Distinct dynamic functional connectivity patterns of pain and touch thresholds: A resting-state fMRI study


Dynamic functional connectivity (dFC) analysis based on resting-state functional magnetic resonance imaging (fMRI) has gained popularity in recent years. Despite many studies have linked dFC patterns to various mental diseases and cognitive functions, little research has used dFC in the investigation of low-level sensory perception. The present study is aimed to explore resting-state fMRI dFC patterns correlated with thresholds of two types of perception, pain and touch, on an individual basis. We collected and analyzed resting-state fMRI data and thresholds of pain and touch from 80 healthy participants. dFC states were identified by using independent component analysis, sliding window correlation, and clustering, and then the thresholds of pain and touch are correlated with the occurrence frequencies of dFC states. A new permutation analysis is developed to make identified dFC states more interpretable. We found that the occurrence frequency of a default mode network (DMN)-dominated state was positively correlated with the pain threshold, while the occurrence frequency of a static functional connectivity (sFC)-like state was negatively correlated with the touch threshold. This study showed that the thresholds of pain and touch have distinct dFC correlates, suggesting different influences of baseline brain states on different types of sensory perception. This study also showed that dFC could serve as an indicator of an individual’s pain sensitivity, which can be potentially used for pain management.

Behavioural brain research
Gan Huang
Gan Huang

My research interests include Neural Modulation, Brain Computer Interface and Neural Prosthetics.