Investigating cortical networks from vibrotactile stimulation in young adults using independent component analysis: an fMRI study

Abstract

This study investigated the functional connectivity of the neural networks when vibrotactile stimulation is applied to the fingertips of young adults. Twenty healthy, right-handed subjects were stimulated with vibrotactile stimulation whilst being scanned with a 3.0 T magnetic resonance imaging scanner. The subjects were stimulated at 30 Hz – 240 Hz using a piezoelectric vibrator attached to the subjects' bilateral index fingers. The scanned data were processed with independent component analysis (ICA), while the temporal configuration and spatial localisation of the component were investigated. The activation locations were tabulated and compared with regions of somatosensory in the brain. Using ICA, somatosensory regions and their neighbouring areas identified one or more of these components mapped to the common significant regions in the medial frontal gyrus (MFG), paracentral lobule (PaCL), precentral gyrus (PrG), postcentral gyrus (PoG), inferior parietal lobule (IPL), and cingulate gyrus (CgG). Using Neuromark as a reference, six significant networks with the highest correlation values, r>0.5, were identified: the visual network (VIN), sensorimotor network (SMN), cognitive-control network (CCN), subcortical network (SCN), default-mode network (DMN), and auditory network (AUN). It showed that VIN and SMN were the most activated during the vibrotactile stimulation. A comparison of the network volumes and peak activations during the conditions demonstrated changes in volume and corresponding peak activation during vibrotactile stimulation. This study contributes to a better understanding of the underlying mechanisms of the somatosensory areas. Other than that, not only this study highlighted the underlying effect of vibrotactile stimulation towards the functional brain connectivity at network levels, but it also highlighted the impact of frequencies in somatosensory studies. In the future, we suggest that exploring the change in the range of frequencies and examining its differences will allow us to comprehend aspects of somatosensory networks and their connectivity.