Figure - available from: Frontiers in Psychiatry
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Structural covariance connectivity matrix in the sleep restriction condition (left) and full sleep condition (right). The color bar denotes Pearson correlation values with warm colors indicating positive correlation, and blue colors indicating negative correlation. Both conditions had similar covariance connectivity pattern. LH, left hemisphere; RH, right hemisphere.
Source publication
Sleep loss leads to serious health problems, impaired attention, and emotional processing. It has been suggested that the abnormal neurobehavioral performance after sleep deprivation was involved in dysfunction of specific functional connectivity between brain areas. However, to the best of our knowledge, there was no study investigating the struct...
Citations
... The improvement in local efficiency may be connected to the modification of the brain's structural function [29]. Additionally, it has been proposed that the improved local efficiency of brain networks may result from a network's compensatory adaptation brought on by sleep limitation or deprivation [30,31]. Consequently, we postulate that the higher local efficiency in PWSD may be a compensation mechanism set off by the remodeling of brain structures brought on by the interplay of recurrent seizures and sleep disturbances, making their networks more forgiving and lessening the detrimental impacts of the condition. ...
Objective:
The structural covariance network (SCN) alterations in patients with temporal lobe epilepsy and comorbid sleep disorder (PWSD) remain poorly understood. This study aimed to investigate changes in SCNs using structural magnetic resonance imaging.
Methods:
Thirty-four PWSD patients, thirty-three patients with temporal lobe epilepsy without sleep disorder (PWoSD), and seventeen healthy controls underwent high-resolution structural MRI imaging. Subsequently, SCNs were constructed based on gray matter volume and analyzed via graph-theoretical approaches.
Results:
PWSD exhibited significantly increased clustering coefficients, shortest path lengths, transitivity, and local efficiency. In addition, various distributions and numbers of SCN hubs were identified in PWSD. Furthermore, PWSD networks were less robust to random and target attacks than those of healthy controls and PWoSD patients.
Conclusion:
This study identifies aberrant SCN changes in PWSD that may be related to the susceptibility of patients with epilepsy to sleep disorders.
... Our findings suggest that childhood OSA may cause microglial mitochondria dysfunction in cortical neurons and apoptotic neuronal cell death resulting in cortical thinning, consistent with a previous [11] reporting cortical thinning in the superior parietal area. The significant correlation between arousal index and cortical thinning supports previous studies that found an association between the cortical thinning and sleep restriction [44], or sleep fragmentation in adults [20]. Restricted sleep has also been associated with altered slow wave density [45] and glucose metabolism [46], that may alter cortical structure [45]. ...
Study objectives
Intermittent hypoxia and sleep fragmentation due to obstructive sleep apnea (OSA) may contribute to oxidative tissue damage and apoptotic neuronal cell death, inflammation, and intracellular edema in a brain. We examined whether OSA in overweight and obese adolescent children is associated with cortical thickness and hippocampal structure compared to overweight and obese controls and whether OSA severity is associated with measures of brain integrity.
Methods
We calculated cortical thickness and hippocampal subfield volumes from T1-weighted images of 45 controls (age 15.43±1.73 years, 21 male) and 53 adolescent children with OSA (age 15.26±1.63 years, 32 male) to investigate the association of childhood OSA with the alteration of cortical structure and hippocampal subfield structural changes. In addition, we investigated the correlation between OSA severity and cortical thickness or hippocampal subfield volume using Pearson’s correlation analysis.
Results
We found cortical thinning in the right superior parietal area of adolescent children with OSA (cluster size 32.29mm 2, cluster-wise corrected P-value=0.030) that was negatively correlated with apnea-hypopnea index (AHI) (R=−0.27, P-value=0.009) and arousal index (R=−0.25, P-value=0.014). In addition, the volume of right subiculum-head area of the hippocampus of adolescent children with OSA was larger than controls (0.19±0.02ml vs. 0.18±0.02ml, β=13.79, false discovery rate corrected P-value=0.044), and it was positively correlated with AHI (R=0.23, P-value=0.026) and arousal index (R=0.31, P-value=0.002).
