Decoding spatial location of perceived pain to acupuncture needle using multivoxel pattern analysis

The present study applied multivoxel pattern analysis to decode spatial discrimination in pain perception to acupuncture needle from brain functional magnetic resonance image. Fourteen participants were stimulated by acupuncture needles at two adjacent body parts on their left forearm (PC6 vs. HT7). We trained support vector machines on the spatial information from the whole-brain functional magnetic resonance imaging data and projected the support vector machine weight to the brain image space to represent the effect of each voxel on the classifier output. Using region-of-interest masks in individual brains, we trained and tested a linear support vector machine classifier on the accuracy of spatial discrimination in trial-wise functional magnetic resonance imaging data. A classical univariate general linear model analysis testing for differences between the two different locations did not reveal any significant differences. Multivoxel pattern analysis revealed that the brain regions for the prediction of sensory discrimination in pain perceptions to two different points were in the primary somatosensory cortex, primary motor cortex, and supramarginal gyrus, anterior and posterior insula, anterior and posterior cingulate cortex, ventromedial prefrontal cortex, and inferior parietal lobule. Our findings suggest that spatial localizations of pain perceptions to acupuncture needle can be predicted by the neural response patterns in the somatosensory areas and the frontoparietal areas.