Regional impairment of intrinsic functional connectivity strength in patients with chronic primary insomnia

Zheng

et al. 2018

Sci Rep

Primary insomnia (PIs) is highly prevalent and can lead to adverse socioeconomic impacts, but the underlying mechanism of its complex brain network impairment remains largely unknown. Functional studies are too few and diverse in methodology, which makes it difficult to glean general conclusions. To answer this question, we first used graph theory-based network analyse, together with seed-based functional connectivity approach, to characterize the topology architecture of whole-brain functional networks associated with PIs. Forty-eight subjects with PIs and 48 age/sex/education-matched good sleepers were recruited. We found PIs is associated with altered connection properties of intra-networks within the executive control network, default mode network and salience network, and inter-network between auditory language comprehension center and executive control network. These complex networks were correlated with negative emotions and insomnia severity in the PIs group. Altered connection properties of these network hubs appeared to be neural risk factors for neuropsychological changes of PIs, and might be used as potential neuroimaging markers to distinguish the PIs from the good sleepers. These findings highlight the role of functional connectivity in the pathophysiology of PIs, and may underlie the neural mechanisms of etiology of PIs.

Section: Discussionmentioning

confidence: 99%

Altered connection properties of important network hubs may be neural risk factors for individuals with primary insomnia

Zheng

et al. 2018

Sci Rep

“…FDG hypometabolism in aMCI/AD was prevalent in DMN regions (Brown et al, 2014) and larger in spatial extent as compared to patterns of altered functional activity and hypo-connectivity derived from rs-fMRI. This could reflect basic physiological differences between FDG and BOLD signal: the former capitalizes on high stable signal reflecting regionally variable levels of resting-state glucose utilization (Fox et al, 1988) experiencing little or no physiological artifacts, whereas the latter has low intrinsic signal that arises from hemodynamic mechanisms in relation to oxygen consumption (Hyder et al, 2016), which can be affected by in-scanner drowsiness or physiologically altered conditions (Huang et al, 2017, Algarin et al, 2017Zhou et al, 2017. The differences could also arise…”

Section: Discussionmentioning

confidence: 99%

Simultaneous resting-state FDG-PET/fMRI in Alzheimer Disease: Relationship between glucose metabolism and intrinsic activity

et al. 2018

Simultaneously evaluating resting-state brain glucose metabolism and intrinsic functional activity has potential to impact the clinical neurosciences of Alzheimer Disease (AD). Indeed, integrating such combined information obtained in the same physiological setting may clarify how impairments in neuroenergetic and neuronal function interact and contribute to the mechanisms underlying AD. The present study used this multimodality approach to investigate, by means of a hybrid PET/MR scanner, the coupling between glucose consumption and intrinsic functional activity in 23 patients with AD-related cognitive impairment ranging from amnestic mild cognitive impairment (MCI) to mild-moderate AD (aMCI/AD), in comparison with a group of 23 healthy elderly controls. Between-group (Controls > Patients) comparisons were conducted on data from both imaging modalities using voxelwise 2-sample t-tests, corrected for partial-volume effects, head motion, age, gender and multiple tests. FDG-PET/fMRI relationships were assessed within and across subjects using Spearman partial correlations for three different resting-state fMRI (rs-fMRI) metrics sensitive to AD: fractional amplitude of low frequency fluctuations (fALFF), regional homogeneity (ReHo) and group independent component analysis with dual regression (gICA-DR). FDG and rs-fMRI metrics distinguished aMCI/AD from controls according to spatial patterns analogous to those found in stand-alone studies. Within-subject correlations were comparable across the three rs-fMRI metrics. Correlations were overall high in healthy controls (ρ = 0.80 ± 0.04), but showed a significant 17% reduction (p < 0.05) in aMCI/AD patients (ρ = 0.67 ± 0.05). Positive across-subject correlations were overall moderate (ρ = 0.33 ± 0.07) and consistent across rs-fMRI metrics. These were confined around AD-target posterior regions for metrics of functional connectivity (ReHo and gICA-DR). In contrast, FDG/fALFF correlations were distributed in the frontal gyrus, thalami and caudate nuclei. Taken together, these results support the presence of bioenergetic coupling between glucose utilization and rapid transmission of neural information in healthy ageing, which is substantially reduced in aMCI/AD, suggesting that abnormal glucose utilization is in some way linked to communication breakdown among brain regions impacted by the underlying pathological process.

“…Moreover, applied rs-fMRI methods in ID were also diverse e.g. independent component analysis (ICA), amplitude of low-frequency fluctuations (ALFF), regional homogeneity, and whole brain functional connectivity (40)(41)(42)(43)(44)(45)(46)(47). Similarly, although there is no experimental variability in the included structural MRI (27,30,31) and PET studies (32,33), analytical heterogeneity such as various statistical thresholds or spatial transformation of the brain images is an important issue in such studies.…”

Section: Discussionmentioning

confidence: 99%

“…Our screening process yielded 19 studies consisting of 6 task-based fMRI, 8 rs-fMRI, 3 VBM, and 2 PET publications comprising 404 patients with ID and 395 good sleepers (27,(30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40)(41)(42)(43)(44)(45)(46)(47) (Table 1, S1). Recorded data includes the first author's name, year of publication, age, gender, number of subjects, scanning modality, and the peak coordinates (x,y,z) in Talairach (57) or Montreal neurological institute (MNI) (58) stereotactic space.…”

Section: Data Extractionmentioning

confidence: 99%

A lack of consistent brain alterations in insomnia disorder: An activation likelihood estimation meta-analysis

Tahmasian

Noori

Samea

et al. 2018

Sleep Medicine Reviews

Insomnia disorder is a prevalent sleep disorder, which affects about 10% of general population. However, its neural mechanisms are poorly understood. Recently, several structural and functional neuroimaging studies have been conducted in patients with insomnia disorder, but these studies have yielded diverse findings. Here, we aimed to identify consistent patterns of abnormal brain alterations in insomnia disorder by performing a quantitative coordinate-based meta-analysis. Following the preferred reporting for systematic reviews and meta-analyses statement, we searched PubMed database and used reference tracking and finally retrieved 19 eligible studies (six task-based functional magnetic resonance imaging, eight resting-state functional magnetic resonance imaging, three voxel-based morphometry, and two positron emission tomography). We extracted peak coordinates from these studies and tested for convergence using the activation likelihood estimation method. Using this method, we found no significant convergent evidence for combination of structural atrophy and functional disturbances across previous studies (p = 0.914). Inconsistencies across these studies might be related to heterogonous clinical populations, the explorative nature of these studies in combination with small sample sizes, different experimental designs, and various preprocessing and statistical approaches. Future neuroimaging studies on insomnia disorder should include larger well-characterized samples, as well as standard imaging and analysis protocols.