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Resting-state functional connectivity and motor imagery brain activation.
Catarina Saiote1, Andrea Tacchino2, Giampaolo Brichetto2
1Department of Neurology, Icahn School of Medicine at Mount Sinai, New York.
Human Brain Mapping
|June 9, 2016
Summary
Resting-state functional connectivity (RSFC) in the motor imagery (MI) network predicts brain activation during MI tasks. This finding suggests RSFC plays a role in understanding MI abilities and their neural basis.
Area of Science:
- Neuroscience
- Cognitive Neuroscience
- Neuroimaging
Background:
- Motor imagery (MI) involves mentally simulating actions without physical movement.
- MI aids motor learning and neurological rehabilitation.
- Shared brain regions exist for MI and motor execution (ME), but the role of resting-state functional connectivity (RSFC) is unclear.
Purpose of the Study:
- Investigate the relationship between RSFC in the MI network and brain activation during MI.
- Determine if RSFC predicts behavioral performance in MI tasks.
Main Methods:
- Performed resting-state fMRI and task-based fMRI during ME and MI.
- Used behavioral chronometry to assess movement duration and performance index (IP).
- Analyzed voxel-matched correlations between MI activation and seed-based RSFC maps.
Main Results:
- Inter-individual differences in intrinsic connectivity within the MI network predicted activation in several brain clusters.
- RSFC was found to be predictive of MI brain region activation.
- This connectivity predicted regions associated with behavioral performance.
Conclusions:
- RSFC within the MI network is a predictor of MI-related brain activation.
- RSFC may be crucial for understanding the neural underpinnings of MI ability.
- Findings suggest a role for RSFC in MI and its potential applications in rehabilitation.
