Electrocorticographic signals comparison in sensorimotor cortex between contralateral and ipsilateral hand movements

Area of Science:

• Neuroscience
• Biomedical Engineering
• Rehabilitation Technology

Background:

• Brain machine interfaces (BMIs) are crucial for restoring motor function in impaired patients.
• Current BMI systems primarily utilize neural signals from the contralateral hemisphere.
• The role of the ipsilateral hemisphere in motor control and BMI applications remains less understood.

Purpose of the Study:

• To investigate the neural signal characteristics and decoding capabilities of the ipsilateral sensorimotor cortex during hand movement.
• To compare the effectiveness of ipsilateral versus contralateral neural signals for controlling hand movements using BMIs.
• To explore the potential of ipsilateral brain activity for expanding BMI applications.

Main Methods:

• Analysis of electrocorticographic (ECoG) signals from the sensorimotor cortex in two epilepsy participants.
• Participants performed a visual-guided rock-scissors-paper task using both contralateral and ipsilateral hands.
• High gamma frequency band (70-135Hz) power spectrum of ECoG signals was extracted as neural features for decoding hand movements.

Main Results:

• Observed typical beta suppression and increased gamma activity during hand movements for both contralateral and ipsilateral hands.
• Stronger neural responses were noted when using the contralateral hand compared to the ipsilateral hand.
• Decoding accuracies for contralateral hand movements were 81% (P1) and 84% (P2), while ipsilateral hand movements achieved 78% (P1) and 77% (P2).

Conclusions:

• Ipsilateral sensorimotor cortex contains significant hand movement information, enabling decoding with accuracy comparable to the contralateral hemisphere.
• The ipsilateral hemisphere appears to be involved in neural modulation during unimanual movements, similar to the contralateral hemisphere.
• These findings suggest that ipsilateral neural signals can be effectively utilized in brain machine interfaces, broadening their clinical applicability.