Alpha and gamma oscillation amplitudes synergistically predict the perception of forthcoming nociceptive stimuli. Issue 2 (2nd November 2015)

• Record Type: Journal Article
• Authors: Tu, Yiheng; Zhang, Zhiguo; Tan, Ao; Peng, Weiwei; Hung, Yeung Sam; Moayedi, Massieh; Iannetti, Gian Domenico; Hu, Li
• Is Part Of: Human brain mapping. Volume 37:Issue 2(2016:Feb.)
• Page Start: 501
• Page End: 514
• Publication Date: 2015-11-02
• Subjects: default mode networks -- prestimulus alpha oscillations -- prestimulus gamma oscillations -- sensorimotor networks -- sensory perception; Brain mapping -- Periodicals; 611.81
• DOI: 10.1002/hbm.23048
• Languages: English
• ISSNs: 1065-9471

Abstract

Abstract: Ongoing fluctuations of intrinsic cortical networks determine the dynamic state of the brain, and influence the perception of forthcoming sensory inputs. The functional state of these networks is defined by the amplitude and phase of ongoing oscillations of neuronal populations at different frequencies. The contribution of functionally different cortical networks has yet to be elucidated, and only a clear dependence of sensory perception on prestimulus alpha oscillations has been clearly identified. Here, we combined electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) in a large sample of healthy participants to investigate how ongoing fluctuations in the activity of different cortical networks affect the perception of subsequent nociceptive stimuli. We observed that prestimulus EEG oscillations in the alpha (at bilateral central regions) and gamma (at parietal regions) bands negatively modulated the perception of subsequent stimuli. Combining information about alpha and gamma oscillations predicted subsequent perception significantly more accurately than either measure alone. In a parallel experiment, we found that prestimulus fMRI activity also modulated the perception of subsequent stimuli: perceptual ratings were higher when the BOLD signal was higher in nodes of the sensorimotor network and lower in nodes of the default mode network. Similar to what observed in the EEG data, prediction accuracy was improved when the amplitude of prestimulus BOLD signals in both networks was combined. These findings provide a comprehensive physiological basis to the idea that dynamic changes in brain state determine forthcoming behavioral outcomes. Hum Brain Mapp 37:501–514, 2016 . ©2015 Wiley Periodicals, Inc.