Effects of Aging on Cortical Neural Dynamics and Local Sleep Homeostasis in Mice

Healthy aging is associated with marked effects on sleep, including its daily amount and architecture, as well as the specific EEG oscillations. Neither the neurophysiological underpinnings nor the biological significance of these changes are understood, and crucially the question remains whether ag...

Full description

Saved in:
Bibliographic Details
Published inThe Journal of neuroscience Vol. 38; no. 16; pp. 3911 - 3928
Main Authors McKillop, Laura E., Fisher, Simon P., Cui, Nanyi, Peirson, Stuart N., Foster, Russell G., Wafford, Keith A., Vyazovskiy, Vladyslav V.
Format Journal Article
LanguageEnglish
Published United States Society for Neuroscience 18.04.2018
Subjects
Online AccessGet full text

Cover

Loading…
Abstract Healthy aging is associated with marked effects on sleep, including its daily amount and architecture, as well as the specific EEG oscillations. Neither the neurophysiological underpinnings nor the biological significance of these changes are understood, and crucially the question remains whether aging is associated with reduced sleep need or a diminished capacity to generate sufficient sleep. Here we tested the hypothesis that aging may affect local cortical networks, disrupting the capacity to generate and sustain sleep oscillations, and with it the local homeostatic response to sleep loss. We performed chronic recordings of cortical neural activity and local field potentials from the motor cortex in young and older male C57BL/6J mice, during spontaneous waking and sleep, as well as during sleep after sleep deprivation. In older animals, we observed an increase in the incidence of non-rapid eye movement sleep local field potential slow waves and their associated neuronal silent (OFF) periods, whereas the overall pattern of state-dependent cortical neuronal firing was generally similar between ages. Furthermore, we observed that the response to sleep deprivation at the level of local cortical network activity was not affected by aging. Our data thus suggest that the local cortical neural dynamics and local sleep homeostatic mechanisms, at least in the motor cortex, are not impaired during healthy senescence in mice. This indicates that powerful protective or compensatory mechanisms may exist to maintain neuronal function stable across the life span, counteracting global changes in sleep amount and architecture. SIGNIFICANCE STATEMENT The biological significance of age-dependent changes in sleep is unknown but may reflect either a diminished sleep need or a reduced capacity to generate deep sleep stages. As aging has been linked to profound disruptions in cortical sleep oscillations and because sleep need is reflected in specific patterns of cortical activity, we performed chronic electrophysiological recordings of cortical neural activity during waking, sleep, and after sleep deprivation from young and older mice. We found that all main hallmarks of cortical activity during spontaneous sleep and recovery sleep after sleep deprivation were largely intact in older mice, suggesting that the well-described age-related changes in global sleep are unlikely to arise from a disruption of local network dynamics within the neocortex.
AbstractList Healthy aging is associated with marked effects on sleep, including its daily amount and architecture, as well as the specific EEG oscillations. Neither the neurophysiological underpinnings nor the biological significance of these changes are understood, and crucially the question remains whether aging is associated with reduced sleep need or a diminished capacity to generate sufficient sleep. Here we tested the hypothesis that aging may affect local cortical networks, disrupting the capacity to generate and sustain sleep oscillations, and with it the local homeostatic response to sleep loss. We performed chronic recordings of cortical neural activity and local field potentials from the motor cortex in young and older male C57BL/6J mice, during spontaneous waking and sleep, as well as during sleep after sleep deprivation. In older animals, we observed an increase in the incidence of non-rapid eye movement sleep local field potential slow waves and their associated neuronal silent (OFF) periods, whereas the overall pattern of state-dependent cortical neuronal firing was generally similar between ages. Furthermore, we observed that the response to sleep deprivation at the level of local cortical network activity was not affected by aging. Our data thus suggest that the local cortical neural dynamics and local sleep homeostatic mechanisms, at least in the motor cortex, are not impaired during healthy senescence in mice. This indicates that powerful protective or compensatory mechanisms may exist to maintain neuronal function stable across the life span, counteracting global changes in sleep amount and architecture.SIGNIFICANCE STATEMENT The biological significance of age-dependent changes in sleep is unknown but may reflect either a diminished sleep need or a reduced capacity to generate deep sleep stages. As aging has been linked to profound disruptions in cortical sleep oscillations and because sleep need is reflected in specific patterns of cortical activity, we performed chronic electrophysiological recordings of