Context-dependent relationship in high-resolution micro-ECoG studies during finger movements.

Area of Science:

• Neuroscience
• Motor Control
• Brain-Computer Interfaces

Background:

• Electrocorticography (ECoG) signals correlate with human hand movements.
• The relationship between synergistic finger movements and ECoG signals requires further exploration.

Purpose of the Study:

• To investigate the link between neural signals and individual/synergistic finger movements using high-resolution micro-ECoG (µECoG).
• To analyze the sensorimotor cortex's tuning for specific motor behaviors.

Main Methods:

• Utilized intraoperative high-resolution µECoG grids on the sensorimotor cortex of three neurosurgical patients.
• Recorded high-gamma (HG) filtered µECoG signals during thumb-only, index-only, and pinch movements, synchronized with dataglove recordings.

Main Results:

• HG-filtered µECoG successfully identified distinct electrodes for thumb and index finger movements.
• While index finger movement-to-signal relationships were consistent, thumb movement showed a markedly decreased output during pinch despite similar cortical activation.
• Pinch movement µECoG signals were a combination of individual thumb and index finger signals.

Conclusions:

• HG-filtered µECoG is effective for mapping finger-specific sensorimotor cortex regions.
• A nonlinear relationship exists between cortical signals and motor output for certain movements, like the thumb during pinch.
• Findings offer insights into motor cortex tuning for diverse motor behaviors.