial data.
Analysis of cognitive signals recorded from the PPC.
Investigation of neural representations within PPC cell populations.

Main Results:

The PPC contains diverse cognitive signals related to movement control and body monitoring.
These signals encompass sensorimotor integration, action planning, trajectory representation, somatosensation, action semantics, learning, and decision-making.
A "partially mixed selectivity" architecture binds related sensory and motor variables within PPC cells.

Conclusions:

Diverse cognitive signals from the PPC complement traditional motor commands for BMIs.
These signals enable more natural and intuitive control of external devices.
The PPC plays a crucial role in higher-level cognitive aspects of movement control.