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Related Experiment Video

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Design and Use of an Apparatus for Presenting Graspable Objects in 3D Workspace

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Targeting Optimal Grasp-Related Cortical Areas for Intracortical Brain-Machine Interfaces after Spinal Cord Injury.

Tyler R Johnson, Crispin Foli, Emily C Conlan

Medrxiv : the Preprint Server for Health Sciences

|November 24, 2025

Summary

This summary is machine-generated.

This study optimized brain-computer interface (BCI) electrode placement for grasp decoding in tetraplegia using advanced imaging and 3D modeling. The approach successfully identified optimal sites for high-fidelity arm and hand movement decoding.

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Assessing Corticospinal Excitability During Goal-Directed Reaching Behavior

Assessing Corticospinal Excitability During Goal-Directed Reaching Behavior

Published on: December 2, 2022

Area of Science:

Neuroscience
Biomedical Engineering
Rehabilitation Medicine

Background:

Spinal cord injury (SCI) often results in paralysis, necessitating advanced assistive technologies.
Brain-machine interfaces (BCIs) offer a potential pathway to restore function by decoding neural signals.
Optimizing intracortical electrode placement is crucial for effective grasp-related motor decoding.

Purpose of the Study:

To refine intracortical microelectrode array implantation sites for grasp decoding.
To integrate anatomical, functional, and vascular imaging with 3D surgical modeling for precise targeting.
To identify surgically feasible locations within the grasp network for individuals with SCI.

Main Methods:

Utilized anatomical, diffusion-weighted, and functional MRI (fMRI) in a participant with C5 tetraplegia.
Employed Quicktome software for integrating structural connectivity and functional activation data.
Developed a 3D-printed model for preoperative planning and simulated electrode positioning.
Validated electrode placement using post-operative neural data during attempted movements.

Main Results:

Identified significant grasp-related activation in the anterior intraparietal area (AIP), ventral premotor cortex (PMv), and inferior frontal gyrus (IFG).
Selected AIP due to strong connectivity with motor cortex and distinct functional activation.
Chose surgically accessible subregions 6v and 6r of PMv over the posterior IFG.
Achieved 96% accuracy in decoding arm and hand movements post-implantation.

Conclusions:

A multi-modal approach combining MRI, fMRI, connectivity, and 3D modeling optimizes intracortical electrode placement.
Demonstrated an effective method for identifying feasible grasp network implant locations in paralyzed individuals.
This is a critical step towards developing BMI systems for restoring upper limb function in SCI patients.