Functional connectivity dynamics slow with descent from wakefulness to sleep
Autoři:
Mazen El-Baba aff001; Daniel J. Lewis aff002; Zhuo Fang aff003; Adrian M. Owen aff002; Stuart M. Fogel aff002; J. Bruce Morton aff002
Působiště autorů:
Faculty of Medicine, University of Toronto, Toronto, Ontario
aff001; Department of Psychology, Western University, London, Ontario
aff002; Brain and Mind Institute, Western University, London, Ontario
aff003; School of Psychology, University of Ottawa, Ottawa, Ontario
aff004; The Royal’s Institute for Mental Health Research, University of Ottawa, Ottawa, Ontario
aff005; Brain & Mind Institute, University of Ottawa, Ottawa, Ontario
aff006
Vyšlo v časopise:
PLoS ONE 14(12)
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pone.0224669
Souhrn
The transition from wakefulness to sleep is accompanied by widespread changes in brain functioning. Here we investigate the implications of this transition for interregional functional connectivity and their dynamic changes over time. Simultaneous EEG-fMRI was used to measure brain functional activity of 21 healthy participants as they transitioned from wakefulness into sleep. fMRI volumes were independent component analysis (ICA)-decomposed, yielding 42 neurophysiological sources. Static functional connectivity (FC) was estimated from independent component time courses. A sliding window method and k-means clustering (k = 7, L2-norm) were used to estimate dynamic FC. Static FC in Wake and Stage-2 Sleep (NREM2) were largely similar. By contrast, FC dynamics across wake and sleep differed, with transitions between FC states occurring more frequently during wakefulness than during NREM2. Evidence of slower FC dynamics during sleep is discussed in relation to sleep-related reductions in effective connectivity and synaptic strength.
Klíčová slova:
Functional magnetic resonance imaging – Neurophysiology – Electroencephalography – Vision – Anesthesia – Sleep – k means clustering – Dwell time
Zdroje
1. Deco G, Hagmann P, Hudetz AG, Tononi G. Modeling Resting-State Functional Networks When the Cortex Falls Sleep: Local and Global Changes. Cereb Cortex. 2013. doi: 10.1093/cercor/bht176 23845770
2. Horovitz SG, Braun AR, Carr WS, Picchioni D, Balkin TJ, Fukunaga M, et al. Decoupling of the brain’s default mode network during deep sleep. Proc Natl Acad Sci U S A. 2009;106: 11376–11381. doi: 10.1073/pnas.0901435106 19549821
3. Tagliazucchi E, von Wegner F, Morzelewski A, Borisov S, Jahnke K, Laufs H. Automatic sleep staging using fMRI functional connectivity data. Neuroimage. 2012;63: 63–72. doi: 10.1016/j.neuroimage.2012.06.036 22743197
4. Massimini M;, Ferrarelli F;, Huber R;, Esser SK. Breakdown of Cortical Effective Connectivity During Sleep. Science (80-). 2005;309: 2228–2233. doi: 10.1126/science.1117256 16195466
5. Dang-Vu TT, Bonjean M, Schabus M, Boly M, Darsaud A, Desseilles M, et al. Interplay between spontaneous and induced brain activity during human non-rapid eye movement sleep. Proc Natl Acad Sci U S A. 2011;108: 15438–15443. doi: 10.1073/pnas.1112503108 21896732
6. Schabus M, Dang-Vu TT, Heib DPJ, Boly M, Desseilles M, Vandewalle G, et al. The Fate of Incoming Stimuli during NREM Sleep is Determined by Spindles and the Phase of the Slow Oscillation. Front Neurol. 2012;3: 40. doi: 10.3389/fneur.2012.00040 22493589
7. Maquet P, Ruby P, Maudoux A, Albouy G, Sterpenich V, Dang-Vu T, et al. Human cognition during REM sleep and the activity profile within frontal and parietal cortices: a reappraisal of functional neuroimaging data. Progress in brain research. 2005. pp. 219–595. doi: 10.1016/S0079-6123(05)50016-5
8. Tononi G, Cirelli C. Sleep and the price of plasticity: from synaptic and cellular homeostasis to memory consolidation and integration. Neuron. 2014;81: 12–34. doi: 10.1016/j.neuron.2013.12.025 24411729
9. Diering GH, Nirujogi RS, Roth RH, Worley PF, Pandey A, Huganir RL. Homer1a drives homeostatic scaling-down of excitatory synapses during sleep. Science (80-). 2017;355: 511–515. doi: 10.1126/science.aai8355 28154077
10. Fogel SM, Smith CT. The function of the sleep spindle: a physiological index of intelligence and a mechanism for sleep-dependent memory consolidation. Neurosci Biobehav Rev. 2011;35: 1154–1165. doi: 10.1016/j.neubiorev.2010.12.003 21167865
11. Peigneux P, Fogel S, Smith C. Chapter 22 –Memory Processing in Relation to Sleep. Principles and Practice of Sleep Medicine. Principles and Practice of Sleep Medicine. 2017. pp. 335–347.