cortical neural activity during waking, sleep, and after sleep deprivation from young and older mice. We found that all main hallmarks of cortical activity during spontaneous sleep and recovery sleep after sleep deprivation were largely intact in older mice, suggesting that the well-described age-related changes in global sleep are unlikely to arise from a disruption of local network dynamics within the neocortex.Healthy aging is associated with marked effects on sleep, including its daily amount and architecture, as well as the specific EEG oscillations. Neither the neurophysiological underpinnings nor the biological significance of these changes are understood, and crucially the question remains whether aging is associated with reduced sleep need or a diminished capacity to generate sufficient sleep. Here we tested the hypothesis that aging may affect local cortical networks, disrupting the capacity to generate and sustain sleep oscillations, and with it the local homeostatic response to sleep loss. We performed chronic recordings of cortical neural activity and local field potentials from the motor cortex in young and older male C57BL/6J mice, during spontaneous waking and sleep, as well as during sleep after sleep deprivation. In older animals, we observed an increase in the incidence of non-rapid eye movement sleep local field potential slow waves and their associated neuronal silent (OFF) periods, whereas the overall pattern of state-dependent cortical neuronal firing was generally similar between ages. Furthermore, we observed that the response to sleep deprivation at the level of local cortical network activity was not affected by aging. Our data thus suggest that the local cortical neural dynamics and local sleep homeostatic mechanisms, at least in the motor cortex, are not impaired during healthy senescence in mice. This indicates that powerful protective or compensatory mechanisms may exist to maintain neuronal function stable across the life span, counteracting global changes in sleep amount and architecture.SIGNIFICANCE STATEMENT The biological significance of age-dependent changes in sleep is unknown but may reflect either a diminished sleep need or a reduced capacity to generate deep sleep stages. As aging has been linked to profound disruptions in cortical sleep oscillations and because sleep need is reflected in specific patterns of cortical activity, we performed chronic electrophysiological recordings of cortical neural activity during waking, sleep, and after sleep deprivation from young and older mice. We found that all main hallmarks of cortical activity during spontaneous sleep and recovery sleep after sleep deprivation were largely intact in older mice, suggesting that the well-described age-related changes in global sleep are unlikely to arise from a disruption of local network dynamics within the neocortex.
Healthy aging is associated with marked effects on sleep, including its daily amount and architecture, as well as the specific EEG oscillations. Neither the neurophysiological underpinnings nor the biological significance of these changes are understood, and crucially the question remains whether aging is associated with reduced sleep need or a diminished capacity to generate sufficient sleep. Here we tested the hypothesis that aging may affect local cortical networks, disrupting the capacity to generate and sustain sleep oscillations, and with it the local homeostatic response to sleep loss. We performed chronic recordings of cortical neural activity and local field potentials from the motor cortex in young and older male C57BL/6J mice, during spontaneous waking and sleep, as well as during sleep after sleep deprivation. In older animals, we observed an increase in the incidence of non-rapid eye movement sleep local field potential slow waves and their associated neuronal silent (OFF) periods, whereas the overall pattern of state-dependent cortical neuronal firing was generally similar between ages. Furthermore, we observed that the response to sleep deprivation at the level of local cortical network activity was not affected by aging. Our data thus suggest that the local cortical neural dynamics and local sleep homeostatic mechanisms, at least in the motor cortex, are not impaired during healthy senescence in mice. This indicates that powerful protective or compensatory mechanisms may exist to maintain neuronal function stable across the life span, counteracting global changes in sleep amount and architecture. SIGNIFICANCE STATEMENT The biological significance of age-dependent changes in sleep is unknown but may reflect either a diminished sleep need or a reduced capacity to generate deep sleep stages. As aging has been linked to profound disruptions in cortical sleep oscillations and because sleep need is reflected in specific patterns of cortical activity, we performed chronic electrophysiological recordings of cortical neural activity during waking, sleep, and after sleep deprivation from young and older mice. We found that all main hallmarks of cortical activity during spontaneous sleep and recovery sleep after sleep deprivation were largely intact in older mice, suggesting that the well-described age-related changes in global sleep are unlikely to arise from a disruption of local network dynamics within the neocortex.
