Research abstract:
Although altered resting-state functional connectivity is a characteristic of many chronic pain conditions it has not yet been evaluated in patients with chronic fatigue. Our objective was to investigate the association between fatigue and altered resting-state functional connectivity in myalgic-encephalomyelitis/chronic fatigue syndrome (ME/CFS).
Thirty-six female subjects, 19 ME/CFS and 17 healthy controls completed a fatigue inventory before undergoing functional magnetic-resonance imaging. Two methods, 1) data driven and 2) model-based, were used to estimate and compare the intra-regional functional connectivity between both groups during the resting state (RS).
The first approach using independent-component analysis was applied to investigate five RS-networks: the default mode network (DMN), salience network (SN), left and right fronto-parietal networks (LFPN, RFPN), and sensory-motor network (SMN). The second approach used a-priori selected seed regions demonstrating abnormal regional cerebral blood-flow (rCBF) in ME/CFS patients at rest.
In ME/CFS patients, Method-1 identified decreased intrinsic connectivity among regions within the LFPN. Furthermore, the functional connectivity of the left anterior mid-cingulate with the SMN and the connectivity of the left posterior-cingulate cortex with the SN were significantly decreased.
For Method-2, five distinct clusters within the right parahippocampus and occipital lobes, demonstrating significant rCBF reductions in ME/CFS patients were used as seeds. The parahippocampal seed and three occipital-lobe seeds showed altered functional connectivity with other brain regions. The degree of abnormal connectivity correlated with the level of self-reported fatigue.
Our results confirm altered RS functional connectivity in patients with ME/CFS which was significantly correlated with the severity of their chronic fatigue.
http://www.ncbi.nlm.nih.gov/pubmed/26449441
Abnormal Resting-State Functional Connectivity in Patients with Chronic Fatigue Syndrome: Results of Seed and Data-Driven Analyses, by C Gay, ME Robinson, S Lai, A O’Shea, J Craggs, DD Price, R Staud in Brain Connect. 2015 Oct 9. [Epub ahead of print]
