Tag: connectivity

Decreased connectivity and increased BOLD complexity in the default mode network in individuals with chronic fatigue syndrome

Abstract:

The chronic fatigue syndrome / myalgic encephalomyelitis (CFS) is a debilitating disease with unknown pathophysiology and no diagnostic test. This study investigated the default mode network (DMN) in order to understand the pathophysiology of CFS and to identify potential biomarkers.

Using functional MRI (fMRI) collected from 72 subjects (45 CFS and 27 controls) with a temporal resolution of 0.798s, we evaluated the default mode network using static functional connectivity (FC), dynamic functional connectivity (DFC) and DFC complexity, blood oxygenation level dependent (BOLD) activation maps and complexity of activity. General linear model (GLM) univariate analysis was used for inter group comparison to account for age and gender differences. Hierarchical regression analysis was used to test whether fMRI measures could be used to explain variances of health scores.

BOLD signals in the posterior cingulate cortex (PCC), the driving hub in the DMN, were more complex in CFS in both resting state and task (P < 0.05). The FCs between medial prefrontal cortex (mPFC) and both inferior parietal lobules (IPLs) were weaker (P < 0.05) during resting state, while during task mPFC – left IPL and mPFC – PCC were weaker (P < 0.05). The DFCs between the DMN hubs were more complex in CFS (P < 0.05) during task. Each of these differences accounted for 7 – 11% variability of health scores. This study showed that DMN activity is more complex and less coordinated in CFS, suggesting brain network analysis could be potential used as a diagnostic biomarker for CFS.

Source: Shan ZY, Finegan K, Bhuta S, Ireland T, Staines DR, Marshall-Gradisnik SM, Barnden LR. Decreased connectivity and increased BOLD complexity in the default mode network in individuals with chronic fatigue syndrome. Brain Connect. 2017 Nov 20. doi: 10.1089/brain.2017.0549. [Epub ahead of print] https://www.ncbi.nlm.nih.gov/pubmed/29152994

Altered right anterior insular connectivity and loss of associated functions in adolescent chronic fatigue syndrome

Abstract:

Impairments in cognition, pain intolerance, and physical inactivity characterize adolescent chronic fatigue syndrome (CFS), yet little is known about its neurobiology. The right dorsal anterior insular (dAI) connectivity of the salience network provides a motivational context to stimuli. In this study, we examined regional functional connectivity (FC) patterns of the right dAI in adolescent CFS patients and healthy participants.

Eighteen adolescent patients with CFS and 18 aged-matched healthy adolescent control participants underwent resting-state functional magnetic resonance imaging. The right dAI region of interest was examined in a seed-to-voxel resting-state FC analysis using SPM and CONN toolbox. Relative to healthy adolescents, CFS patients demonstrated reduced FC of the right dAI to the right posterior parietal cortex (PPC) node of the central executive network. The decreased FC of the right dAI-PPC might indicate impaired cognitive control development in adolescent CFS. Immature FC of the right dAI-PPC in patients also lacked associations with three known functional domains: cognition, pain and physical activity, which were observed in the healthy group. These results suggest a distinct biological signature of adolescent CFS and might represent a fundamental role of the dAI in motivated behavior.

Source: Wortinger LA, Glenne Øie M, Endestad T, Bruun Wyller V. Altered right anterior insular connectivity and loss of associated functions in adolescent chronic fatigue syndrome. PLoS One. 2017 Sep 7;12(9):e0184325. doi: 10.1371/journal.pone.0184325. ECollection 2017. https://www.ncbi.nlm.nih.gov/pubmed/28880891

Static and dynamic functional connectivity in patients with chronic fatigue syndrome: use of arterial spin labelling fMRI

Abstract:

Studies using arterial spin labelling (ASL) have shown that individuals with chronic fatigue syndrome (CFS) have decreased regional cerebral blood flow, which may be associated with changes in functional neural networks.

Indeed, recent studies indicate disruptions in functional connectivity (FC) at rest in chronically fatigued patients including perturbations in static FC (sFC), that is average FC at rest between several brain regions subserving neurocognitive, motor and affect-related networks.

