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

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.

Mast cell‐neural interactions contribute to pain and itch

“…[40][41][42] Brain neuroimaging also demonstrated the existence of central sensitization in patients with SCD. 41,43 Mast cells are also present in the meninges and different regions of the brain including thalamus and are known to influence blood-brain barrier permeability. 26,[44][45][46] Their number and distribution in the brain are affected by the environment, age, gender, pathological condition, and stimuli such as stress.…”

Neuromodulation Management of Chronic Neuropathic Pain in the Central Nervous System

“…Dynamic and precise functional imaging using scalp EEG has been demonstrated to allow for better understanding the brain network and its connectivity of chronic pain in SCD, [27,194] further differentiating SCD severity levels based on graph theory analyses [194] and assisting an objective assessment of tonic thermal pain. [29] More specifically, the EEG-fMRI spontaneous power analyses have depicted the significant differences of neural activities at color-indicated brain regions in both alpha and low beta bands between the SCD patients and healthy controls, as seen in Figure 6a,b.…”

Resting state functional connectivity in early post-anesthesia recovery is characterized by globally reduced anticorrelations

“…Specifically, RSN expression at each peri-anesthetic time-point was quantified as the volume of each RSN, measured as the number of voxels counted in the corresponding ICA component(s) (p<0.001 FDR corrected, cluster size p<0.05 FDR corrected) 26 Similar quantification of RSN volume for all RSNs studied is shown in FIG 2A. In order to facilitate comparison between networks, expression at each time point was normalized to each network's baseline level.…”

“…Specifically, RSN expression at each peri-anesthetic time-point was quantified as the volume of each RSN, measured as the number of voxels counted in the corresponding ICA component(s) (p<0.001 FDR corrected, cluster size p<0.05 FDR corrected) 26…”