Changes in the cortical network during sleep stage transitions.

Sleep state transitions are closely related to insomnia, drowsiness, and sleep maintenance. However, how the cortical network varies during such a transition process remains unclear. Changes in the cortical interaction during the short-term process of sleep stage transitions were investigated. In all, 40 healthy young participants underwent overnight polysomnography. The phase transfer entropy of six frequency bands was obtained from 16 electroencephalography channels to assess the strength and direction of information flow between the cortical regions. Differences in the cortical network between the first and the last 10 s in a 40-s transition period across wakefulness, N1, N2, N3, and rapid eye movement were, respectively, studied. Various frequency bands exhibited different patterns during the sleep stage transitions. It was found that the mutual transitions between the sleep stages were not necessarily the opposite. More significant changes were observed in the sleep deepening process than in the process of sleep awakening. During sleep stage transitions, changes in the inflow and outflow strength of various cortical regions led to regional differences, but for the entire sleep progress, such an imbalance did not intensify, and a dynamic balance was instead observed. The detailed findings of variations in cortical interactions during sleep stage transition promote understanding of sleep mechanism, sleep process, and sleep function. Additionally, it is expected to provide helpful clues for sleep improvement, like reducing the time required to fall asleep and maintaining sleep depth.

Characterization of specific spatial functional connectivity difference in depression during sleep.

Depression is a common mental illness and a large number of researchers have been still devoted to exploring effective biomarkers for the identification of depression. Few researches have been conducted on functional connectivity (FC) during sleep in depression. In this paper, a novel depression characterization is proposed using specific spatial FC features of sleep electroencephalography (EEG). Overnight polysomnography recordings were obtained from 26 healthy individuals and 25 patients with depression. The weighted phase lag indexes (WPLIs) of four frequency bands and five sleep periods were obtained from 16 EEG channels. The high discriminative connections extracted via feature evaluation and the cross-within variation (CW)-the spatial feature constructed to characterize the different performances in inter- and intra-hemispheric FC based on WPLIs, were utilized to classify patients and normal controls. The results showed that enhanced average FC and spatial differences, higher inter-hemispheric FC and lower intra-hemispheric FC, were found in patients. Furthermore, abnormalities in the inter-hemispheric connections of the temporal lobe in the theta band should be important indicators of depression. Finally, both CW and high discriminative WPLI features performed well in depression screening and CW was more specific for characterizing abnormal cortical EEG performance of depression. Our work investigated and characterized the abnormalities in sleep cortical activity in patients with depression, and may provide potential biomarkers for assisting with depression identification and new insights into the understanding of pathological mechanisms in depression.

Investigation of Sleep-Dependent Activation-Interaction Association Network.

The cortical activation and the interaction between cortical regions were considered to exist a strong correlation in recent neuroscience researches. However, such association during sleep was still unclear. The aim of the present work was to further investigate this association according to an activation-interaction association network. This study included 24 healthy individuals and all of them underwent overnight polysomnography. The absolute spectral powers of three frequency bands and the phase transfer entropy were extracted from six electroencephalogram channels. For each frequency band and sleep stage, activation-interaction association networks were built and correlation analysis was conducted by using Pearson correlation test. Results revealed the evident association between features derived from the two approaches during sleep, and as the sleep deepened, these correlation values attenuated in the alpha band, whereas the inversion happened in the delta band. This study exposed more detailed information of cortical activity during sleep, which will facilitate us to conduct research from a more comprehensive perspective, helping us make a more appropriate evaluation and explanation.

Regional characterization of functional connectivity in patients with sleep apnea hypopnea syndrome during sleep.

Objective. Sleep apnea hypopnea syndrome (SAHS) induces abnormalities in brain function. This study aims to find features that can characterize the impact of SAHS on the brain functional connectivity (FC) during sleep.Approach. Seventy-eight participants (39 SAHS patients and 39 age-matched healthy controls) were recruited and underwent a whole night of polysomnography. The improved weighted phase lag index algorithm was utilized to evaluate FC inδ,θ,α,ß, andγbands of six EEG channels. The regional FC features were further constructed to characterize the asymmetries of FC between the left and right hemispheres, the imbalances of FC between the inter- and intra-hemispheres, and those between the anterior and posterior cortex, respectively. Then, support vector machines and feature evaluation were used to verify the discriminative ability for the abnormal FC in SAHS patients of the above-mentioned features.Main results.The study observed abnormal FC changes in SAHS patients during sleep in multiple frequency bands. Moreover, regional FC features performed better in SAHS screening, and important features were mainly distributed inßandγbands.Significance. Our research exhibited the abnormal regional FC in SAHS patients during sleep, which provided new insights and established indicators to investigate the changes of brain function in patients.

Sleep-Dependent Anomalous Cortical Information Interaction in Patients With Depression.

Depression is a prevalent mental illness with high morbidity and is considered the main cause of disability worldwide. Brain activity while sleeping is reported to be affected by such mental illness. To explore the change of cortical information flow during sleep in depressed patients, a delay symbolic phase transfer entropy of scalp electroencephalography signals was used to measure effective connectivity between cortical regions in various frequency bands and sleep stages. The patient group and the control group shared similar patterns of information flow between channels during sleep. Obvious information flows to the left hemisphere and to the anterior cortex were found. Moreover, the occiput tended to be the information driver, whereas the frontal regions played the role of the receiver, and the right hemispheric regions showed a stronger information drive than the left ones. Compared with healthy controls, such directional tendencies in information flow and the definiteness of role division in cortical regions were both weakened in patients in most frequency bands and sleep stages, but the beta band during the N1 stage was an exception. The computable sleep-dependent cortical interaction may provide clues to characterize cortical abnormalities in depressed patients and should be helpful for the diagnosis of depression.