Spectral and spatial changes of brain rhythmic activity in response to the sustained thermal pain stimulation. Issue 8 (11th May 2016)

• Record Type: Journal Article
• Authors: Huishi Zhang, Clara; Sohrabpour, Abbas; Lu, Yunfeng; He, Bin
• Is Part Of: Human brain mapping. Volume 37:Issue 8(2016:Aug.)
• Page Start: 2976
• Page End: 2991
• Publication Date: 2016-05-11
• Subjects: pain quantification -- source localization -- Granger causality -- electroencephalography -- thermal stimulation; Brain mapping -- Periodicals; 611.81
• DOI: 10.1002/hbm.23220
• Languages: English
• ISSNs: 1065-9471

Abstract

Abstract: The aim of this study was to investigate the neurophysiological correlates of pain caused by sustained thermal stimulation. A group of 21 healthy volunteers was studied. Sixty‐four channel continuous electroencephalography (EEG) was recorded while the subject received tonic thermal stimulation. Spectral changes extracted from EEG were quantified and correlated with pain scales reported by subjects, the stimulation intensity, and the time course. Network connectivity was assessed to study the changes in connectivity patterns and strengths among brain regions that have been previously implicated in pain processing. Spectrally, a global reduction in power was observed in the lower spectral range, from delta to alpha, with the most marked changes in the alpha band. Spatially, the contralateral region of the somatosensory cortex, identified using source localization, was most responsive to stimulation status. Maximal desynchrony was observed when stimulation was present. The degree of alpha power reduction was linearly correlated to the pain rating reported by the subjects. Contralateral alpha power changes appeared to be a robust correlate of pain intensity experienced by the subjects. Granger causality analysis showed changes in network level connectivity among pain‐related brain regions due to high intensity of pain stimulation versus innocuous warm stimulation. These results imply the possibility of using noninvasive EEG to predict pain intensity and to study the underlying pain processing mechanism in coping with prolonged painful experiences. Once validated in a broader population, the present EEG‐based approach may provide an objective measure for better pain management in clinical applications. Hum Brain Mapp 37:2976–2991, 2016 . ©2016 Wiley Periodicals, Inc.