Science - USA (2021-10-29)

(Antfer) #1

  1. D. Tingley, A. Peyrache,Philos. Trans. R. Soc. London Ser. B
    375 , 20190231 (2020).

  2. B. E. Pfeiffer,Hippocampus 30 ,6–18 (2020).

  3. T. Schreiner, T. Staudigl,Philos. Trans. R. Soc. London Ser. B
    375 , 20190293 (2020).

  4. G. Girardeau, K. Benchenane, S. I. Wiener, G. Buzsáki,
    M. B. Zugaro,Nat. Neurosci. 12 , 1222–1223 (2009).

  5. V. Ego-Stengel, M. A. Wilson,Hippocampus 20 ,1–10 (2010).

  6. G. M. van de Ven, S. Trouche, C. G. McNamara, K. Allen,
    D. Dupret,Neuron 92 , 968–974 (2016).

  7. B. Giri, H. Miyawaki, K. Mizuseki, S. Cheng, K. Diba,J. Neurosci.
    39 , 866–875 (2019).

  8. V. Lopes-Dos-Santoset al.,Neuron 100 , 940–952.e7 (2018).

  9. A. Oliva, A. Fernández-Ruiz, F. Leroy, S. A. Siegelbaum,Nature
    587 , 264–269 (2020).

  10. I. Gridchyn, P. Schoenenberger, J. O’Neill, J. Csicsvari,Neuron
    106 , 291–300.e6 (2020).

  11. S. Lensu, T. Waselius, M. Penttonen, M. S. Nokia,J. Neurophysiol.
    121 , 131–139 (2019).

  12. J. G. Klinzing, N. Niethard, J. Born,Nat. Neurosci. 22 ,
    1598 – 1610 (2019).

  13. N. Maingret, G. Girardeau, R. Todorova, M. Goutierre,
    M. Zugaro,Nat. Neurosci. 19 , 959–964 (2016).

  14. C. V. Latchoumane, H.-V. V. Ngo, J. Born, H.-S. Shin,Neuron
    95 , 424–435.e6 (2017).

  15. L. Marshall, H. Helgadóttir, M. Mölle, J. Born,Nature 444 ,
    610 – 613 (2006).

  16. T. Gulati, L. Guo, D. S. Ramanathan, A. Bodepudi, K. Ganguly,
    Nat. Neurosci. 20 , 1277–1284 (2017).

  17. R. Todorova, M. Zugaro,Science 366 , 377–381 (2019).

  18. I. Skelinet al.,Proc. Natl. Acad. Sci. U.S.A. 118 , e2012075118 (2021).

  19. I. Skelin, S. Kilianski, B. L. McNaughton,Neurobiol. Learn. Mem.
    160 , 21–31 (2019).

  20. G.Rothschild,E.Eban,L.M.Frank,Nat. Neurosci. 20 , 251–259 (2017).

  21. P. A. Lewis, D. Bendor,Curr. Biol. 29 , R906–R912 (2019).

  22. C. S. Lansink, P. M. Goltstein, J. V. Lankelma, B. L. McNaughton,
    C. M. A. Pennartz,PLOS Biol. 7 , e1000173 (2009).

