Abstract
Brain signals recorded from the primary motor cortex (M1) are known to serve a significant role in coding the information brain–machine interfaces (BMIs) need to perform real and imagined movements, and also to form several functional networks with motor association areas. However, whether functional networks between M1 and other brain regions, such as these motor association areas, are related to the performance of BMIs is unclear. To examine the relationship between functional connectivity and performance of BMIs, we analyzed the correlation coefficient between performance of neural decoding and functional connectivity over the whole brain using magnetoencephalography. Ten healthy participants were instructed to execute or imagine three simple right upper limb movements. To decode the movement type, we extracted 40 virtual channels in the left M1 via the beam forming approach, and used them as a decoding feature. In addition, seed-based functional connectivities of activities in the alpha band during real and imagined movements were calculated using imaginary coherence. Seed voxels were set as the same virtual channels in M1. After calculating the imaginary coherence in individuals, the correlation coefficient between decoding accuracy and strength of imaginary coherence was calculated over the whole brain. The significant correlations were distributed mainly to motor association areas for both real and imagined movements. These regions largely overlapped with brain regions that had significant connectivity to M1. Our results suggest that use of the strength of functional connectivity between M1 and motor association areas has the potential to improve the performance of BMIs to perform real and imagined movements.
Highlights
The brain signals recorded from the primary motor cortex (M1) are known to serve a significant role in providing the information necessary for brain–machine interfaces (BMIs)
Considering that our results showed that these brain regions are functionally connected with M1 and exhibit significant correlations between decoding accuracy and strength of functional connectivity, it is possible that the DLPFC and parietal area modulate the M1 activity related to the representation of motor information by interacting with the M1 during imagined movement
Because our results showed that participants with strong functional connectivity between left M1 and right inferior frontal gyrus (IFG) exhibited high decoding accuracy, such inhibition processes in the IFG may work to generate the clear imagery of the movement necessary to decode the imagined movements
Summary
The brain signals recorded from the primary motor cortex (M1) are known to serve a significant role in providing the information necessary for brain–machine interfaces (BMIs) This technology is expected to offer patients who have lost control of voluntary movements, including those with amyotrophic lateral sclerosis (ALS) and spinal cord injury, greater independence, and a higher quality of life by enabling them to control external devices to communicate with others and to manipulate their environment at will (Wolpaw et al, 2002; Birbaumer, 2006; Hirata et al, 2012; Hochberg et al, 2012; Collinger et al, 2013).
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