Vibratory (e.g., piezoelectric) devices can stimulate cortical responses from the somatosensory area during functional magnetic resonance imaging. Twelve healthy, right-handed subjects (7 males and 5 females) were scanned with a 3.0 T magnetic resonance imaging scanner and stimulated at 30-240 Hz using a piezoelectric vibrator attached to the subjects’ index fingers. The functional images were analysed to determine the brain activation region by performing random effects analyses at the group level. One-way analysis of variance was used to measure changes in frequency on brain activity. The activated regions were identified with WFU PickAtlas software, and the images were thresholded at Puncorrected < 0.001 for multiple comparisons. The average effect of frequency revealed significant activations in the right insula and right middle frontal gyrus; the corresponding region in the somatosensory area may act as a top-down control signal to improve sensory targets. Results revealed significant differences between frequencies; 90 Hz > 120 Hz activated right inferior parietal gyrus, 120 Hz > 150 Hz activated right cerebellum, and 60 Hz > 90 Hz activated right supramarginal gyrus and bilateral inferior frontal gyrus pars triangularis. Findings indicated the role of secondary somatosensory areas and the cerebellum in performing higher-order functions and discriminating various frequencies during vibratory stimulation. Increasing the patient sample size and testing higher frequencies in future experiments will contribute to furthering brain mapping of somatosensory areas.
This fMRI study investigated the effects of vibratory stimulation on somatosensory areas during high-frequencies stimulation using a piezoelectric finger stimulation system during an fMRI scan. Twelve healthy right-handed subjects were stimulated at 270 Hz-480 Hz and the fMRI dataset was analysed to generate the activated regions due to the high-frequencies stimulation. The activated regions were identified and thresholded at Puncorrected<0.001 for multiple comparisons. The average effect of frequencies revealed significant activation in the left thalamus, right inferior parietal gyrus, right medial frontal gyrus, and right precuneus whereas the main effect of frequencies revealed significant activation in the left thalamus. The positive effect of frequencies displayed significant activation in the left pallidum, right amygdala, right superior temporal gyrus, right medial temporal gyrus. The vibratory stimulation at a frequency of 330 Hz and 360 Hz (330 Hz<360 Hz) revealed a significant difference in the left thalamus. Findings indicated the role of the secondary somatosensory areas processing and transporting sensory information to perform the perceptual and cognitive function.
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.
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