Healthy aging is associated with marked effects on sleep, including its daily amount and architecture, as well as the specific EEG oscillations. Neither the neurophysiological underpinnings nor the biological significance of these changes are understood, and crucially the question remains whether aging is associated with reduced sleep need or a diminished capacity to generate sufficient sleep. Here we tested the hypothesis that aging may affect local cortical networks, disrupting the capacity to generate and sustain sleep oscillations, and with it the local homeostatic response to sleep loss. We performed chronic recordings of cortical neural activity and local field potentials from the motor cortex in young and older male C57BL/6J mice, during spontaneous waking and sleep, as well as during sleep after sleep deprivation. In older animals, we observed an increase in the incidence of non-rapid eye movement sleep local field potential slow waves and their associated neuronal silent (OFF) periods, whereas the overall pattern of state-dependent cortical neuronal firing was generally similar between ages. Furthermore, we observed that the response to sleep deprivation at the level of local cortical network activity was not affected by aging. Our data thus suggest that the local cortical neural dynamics and local sleep homeostatic mechanisms, at least in the motor cortex, are not impaired during healthy senescence in mice. This indicates that powerful protective or compensatory mechanisms may exist to maintain neuronal function stable across the life span, counteracting global changes in sleep amount and architecture.
Healthy aging is associated with marked effects on sleep, including its daily amount and architecture, as well as the specific EEG oscillations. Neither the neurophysiological underpinnings nor the biological significance of these changes are understood, and crucially the question remains whether aging is associated with reduced sleep need or a diminished capacity to generate sufficient sleep. Here we tested the hypothesis that aging may affect local cortical networks, disrupting the capacity to generate and sustain sleep oscillations, and with it the local homeostatic response to sleep loss. We performed chronic recordings of cortical neural activity and local field potentials from the motor cortex in young and older male C57BL/6J mice, during spontaneous waking and sleep, as well as during sleep after sleep deprivation. In older animals, we observed an increase in the incidence of non-rapid eye movement sleep local field potential slow waves and their associated neuronal silent (OFF) periods, whereas the overall pattern of state-dependent cortical neuronal firing was generally similar between ages. Furthermore, we observed that the response to sleep deprivation at the level of local cortical network activity was not affected by aging. Our data thus suggest that the local cortical neural dynamics and local sleep homeostatic mechanisms, at least in the motor cortex, are not impaired during healthy senescence in mice. This indicates that powerful protective or compensatory mechanisms may exist to maintain neuronal function stable across the life span, counteracting global changes in sleep amount and architecture. The biological significance of age-dependent changes in sleep is unknown but may reflect either a diminished sleep need or a reduced capacity to generate deep sleep stages. As aging has been linked to profound disruptions in cortical sleep oscillations and because sleep need is reflected in specific patterns of cortical activity, we performed chronic electrophysiological recordings of cortical neural activity during waking, sleep, and after sleep deprivation from young and older mice. We found that all main hallmarks of cortical activity during spontaneous sleep and recovery sleep after sleep deprivation were largely intact in older mice, suggesting that the well-described age-related changes in global sleep are unlikely to arise from a disruption of local network dynamics within the neocortex.
Author Cui, Nanyi
Wafford, Keith A.
Vyazovskiy, Vladyslav V.
Peirson, Stuart N.
Foster, Russell G.
McKillop, Laura E.
Fisher, Simon P.
Author_xml – sequence: 1
  givenname: Laura E.
  orcidid: 0000-0003-3085-1175
  surname: McKillop
  fullname: McKillop, Laura E.
– sequence: 2
  givenname: Simon P.
  surname: Fisher
  fullname: Fisher, Simon P.
– sequence: 3
  givenname: Nanyi
  surname: Cui
  fullname: Cui, Nanyi
– sequence: 4
  givenname: Stuart N.
  surname: Peirson
  fullname: Peirson, Stuart N.
– sequence: 5
  givenname: Russell G.
  surname: Foster
  fullname: Foster, Russell G.
– sequence: 6
  givenname: Keith A.
  orcidid: 0000-0002-8508-4738
  surname: Wafford
  fullname: Wafford, Keith A.
– sequence: 7
  givenname: Vladyslav V.
  orcidid: 0000-0002-4336-6681
  surname: Vyazovskiy
  fullname: Vyazovskiy, Vladyslav V.