12. Rasch B, Born J. About Sleep’s Role in Memory. Physiol Rev. 2013;93: 681–766. doi: 10.1152/physrev.00032.2012 23589831
13. Boly M, Perlbarg V, Marrelec G, Schabus M, Laureys S, Doyon J, et al. Hierarchical clustering of brain activity during human nonrapid eye movement sleep. Proc Natl Acad Sci U S A. 2012;109: 5856–61. doi: 10.1073/pnas.1111133109 22451917
14. Larson-Prior LJ, Zempel JM, Nolan TS, Prior FW, Snyder AZ, Raichle ME. Cortical network functional connectivity in the descent to sleep. Proc Natl Acad Sci. 2009;106: 4489–4494. doi: 10.1073/pnas.0900924106 19255447
15. Tagliazucchi E, Crossley N, Bullmore ET, Laufs H. Deep sleep divides the cortex into opposite modes of anatomical???functional coupling. Brain Struct Funct. 2016;221: 4221–4234. doi: 10.1007/s00429-015-1162-0 26650048
16. Hutchison RM, Womelsdorf T, Gati JS, Everling S, Menon RS. Resting-state networks show dynamic functional connectivity in awake humans and anesthetized macaques. Hum Brain Mapp. 2013;34: 2154–2177. doi: 10.1002/hbm.22058 22438275
17. Calhoun VD, Miller R, Pearlson G, Adali T. The Chronnectome: Time-Varying Connectivity Networks as the Next Frontier in fMRI Data Discovery. Neuron. 2014. pp. 262–274. doi: 10.1016/j.neuron.2014.10.015 25374354
18. Allen EA, Damaraju E, Plis SM, Erhardt EB, Eichele T, Calhoun VD. Tracking Whole-Brain Connectivity Dynamics in the Resting State. Cereb Cortex. 2014; 24: 663–676. doi: 10.1093/cercor/bhs352 23146964
19. Allen EA, Damaraju E, Eichele T, Wu L, Calhoun VD. EEG Signatures of Dynamic Functional Network Connectivity States. Brain Topography. 2017: 1–16.
20. Hutchison RM, Morton JB. Tracking the Brain’s Functional Coupling Dynamics over Development. J Neurosci. 2015;35: 6849–6859. doi: 10.1523/JNEUROSCI.4638-14.2015 25926460
21. Abou-Elseoud A, Starck T, Remes J, Nikkinen J, Tervonen O, Kiviniemi V. The effect of model order selection in group PICA. Hum Brain Mapp. 2010;31: 1207–1216. doi: 10.1002/hbm.20929 20063361
22. Xie H, Calhoun VD, Gonzalez-castillo J, Damaraju E, Miller R, Bandettini PA, et al. NeuroImage Whole-brain connectivity dynamics reflect both task-specific and individual-specific modulation: A multitask study. 2018;180: 495–504. doi: 10.1016/j.neuroimage.2017.05.050 28549798
23. Cash SS, Halgren E, Dehghani N, Rossetti AO, Thesen T, Wang CM, et al. The human K-complex represents an isolated cortical down-state. Science (80-). 2009. doi: 10.1126/science.1169626 19461004
24. Csercsa R, Dombovári B, Fabó D, Wittner L, Erss L, Entz L, et al. Laminar analysis of slow wave activity in humans. Brain. 2010. doi: 10.1093/brain/awq169 20656697
25. Massimini M. The Sleep Slow Oscillation as a Traveling Wave. J Neurosci. 2004. doi: 10.1523/JNEUROSCI.1318-04.2004 15295020
26. Mölle M, Marshall L, Gais S, Born J. Grouping of spindle activity during slow oscillations in human non-rapid eye movement sleep. J Neurosci. 2002.
