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Towards machine to brain interfaces: sensory stimulation enhances sensorimotor dynamic functional connectivity in
Keqin Ding1,2, Andrei Dragomir3,4,2, Rohit Bose3,5
1Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, United States of America.
Sensory stimulation enhances brain connectivity in amputees, improving information transfer speed and network communication. This study reveals dynamic cortical interactions, paving the way for advanced brain-computer interfaces and better motor performance.
Area of Science:
- Neuroscience
- Rehabilitation Medicine
- Biomedical Engineering
Background:
- Sensory stimulation can induce phantom sensations in upper limb amputees.
- Cortical processing and sensorimotor functional connectivity changes due to this stimulation remain understudied.
Purpose of the Study:
- To investigate the impact of sensory stimulation on sensorimotor cortical functional connectivity in amputees.
- To analyze dynamic functional connectivity (dFC) using electroencephalogram (EEG) data.
Main Methods:
- EEG data from two upper limb amputees and three able-bodied individuals were analyzed.
- Dynamic functional connectivity (dFC) was applied to assess interactions between somatosensory, motor, visual, and multisensory cortical areas.
- Changes were quantified using metrics like temporal distance, number of connection paths, and network efficiencies.
Main Results:
- Sensory stimulation significantly altered functional connectivity in amputee brains, enhancing multisensory processing.
- dFC metrics indicated faster information transfer and increased connectivity between sensorimotor processing regions.
- These effects were observed in primary somatosensory, motor, and higher-order processing areas.
Conclusions:
- This is the first study to demonstrate dynamic cortical communication changes in amputees following sensory stimulation.
- Findings offer insights into the cortical effects of sensory stimulation, potentially guiding personalized feedback paradigms.
- The research may inform the development of novel brain-computer interfaces for enhanced motor performance.
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