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

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

doi:10.1016/j.nicl.2016.12.024

Michelle Case, Bin He + Show 5 more

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https://doi.org/10.1016/j.nicl.2016.12.024

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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.

Highlights

Sickle cell disease (SCD) is an inherited blood disorder that can result in life-long pain (Platt et al, 1991)
Patients are often recalcitrant to Abbreviations: DMN, default mode network; SCD, sickle cell disease; EEG, electroencephalography; functional MRI (fMRI), functional magnetic resonance imaging; RSN, resting state networks; ICA, independent component analysis; bloodoxygen-level dependent (BOLD), blood-oxygen-level dependent; principle component analysis (PCA), principal component analysis; OBS, optimal basis set; CBA, cardioballistic artifact; MNI, montreal neurological institute; FWHM, full width at half maximum; HRF, hemodynamic response function; FDR, false discovery rate; ROI, region of interest; PCC, posterior cingulate cortex; HRF, hemodynamic response function; GLM, general linear model; SMA, supplementary motor area; ECN, executive control network; PAG, periaqueductal gray; PFC, prefrontal cortex
Resting state alterations can lead to biomarkers that can be used to help better understand the neural pathophysiology of sickle pain

Summary

Introduction

Sickle cell disease (SCD) is an inherited blood disorder that can result in life-long pain (Platt et al, 1991). This disorder causes red blood cells to deform into sickle shapes with poor oxygen carrying ability leading to recurrent ischemia-reperfusion injury, end-organ damage, and pain (Rees et al, 2010). In SCD, treatment of pain is challenging because pain episodes can start in infancy and progressively increase throughout life, causing chronic pain. Patients are often recalcitrant to Abbreviations: DMN, default mode network; SCD, sickle cell disease; EEG, electroencephalography; fMRI, functional magnetic resonance imaging; RSN, resting state networks; ICA, independent component analysis; BOLD, blood-oxygen-level dependent; PCA, principal component analysis; OBS, optimal basis set; CBA, cardioballistic artifact; MNI, montreal neurological institute; FWHM, full width at half maximum; HRF, hemodynamic response function; FDR, false discovery rate; ROI, region of interest; PCC, posterior cingulate cortex; HRF, hemodynamic response function; GLM, general linear model; SMA, supplementary motor area; ECN, executive control network; PAG, periaqueductal gray; PFC, prefrontal cortex

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