Optimal location for gesture decoding in the sensorimotor cortex and implications for brain-computer interface...

Area of Science:

• Neuroscience
• Biomedical Engineering
• Medical Imaging

Background:

• Implantable brain-computer interfaces (iBCIs) are crucial for restoring communication in individuals with severe motor impairments.
• Optimal electrode placement is essential for achieving high performance in iBCI systems.

Purpose of the Study:

• To map the spatial distribution of brain activity related to hand gestures using high-resolution functional magnetic resonance imaging (fMRI).
• To identify optimal cortical locations for iBCI electrode placement to maximize decoding accuracy.

Main Methods:

• Utilized 7-Tesla fMRI to image brain activity in ten able-bodied participants performing 20 distinct unimanual hand gestures.
• Employed support vector machines to analyze and quantify the decodability of hand gestures across the cortex.
• Investigated the contribution of different cortical regions (gyral vs. sulcal) to decoding performance.

Main Results:

• The highest decoding performance for hand gestures was observed in the sensorimotor cortex's hand region.
• A subset of six distinct gestures effectively predicted optimal decoding locations for a larger set of gestures.
• Decoding was possible in both sulcal and gyral regions, but gyral regions in the precentral and postcentral cortex provided the primary unique information, suggesting surface recordings may be sufficient.

Conclusions:

• Findings provide practical guidance for iBCI electrode placement, optimizing performance for communication restoration.
• Identifying optimal sensorimotor cortex regions can enhance the efficacy of iBCIs for individuals with motor impairments.
• The study suggests that focusing on gyral regions may be sufficient for effective iBCI signal acquisition.