  23. M. Sosa, H. R. Joo, L. M. Frank,Neuron 105 , 725–741.e8 (2020).

  24. G. Girardeau, I. Inema, G. Buzsáki,Nat. Neurosci. 20 ,
    1634 – 1642 (2017).

  25. C. Drieu, R. Todorova, M. Zugaro,Science 362 , 675–679 (2018).

  26. K. Louie, M. A. Wilson,Neuron 29 , 145–156 (2001).

  27. A. Peyrache, M. M. Lacroix, P. C. Petersen, G. Buzsáki,
    Nat. Neurosci. 18 , 569–575 (2015).

  28. S. M. Montgomery, A. Sirota, G. Buzsáki,J. Neurosci. 28 ,
    6731 – 6741 (2008).

  29. D. G. de Almeida-Filhoet al.,Sci. Rep. 11 , 13078 (2021).

  30. J. F. Ramirez-Villegaset al.,Nature 589 , 96–102 (2021).

  31. D. Popa, S. Duvarci, A. T. Popescu, C. Léna, D. Paré,Proc. Natl.
    Acad. Sci. U.S.A. 107 , 6516–6519 (2010).

  32. R. Boyce, S. D. Glasgow, S. Williams, A. Adamantidis,Science
    352 , 812–816 (2016).

  33. D. Kumaret al.,Neuron 107 , 552–565.e10 (2020).

  34. W.Li,L.Ma,G.Yang,W.-B.Gan,Nat. Neurosci. 20 , 427–437 (2017).

  35. L. de Vivoet al.,Science 355 , 507–510 (2017).

  36. V. V. Vyazovskiyet al.,Neuron 63 , 865–878 (2009).

  37. A. D. Grosmark, K. Mizuseki, E. Pastalkova, K. Diba, G. Buzsáki,
    Neuron 75 , 1001–1007 (2012).

  38. H. Miyawaki, K. Diba,Curr. Biol. 26 , 893–902 (2016).

  39. J. H. L. P. Sadowski, M. W. Jones, J. R. Mellor,Cell Rep. 14 ,
    1916 – 1929 (2016).

  40. H. Norimotoet al.,Science 359 , 1524–1527 (2018).

  41. G. R. Poe,J. Neurosci. 37 , 464–473 (2017).

  42. Z. Zhang, L. E. Russell, A. M. Packer, O. M. Gauld, M. Häusser,
    Nat. Methods 15 , 1037–1040 (2018).

  43. D. Levenstein, B. O. Watson, J. Rinzel, G. Buzsáki,Curr. Opin.
    Neurobiol. 44 , 34–42 (2017).

  44. S. Izawaet al.,Science 365 , 1308–1313 (2019).


ACKNOWLEDGMENTS
We thank V. Cazares, L. Roux, D. Almeida-Filho, and members of the
Girardeau lab for helpful comments on the manuscript. We apologize
to all authors whose studies we could not cite because of a focus
on the most recent literature and space restrictions. We acknowledge
that this selection of references does not reflect the highly incremental
and collaborative nature of scientific research.Funding:This work
was supported by an ATIP-Avenir grant; the Fyssen Foundation;
Emergence(s) Ville de Paris; a NARSAD Young Investigator Grant from
the Brain and Behavior Research Foundation and the Schlumberger
Foundation for Science and Education (G.G.); and the Medical
Research Council UK (MC_UU_00003/4; V.L.d.S.).Competing
interests:The authors declare no competing interests. This research
was funded in whole or in part by the Medical Research Council
UK (MC_UU_00003/4), a cOAlition S organization. The author will
make the Author Accepted Manuscript (AAM) version available under
a CC BY public copyright license.


10.1126/science.abi8370


REVIEW

The interconnected causes


and consequences of sleep in the brain


Laura D. Lewis*

Sleep is essential for brain function in a surprisingly diverse set of ways. In the short term, lack of sleep
leads to impaired memory and attention; in the longer term, it produces neurological dysfunction or
even death. I discuss recent advances in understanding how sleep maintains the physiological health of
the brain through interconnected systems of neuronal activity and fluid flow. The neural dynamics
that appear during sleep are intrinsically coupled to its consequences for blood flow, cerebrospinal fluid
dynamics, and waste clearance. Recognizing these linked causes and consequences of sleep has
shed new light on why sleep is important for such disparate aspects of brain function.

O


ur nightly sleep is critical for a wide
array of brain functions. Missing just a
single night of sleep results in memory,
mood, and attentional impairments the
next day ( 1 ); disrupted sleep across the
life span is linked to neurodegeneration ( 2 , 3 ).
These heterogeneous effects of sleep have posed
a puzzle in neuroscience: Why does this brain
state hold a unique role in supporting such
seemingly distinct aspects of brain function?
Decades of work have shown that sleep con-
tains distinct neural dynamics linked to cogni-
tion, such as slow waves in neural activity that
appear in non–rapid eye movement (NREM)
sleep ( 4 ). More recent discoveries have shown
that sleep is also a heightened state for waste
removal from the brain ( 5 , 6 ). Metabolic waste
products are transported out of brain tissue
( 7 ) via the interstitial fluid (ISF) and cerebro-
spinal fluid (CSF), and sleep plays a key role in
both waste regulation and flow of CSF in the
brain ( 8 , 9 ), which is essential for maintaining
neuronal health. These beneficial effects may
explain why we spend so many hours each day
asleep, as sleep’s role in basic housekeeping
for the brain implicates it in broad aspects of
neural function. But why is sleep linked to dis-
tinct fluid dynamics, and why does it play such
a profound role in maintaining brain function?

The control circuits that govern sleep
Sleep is controlled by large-scale arousal regu-
latory systems that can rapidly induce states of
sleep or wakefulness. Extensive circuit-based
investigations have recorded from and manip-
ulated individual brain regions and cell types
to identify their various roles in behavior.
This approach has been powerful, identify-
ing multiple regions in the hypothalamus,
brainstem, basal forebrain, and other subcor-
tical nuclei that control sleep states ( 10 ). Key
interacting circuits include the noradrenergic,

dopaminergic, cholinergic, and orexinergic sys-
tems, which can induce sleep-wake transitions
( 10 ). However, these findings have raised a new
question: Why do so many diverse nuclei play
decisive roles in whether an animal is sleep-
ing or awake?
One possibility is that the system is simply
unusually redundant; sleep is so important
that the brain contains multiple switches to
induce sleep states. However, a second and
perhaps more likely possibility is that these
circuits represent interacting components of
a larger system that induces the many distinct
features of sleep, including altered behavior,
oscillatory neural dynamics, modulated respi-
ratory and vascular physiology, and clearance.
Notably, the circuits that regulate sleep project
widely throughout the forebrain ( 10 ) as well as
to each other, so that activity within one sys-
tem inevitably influences the others. Further-
more, neuromodulators such as noradrenaline
and acetylcholine, which alter neuronal arousal
states, also have direct actions on the vasculature.

Low-frequency neural dynamics
emerge during sleep
During sleep, large-scale neural activity reor-
ganizes into distinctive, oscillatory patterns,
reflecting the wide-ranging reach of arousal
regulatory circuits throughout the thalamo-
cortical networks that generate EEG oscilla-
tions. These patterns have long been recognized
to define distinct stages of sleep, separating
NREM and REM. As sleep progresses into
NREM, many distinct EEG patterns appear,
including spindles (~11 to 14 Hz) and slow
waves, with distinct links to memory and cog-
nition ( 4 ). The increased low-frequency power
is referred to as slow wave activity, a catch-all
term that corresponds to 0.5 to 4 Hz EEG
power, and which can reflect several low-
frequency dynamics (Fig. 1A). These include
individual K-complexes (occurring seconds
or minutes apart), delta (1 to 4 Hz) waves, and
the slow (0.1 to 1 Hz) oscillations that group
and coordinate higher-frequency rhythms
( 11 , 12 ). K-complexes correspond to periods

564 29 OCTOBER 2021•VOL 374 ISSUE 6567 science.orgSCIENCE


Department of Biomedical Engineering, Boston University,
Boston, MA, USA, and Athinoula A. Martinos Center for
Biomedical Imaging, Massachusetts General Hospital,
Boston, MA, USA.
*Corresponding author. Email: [email protected]

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