Characterization of functional brain activity and connectivity using EEG and fMRI in patients with sickle cell disease

Michelle Case, Huishi Zhang, John Mundahl, Yvonne H Datta, Stephen Nelson, Kalpna Gupta, Bin He

Research output: Contribution to journalArticlepeer-review

35 Scopus citations

Abstract

Sickle cell disease (SCD) is a red blood cell disorder that causes many complications including life-long pain. Treatment of pain remains challenging due to a poor understanding of the mechanisms and limitations to characterize and quantify pain. In the present study, we examined simultaneously recording functional MRI (fMRI) and electroencephalogram (EEG) to better understand neural connectivity as a consequence of chronic pain in SCD patients. We performed independent component analysis and seed-based connectivity on fMRI data. Spontaneous power and microstate analysis was performed on EEG-fMRI data. ICA analysis showed that patients lacked activity in the default mode network (DMN) and executive control network compared to controls. EEG-fMRI data revealed that the insula cortex's role in salience increases with age in patients. EEG microstate analysis showed patients had increased activity in pain processing regions. The cerebellum in patients showed a stronger connection to the periaqueductal gray matter (involved in pain inhibition), and negative connections to pain processing areas. These results suggest that patients have reduced activity of DMN and increased activity in pain processing regions during rest. The present findings suggest resting state connectivity differences between patients and controls can be used as novel biomarkers of SCD pain.

Original languageEnglish (US)
Pages (from-to)1-17
Number of pages17
JournalNeuroImage: Clinical
Volume14
DOIs
StatePublished - 2017

Bibliographical note

Funding Information:
This work was supported in part by NIH HL117664, AT009263, NS096761, EB021027, EB008389, NSF DGE-1069104, and NSF CBET-1450956.

Keywords

  • EEG
  • Functional MRI
  • Pain
  • Resting state networks
  • Sickle cell disease

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