Conclusions
Our findings provide evidence for OSA-associated brain structure alterations in adolescent children prior to the onset of treatment that likely have important implications for timely intervention and continued monitoring of health outcomes.
This study examined the stability of the functional connectome (FC) over time using fingerprint analysis in healthy subjects. Additionally, it investigated how a specific stressor, namely sleep deprivation, affects individuals’ differentiation. To this aim, 23 healthy young adults underwent magnetoencephalography (MEG) recording at three equally spaced time points within 24 h: 9 a.m., 9 p.m., and 9 a.m. of the following day after a night of sleep deprivation. The findings indicate that the differentiation was stable from morning to evening in all frequency bands, except in the delta band. However, after a night of sleep deprivation, the stability of the FCs was reduced. Consistent with this observation, the reduced differentiation following sleep deprivation was found to be negatively correlated with the effort perceived by participants in completing the cognitive task during sleep deprivation. This correlation suggests that individuals with less stable connectomes following sleep deprivation experienced greater difficulty in performing cognitive tasks, reflecting increased effort.
The fetal period is a critical stage in brain development, and understanding the characteristics of the fetal brain is crucial. Although some studies have explored aspects of fetal brain functional networks, few have specifically focused on sex differences in brain network characteristics. We adopted the graph theory method to calculate brain network functional connectivity and topology properties (including global and nodal properties), and further compared the differences in these parameters between male and female fetuses. We found that male fetuses showed an increased clustering coefficient and local efficiency than female fetuses, but no significant group differences concerning other graph parameters and the functional connectivity matrix. Our study suggests the existence of sex-related distinctions in the topological properties of the brain network at the fetal stage of development and demonstrates an increase in brain network separation in male fetuses compared with female fetuses.
Background:
Subjective cognitive decline (SCD) may serve as a symptomatic indicator for preclinical Alzheimer's disease; however, SCD is a heterogeneous entity regarding clinical progression. We aimed to investigate whether spatial navigation could reveal subcortical structural alterations and the risk of progression to objective cognitive impairment in SCD individuals.
Methods:
One hundred and eighty participants were enrolled: those with SCD (n = 80), normal controls (NCs, n = 77), and mild cognitive impairment (MCI, n = 23). SCD participants were further divided into the SCD-good (G-SCD, n = 40) group and the SCD-bad (B-SCD, n = 40) group according to their spatial navigation performance. Volumes of subcortical structures were calculated and compared among the four groups, including basal forebrain, thalamus, caudate, putamen, pallidum, hippocampus, amygdala, and accumbens. Topological properties of the subcortical structural covariance network were also calculated. With an interval of 1.5 years ± 12 months of follow-up, the progression rate to MCI was compared between the G-SCD and B-SCD groups.
Results:
Volumes of the basal forebrain, the right hippocampus, and their respective subfields differed significantly among the four groups (p < 0.05, false discovery rate corrected). The B-SCD group showed lower volumes in the basal forebrain than the G-SCD group, especially in the Ch4p and Ch4a-i subfields. Furthermore, the structural covariance network of the basal forebrain and right hippocampal subfields showed that the B-SCD group had a larger Lambda than the G-SCD group, which suggested weakened network integration in the B-SCD group. At follow-up, the B-SCD group had a significantly higher conversion rate to MCI than the G-SCD group.
Conclusion:
Compared to SCD participants with good spatial navigation performance, SCD participants with bad performance showed lower volumes in the basal forebrain, a reorganized structural covariance network of subcortical nuclei, and an increased risk of progression to MCI. Our findings indicated that spatial navigation may have great potential to identify SCD subjects at higher risk of clinical progression, which may contribute to making more precise clinical decisions for SCD individuals who seek medical help.