Whereas sFC often provides information of functional network reorganization in chronic illnesses, investigations of temporal changes in functional connectivity between multiple brain areas may shed light on the dynamic characteristics of brain network activation associated with such maladies.

We used ASL fMRI in 19 patients with CFS and 15 healthy controls (HC) to examine both static and dynamic changes in FC among several a priori selected brain regions during a fatiguing cognitive task. HC showed greater increases than CFS in static FC (sFC) between insula and temporo-occipital structures and between precuneus and thalamus/striatum.

Furthermore, inferior frontal gyrus connectivity to cerebellum, occipital and temporal structures declined in HC but increased in CFS. Patients also showed lower dynamic FC (dFC) between hippocampus and right superior parietal lobule. Both sFC and dFC correlated with task-related fatigue increases.

These data provide the first evidence that perturbations in static and dynamic FC may underlie chronically fatigued patients’ report of task-induced fatigue. Further research will determine whether such changes in sFC and dFC are also characteristic for other fatigued individuals, including patients with chronic pain, cancer and multiple sclerosis.

© 2016 Scandinavian Society of Clinical Physiology and Nuclear Medicine. Published by John Wiley & Sons Ltd.

 

Source: Boissoneault J, Letzen J, Lai S, Robinson ME, Staud R. Static and dynamic functional connectivity in patients with chronic fatigue syndrome: use of arterial spin labelling fMRI. Clin Physiol Funct Imaging. 2016 Sep 28. doi: 10.1111/cpf.12393. [Epub ahead of print] https://www.ncbi.nlm.nih.gov/pubmed/27678090

 

 

Aberrant Resting-State Functional Connectivity in the Salience Network of Adolescent Chronic Fatigue Syndrome

Abstract:

Neural network investigations are currently absent in adolescent chronic fatigue syndrome (CFS). In this study, we examine whether the core intrinsic connectivity networks (ICNs) are altered in adolescent CFS patients.

Eighteen adolescent patients with CFS and 18 aged matched healthy adolescent control subjects underwent resting-state functional magnetic resonance imaging (rfMRI). Data was analyzed using dual-regression independent components analysis, which is a data-driven approach for the identification of independent brain networks. Intrinsic connectivity was evaluated in the default mode network (DMN), salience network (SN), and central executive network (CEN). Associations between network characteristics and symptoms of CFS were also explored.

Adolescent CFS patients displayed a significant decrease in SN functional connectivity to the right posterior insula compared to healthy comparison participants, which was related to fatigue symptoms. Additionally, there was an association between pain intensity and SN functional connectivity to the left middle insula and caudate that differed between adolescent patients and healthy comparison participants.

Our findings of insula dysfunction and its association with fatigue severity and pain intensity in adolescent CFS demonstrate an aberration of the salience network which might play a role in CFS pathophysiology.

 

Source: Wortinger LA, Endestad T, Melinder AM, Øie MG, Sevenius A, Bruun Wyller V. Aberrant Resting-State Functional Connectivity in the Salience Network of Adolescent Chronic Fatigue Syndrome. PLoS One. 2016 Jul 14;11(7):e0159351. doi: 10.1371/journal.pone.0159351. ECollection 2016. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4944916/ (Full article)

 

Abnormal Resting-State Functional Connectivity in Patients with Chronic Fatigue Syndrome: Results of Seed and Data-Driven Analyses

Abstract:

Although altered resting-state functional connectivity (FC) 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 FC 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 intraregional FC 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, salience network (SN), left frontoparietal networks (LFPN) and right frontoparietal networks, and the 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 FC of the left anterior midcingulate 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 FC with other brain regions. The degree of abnormal connectivity correlated with the level of self-reported fatigue.

Our results confirm altered RS FC in patients with ME/CFS, which was significantly correlated with the severity of their chronic fatigue.

 

Source: Gay CW, Robinson ME, Lai S, O’Shea A, Craggs JG, Price DD, Staud R. Abnormal Resting-State Functional Connectivity in Patients with Chronic Fatigue Syndrome: Results of Seed and Data-Driven Analyses. Brain Connect. 2016 Feb;6(1):48-56. doi: 10.1089/brain.2015.0366. Epub 2015 Nov 10. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4744887/ (Full article)