Sleep deprivation leads to a loss of functional connectivity in frontal brain regions

被引:111
|
作者
Verweij, Ilse M. [1 ]
Romeijn, Nico [1 ]
Smit, Dirk J. A. [2 ]
Piantoni, Giovanni [1 ]
Van Someren, Eus J. W. [1 ,3 ,4 ]
van der Werf, Ysbrand D. [1 ,5 ]
机构
[1] Inst Royal Netherlands Acad Arts & Sci, Netherlands Inst Neurosci, NL-1105 BA Amsterdam, Netherlands
[2] Vrije Univ Amsterdam, Dept Psychol, Amsterdam, Netherlands
[3] Vrije Univ Amsterdam, Fac Earth & Life Sci, Dept Integrat Neurophysiol, Amsterdam, Netherlands
[4] Vrije Univ Amsterdam, Med Ctr, Dept Med Psychol, Amsterdam, Netherlands
[5] Vrije Univ Amsterdam, Med Ctr, Dept Anat & Neurosci, Amsterdam, Netherlands
来源
BMC NEUROSCIENCE | 2014年 / 15卷
关键词
Sleep deprivation; Brain connectivity; Graph theory; EEG analysis; Small-world networks; DEFAULT-MODE NETWORK; GRAPH-THEORETICAL ANALYSIS; SMALL-WORLD NETWORKS; SLOW-WAVE SLEEP; RESTING-STATE; SYNCHRONIZATION LIKELIHOOD; SYNAPTIC HOMEOSTASIS; COMPLEX NETWORKS; EEG; COGNITION;
D O I
10.1186/1471-2202-15-88
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Background: The restorative effect of sleep on waking brain activity remains poorly understood. Previous studies have compared overall neural network characteristics after normal sleep and sleep deprivation. To study whether sleep and sleep deprivation might differentially affect subsequent connectivity characteristics in different brain regions, we performed a within-subject study of resting state brain activity using the graph theory framework adapted for the individual electrode level. In balanced order, we obtained high-density resting state electroencephalography (EEG) in 8 healthy participants, during a day following normal sleep and during a day following total sleep deprivation. We computed topographical maps of graph theoretical parameters describing local clustering and path length characteristics from functional connectivity matrices, based on synchronization likelihood, in five different frequency bands. A non-parametric permutation analysis with cluster correction for multiple comparisons was applied to assess significance of topographical changes in clustering coefficient and path length. Results: Significant changes in graph theoretical parameters were only found on the scalp overlying the prefrontal cortex, where the clustering coefficient (local integration) decreased in the alpha frequency band and the path length (global integration) increased in the theta frequency band. These changes occurred regardless, and independent of, changes in power due to the sleep deprivation procedure. Conclusions: The findings indicate that sleep deprivation most strongly affects the functional connectivity of prefrontal cortical areas. The findings extend those of previous studies, which showed sleep deprivation to predominantly affect functions mediated by the prefrontal cortex, such as working memory. Together, these findings suggest that the restorative effect of sleep is especially relevant for the maintenance of functional connectivity of prefrontal brain regions.
引用
收藏
页数:10
相关论文
共 50 条
  • [41] Altered frontal connectivity after sleep deprivation predicts sustained attentional impairment: A resting-state functional magnetic resonance imaging study
    Cai, Ye
    Mai, Zifeng
    Li, Mingzhu
    Zhou, Xiaolin
    Ma, Ning
    [J]. JOURNAL OF SLEEP RESEARCH, 2021, 30 (05)
  • [42] Differential Impact of REM Sleep Deprivation on Cytoskeletal Proteins of Brain Regions Involved in Sleep Regulation
    Rodriguez-Vazquez, Jennifer
    Camacho-Arroyo, Ignacio
    Velazquez-Moctezuma, Javier
    [J]. NEUROPSYCHOBIOLOGY, 2012, 65 (03) : 161 - 167
  • [43] Interindividual differences in matrix reasoning are linked to functional connectivity between brain regions nominated by Parieto-Frontal Integration Theory
    Fraenz, Christoph
    Schlueter, Caroline
    Friedrich, Patrick
    Jung, Rex E.
    Guenturkuen, Onur
    Genc, Erhan
    [J]. INTELLIGENCE, 2021, 87
  • [44] FUNCTIONAL CONNECTIVITY OF BRAIN NETWORKS PREDICTS POLYSOMNOGRAPHICALLY MEASURED SLEEP
    Killgore, William
    Jankowski, Samantha
    Henderson-Arredondo, Kymberly
    Hildebrand, Lindsey
    Elledge, Heidi
    Lucas, Daniel
    Dailey, Natalie
    [J]. SLEEP, 2023, 46
  • [45] BRAIN FUNCTIONAL CONNECTIVITY IN SLEEP-RELATED HYPERMOTOR EPILEPSY
    Ferri, L.
    Evangelisti, S.
    Rizzo, G.
    Gramegna, L. L.
    Testa, C.
    Licchetta, L.
    Magi, L. Rossi
    Remondini, D.
    Castellani, G.
    Tonon, C.
    Bisulli, F.
    Lodi, R.
    Tinuper, P.
    [J]. EPILEPSIA, 2017, 58 : S124 - S124
  • [46] Brain functional connectivity in sleep-related hypermotor epilepsy
    Evangelisti, Stefania
    Testa, Claudia
    Ferri, Lorenzo
    Gramegna, Laura Ludovica
    Manners, David Neil
    Rizzo, Giovanni
    Remondini, Daniel
    Castellani, Gastone
    Naldi, Ilaria
    Bisulli, Francesca
    Tonon, Caterina
    Tinuper, Paolo
    Lodi, Raffaele
    [J]. NEUROIMAGE-CLINICAL, 2018, 17 : 873 - 881
  • [47] Functional brain connectivity predicts sleep duration in youth and adults
    Mummaneni, Anurima
    Kardan, Omid
    Stier, Andrew J.
    Chamberlain, Taylor A.
    Chao, Alfred F.
    Berman, Marc G.
    Rosenberg, Monica D.
    [J]. HUMAN BRAIN MAPPING, 2023, 44 (18) : 6293 - 6307
  • [48] Altered Sleep Brain Functional Connectivity in Acutely Depressed Patients
    Leistedt, Samuel J. J.
    Coumans, Nathalie
    Dumont, Martine
    Lanquart, Jean-Pol
    Stam, Cornelis J.
    Linkowski, Paul
    [J]. HUMAN BRAIN MAPPING, 2009, 30 (07) : 2207 - 2219
  • [49] Directional Connectivity between Frontal and Posterior Brain Regions Is Altered with Increasing Concentrations of Propofol
    Maksimow, Anu
    Silfverhuth, Minna
    Langsjo, Jaakko
    Kaskinoro, Kimmo
    Georgiadis, Stefanos
    Jaaskelainen, Satu
    Scheinin, Harry
    [J]. PLOS ONE, 2014, 9 (11):
  • [50] Loss in Connectivity Among Regions of the Brain Reward System in Alcohol Dependence
    Kuceyeski, Amy
    Meyerhoff, Dieter J.
    Durazzo, Timothy C.
    Raj, Ashish
    [J]. HUMAN BRAIN MAPPING, 2013, 34 (12) : 3129 - 3142