27. Terzano MG, Mancia D, Salati MR, Costani G, Decembrino A, Parrino L. The cyclic alternating pattern as a physiologic component of normal NREM sleep. Sleep. 1985;8: 137–45. doi: 10.1093/sleep/8.2.137 4012156
28. Parrino L, Boselli M, Spaggiari MC, Smerieri A, Terzano MG. Cyclic alternating pattern (CAP) in normal sleep: Polysomnographic parameters in different age groups. Electroencephalogr Clin Neurophysiol. 1998;107: 439–450. doi: 10.1016/s0013-4694(98)00108-4 9922091
29. Terzano MG, Parrino L, Smerieri A, Chervin R, Chokroverty S, Guilleminault C, et al. Erratum: “Atlas, rules, and recording techniques for the scoring of cyclic alternating pattern (CAP) in human sleep” (Sleep Medicine (2001) vol. 2 (6) (537–553)). Sleep Med. 2002;3: 185. doi: 10.1016/S1389-9457(02)00004-7
30. McIntosh AR, Kovacevic N, Itier RJ. Increased brain signal variability accompanies lower behavioral variability in development. PLoS Comput Biol. 2008;4. doi: 10.1371/journal.pcbi.1000106 18604265
31. Saxe GN, Calderone D, Morales LJ. Brain entropy and human intelligence: A resting-state fMRI study. PLoS One. 2018;13. doi: 10.1371/journal.pone.0191582 29432427
32. Hinard V, Mikhail C, Pradervand S, Curie T, Houtkooper RH, Auwerx J, et al. Key Electrophysiological, Molecular, and Metabolic Signatures of Sleep and Wakefulness Revealed in Primary Cortical Cultures. J Neurosci. 2012;32: 12506–12517. doi: 10.1523/JNEUROSCI.2306-12.2012 22956841
33. Huber R, Mäki H, Rosanova M, Casarotto S, Canali P, Casali AG, et al. Human cortical excitability increases with time awake. Cereb Cortex. 2013;23: 332–338. doi: 10.1093/cercor/bhs014 22314045
34. Vahdat S, Fogel S, Benali H, Doyon J. Network-wide reorganization of procedural memory during NREM sleep revealed by fMRI. Elife. 2017;6. doi: 10.7554/eLife.24987 28892464
35. Barttfeld P, Uhrig L, Sitt JD, Sigman M, Jarraya B. Correction for Barttfeld et al., Signature of consciousness in the dynamics of resting-state brain activity. Proc Natl Acad Sci. 2015;112: E5219–E5220. doi: 10.1073/pnas.1515029112 26324930
36. Horovitz SG, Fukunaga M, de Zwart JA, van Gelderen P, Fulton SC, Balkin TJ, et al. Low frequency BOLD fluctuations during resting wakefulness and light sleep: A simultaneous EEG-fMRI study. Hum Brain Mapp. 2008;29: 671–682. doi: 10.1002/hbm.20428 17598166
37. Larson-Prior LJ, Zempel JM, Nolan TS, Prior FW, Snyder AZ, Raichle ME. Cortical network functional connectivity in the descent to sleep. Proc Natl Acad Sci. 2009;106: 4489–4494. doi: 10.1073/pnas.0900924106 19255447
38. Brissenden JA, Levin EJ, Osher DE, Halko MA, Somers DC. Functional Evidence for a Cerebellar Node of the Dorsal Attention Network. J Neurosci. 2016;36: 6083–6096. doi: 10.1523/JNEUROSCI.0344-16.2016 27251628
39. Sämann PG, Wehrle R, Hoehn D, Spoormaker VI, Peters H, Tully C, et al. Development of the brain’s default mode network from wakefulness to slow wave sleep. Cereb Cortex. 2011;21: 2082–2093. doi: 10.1093/cercor/bhq295 21330468
Článok vyšiel v časopise
PLOS One
2019 Číslo 12
- Metamizol jako analgetikum první volby: kdy, pro koho, jak a proč?
- Nejasný stín na plicích – kazuistika
- Masturbační chování žen v ČR − dotazníková studie
- Těžké menstruační krvácení může značit poruchu krevní srážlivosti. Jaký management vyšetření a léčby je v takovém případě vhodný?
- Fixní kombinace paracetamol/kodein nabízí synergické analgetické účinky
Najčítanejšie v tomto čísle
- Methylsulfonylmethane increases osteogenesis and regulates the mineralization of the matrix by transglutaminase 2 in SHED cells
- Oregano powder reduces Streptococcus and increases SCFA concentration in a mixed bacterial culture assay
- The characteristic of patulous eustachian tube patients diagnosed by the JOS diagnostic criteria
- Parametric CAD modeling for open source scientific hardware: Comparing OpenSCAD and FreeCAD Python scripts