Similar articles

Abstract: The difference between sleep and wakefulness is critical for human health. Sleep takes up one third of our lives and remains one of the most mysterious conditions; it plays an important role in memory consolidation and health restoration. Distinct neural behaviors take place under awake and asleep conditions, according to neuroimaging studies. While disordered transitions between wakefulness and sleep accompany brain disease, further investigation of their specific characteristics is required. In this study, the difference is objectively quantified by means of network controllability. We propose a new pipeline using a public intracranial stereo-electroencephalography (stereo-EEG) dataset to unravel differences in the two conditions in terms of system neuroscience. Because intracranial stereo-EEG records neural oscillations covering large-scale cerebral areas, it offers the highest temporal resolution for recording neural behaviors. After EEG preprocessing, the EEG signals are band-passed into sub-slow (0.1?�?1 Hz), delta (1?�?4 Hz), theta (4?�?8 Hz), alpha (8?�?13 Hz), beta (13?�?30 Hz), and gamma (30?�?45 Hz) band oscillations. Then, dynamic functional connectivity is extracted from time-windowed EEG neural oscillations through phase-locking value (PLV) and non-overlapping sliding time windows. Next, average and modal network controllability are implemented on these time-varying brain networks. Based on this preliminary study, it appears that significant differences exist in the dorsolateral frontal-parietal network (FPN), salience network (SN), and default-mode network (DMN). The combination of network controllability and dynamic functional networks offers new insight for characterizing distinctions between awake and asleep stages in the brain. In other words, network controllability captures the underlying brain dynamics under both awake and asleep conditions.

大脑清醒和睡眠状态下的网络可控性分析

[1]AndrillonT, BurnsA, MackayT, et al., 2021. Predicting lapses of attention with sleep-like slow waves. Nat Commun, 12:3657.

[2]BeynelL, DengLF, CrowellCA, et al., 2020. Structural controllability predicts functional patterns and brain stimulation benefits associated with working memory. J Neurosci, 40(35):6770-6778.

[3]ChengW, RollsET, RuanHT, et al., 2018. Functional connectivities in the brain that mediate the association between depressive problems and sleep quality. JAMA Psychiatry, 75(10):1052-1061.

[4]CornblathEJ, TangE, BaumGL, et al., 2019. Sex differences in network controllability as a predictor of executive function in youth. NeuroImage, 188:122-134.

[5]DoellingKB, AssaneoMF, 2021. Neural oscillations are a start toward understanding brain activity rather than the end. PLoS Biol, 19(5):e3001234.

[6]GuS, PasqualettiF, CieslakM, et al., 2015. Controllability of structural brain networks. Nat Commun, 6:8414.

[7]IoannidesAA, 2018. Neurofeedback and the neural representation of self: lessons from awake state and sleep. Front Hum Neurosci, 12:142.

[8]KenettYN, MedagliaJD, BeatyRE, et al., 2018. Driving the brain towards creativity and intelligence: a network control theory analysis. Neuropsychologia, 118(Pt A):79-90.

[9]KinreichS, PodlipskyI, JamshyS, et al., 2014. Neural dynamics necessary and sufficient for transition into pre-sleep induced by EEG NeuroFeedback. NeuroImage, 97:19-28.

[10]KlimeschW, 2018. The frequency architecture of brain and brain body oscillations: an analysis. Eur J Neurosci, 48(7):2431-2453.

[11]LiaoZL, TanYF, QiuYJ, et al., 2018. Interhemispheric functional connectivity for Alzheimer’s disease and amnestic mild cognitive impairment based on the triple network model. J Zhejiang Univ-Sci B (Biomed & Biotechnol), 19(12):924-934.

[12]MedagliaJD, HarveyDY, KelkarAS, et al., 2021. Language tasks and the network control role of the left inferior frontal gyrus. eNeuro, 8(5):ENEURO.0382-20.2021.

[13]ParkesL, MooreTM, CalkinsME, et al., 2021. Network controllability in transmodal cortex predicts positive psychosis spectrum symptoms. Biol Psychiatry, 90(6):409-418.

[14]SarassoS, D'AmbrosioS, FecchioM, et al., 2020. Local sleep-like cortical reactivity in the awake brain after focal injury. Brain, 143(12):3672-3684.

[15]TangBQ, ZhangWJ, DengSK, et al., 2022. Age-associated network controllability changes in first episode drug-naïve schizophrenia. BMC Psychiatry, 22:26.

[16]WuY, ZhaoWR, ChenXY, et al., 2020. Aberrant awake spontaneous brain activity in obstructive sleep apnea: a review focused on resting-state EEG and resting-state fMRI. Front Neurol, 11:768.

[17]XueSW, LeeTW, GuoYH, 2018. Spontaneous activity in medial orbitofrontal cortex correlates with trait anxiety in healthy male adults. J Zhejiang Univ-Sci B (Biomed & Biotechnol), 19(8):643-653.