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2026-07-20 00:00 United States Papers Foundations & Methods Translated from EN

Targeting Grasp-Related Cortical Areas for Intracortical Brain-Machine Interfaces

Summary For a C5 tetraplegic participant, the study integrated anatomical, functional and vascular imaging with preoperative 3D modeling to optimize placement of intracortical microelectrode arrays for grasp-related motor decoding. Anatomical MRI, diffusion-weighted imaging and task-based fMRI identified grasp-related cortex while avoiding vasculature and speech-critical regions; Quicktome software refined target selection using structural connectivity and functional activation data, and 3D-printed skull and cortex models supported surgical planning. Functional imaging highlighted the anterior intraparietal sulcus (AIP), ventral premotor cortex (PMv) and inferior frontal gyrus (IFG); arrays placed in AIP and PMv subregions 6v and 6r reached a combined classification accuracy of 96%.
Why it matters Multimodal imaging plus 3D modeling turns electrode placement into a pre-planned, image-guided step — the difference between hitting and missing the grasp-related cortex.

术前多模态成像选好植入点,四肢瘫患者抓握解码准确率96%
Image: Neuroimage. Reports, CC BY 4.0

This study, published in NeuroImage: Reports, improved intracortical microelectrode array implantation sites for grasp-related motor decoding by integrating anatomical, functional and vascular imaging with preoperative 3D modeling; functional imaging identified distinct grasp-related activation in the anterior intraparietal area (AIP), ventral premotor cortex (PMv) and inferior frontal gyrus (IFG).

Electrode placement was validated postoperatively using neural data collected during attempted arm and hand movements, with the arrays enabling high-fidelity decoding at a combined classification accuracy of 96%; the authors conclude this multimodal approach effectively identifies surgically feasible grasp-network implant locations in a paralyzed individual. PMID 42473457, DOI 10.1016/j.ynirp.2026.100381

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