BackLink https://www.ncbi.nlm.nih.gov/pubmed/29581380$$D View this record in MEDLINE/PubMed
BookMark eNqFUctO3DAUtSoQDJRfQJa6YZPBduzEkSokNJ3y0ABVKWvLc7mZGiX2NE4q8fc4AkbAhtVdnIfOPWePbPngkZBDzqZcifz48np-9_vmdnYxFYrnGS-ngnH9hUwSWmVCMr5FJkyULCtkKXfJXowPjLGS8XKH7IpKaZ5rNiG_5nWN0Ecaanq6cn5Fg6ez0PUObEOvcejS-fHobesgUuvv6SKMyG2DuKbnocUQextdpM7TKwf4lWzXtol48HL3yd3P-Z_Zeba4ObuYnS4yUEz3WV6j1AgVAKhcWpZbkBoKAK5BgLBiyRGXyLWu6hS7hEothSpkoS2owqp8n5w8-66HZYv3gL5PUc26c63tHk2wzrxHvPtrVuG_UVVqQclkcPRi0IV_A8betC4CNo31GIZoUp8Vk7JkRaJ--0B9CEPn03uJVUnFGJej4eHbRJsor2UnQvFMgC7E2GG9oXBmxlXNZlUzrmp4OabQSfj9gxBcb3sXxs9c85n8CUuYqMA
CitedBy_id crossref_primary_10_7554_eLife_54148
crossref_primary_10_1093_sleep_zsz157
crossref_primary_10_3233_JAD_230527
crossref_primary_10_1016_j_neuron_2024_09_017
crossref_primary_10_1016_j_arr_2019_04_006
crossref_primary_10_1016_j_jsmc_2023_06_007
crossref_primary_10_3389_fnagi_2021_682388
crossref_primary_10_1016_j_cophys_2019_10_020
crossref_primary_10_3389_fneur_2022_955298
crossref_primary_10_1016_j_bcp_2021_114563
crossref_primary_10_1093_braincomms_fcac089
crossref_primary_10_1186_s12915_021_00982_w
crossref_primary_10_1038_s41598_021_04502_2
crossref_primary_10_1093_sleep_zsab194
crossref_primary_10_1126_sciadv_abb3567
crossref_primary_10_3390_brainsci11081003
crossref_primary_10_1111_jsr_13603
crossref_primary_10_3390_cells12111477
crossref_primary_10_1016_j_nbas_2023_100068
crossref_primary_10_1016_j_bbr_2019_01_017
crossref_primary_10_1152_ajpregu_00383_2018
crossref_primary_10_1371_journal_pone_0304306
crossref_primary_10_3389_fnins_2023_1173537
crossref_primary_10_7554_eLife_64337
crossref_primary_10_1016_j_ijbiomac_2023_124609
crossref_primary_10_1038_s41593_022_01214_2
crossref_primary_10_1016_j_neurobiolaging_2019_02_004
crossref_primary_10_1038_s41467_024_50166_7
crossref_primary_10_1111_acel_13021
crossref_primary_10_1016_j_neuroscience_2019_11_033
crossref_primary_10_1111_jsr_13399
crossref_primary_10_1093_sleepadvances_zpac022
crossref_primary_10_1111_ejn_16460
crossref_primary_10_3389_fnagi_2022_988166
crossref_primary_10_1016_j_cub_2025_02_053
crossref_primary_10_26508_lsa_202301992
crossref_primary_10_1080_07420528_2023_2253299
crossref_primary_10_1186_s12868_023_00780_w
crossref_primary_10_3389_fnsys_2019_00051
crossref_primary_10_1016_j_cophys_2020_03_004
crossref_primary_10_1016_j_cell_2019_08_040
crossref_primary_10_1038_s41593_021_00894_6
crossref_primary_10_1371_journal_pcbi_1012245
crossref_primary_10_1111_jsr_13262
crossref_primary_10_7554_eLife_84740
crossref_primary_10_1038_s41598_022_11888_0
crossref_primary_10_3389_fnins_2021_616760
crossref_primary_10_3389_fnagi_2018_00233
crossref_primary_10_1007_s10072_023_07232_7
crossref_primary_10_1016_j_bcp_2021_114515
Cites_doi 10.1016/j.cub.2016.08.035
10.1016/S1388-2457(99)00020-6
10.1016/0006-8993(95)00713-Z
10.1159/000336149
10.2174/156802611797470330
10.1016/B0-72-160797-7/50014-8
10.1016/j.neurobiolaging.2012.05.018
10.12871/0002982920142310
10.1097/00001756-199707280-00027
10.1016/S0306-4522(01)00285-8
10.1016/j.neurobiolaging.2004.03.004
10.1016/j.cub.2015.11.062
10.1038/nature07150
10.1038/nrn1809
10.1523/JNEUROSCI.5773-08.2009
10.1038/nature04285
10.1016/j.neurobiolaging.2008.06.003
10.1038/nrn3494
10.1002/hbm.21374
10.1016/S1388-2457(00)00542-3
10.1016/j.ceca.2009.11.013
10.1016/j.neuron.2012.08.015
10.1038/nature14979
10.1113/jphysiol.2012.227462
10.1212/WNL.42.3.527
10.1093/cercor/bht188
10.1093/cercor/bhi110
10.3389/fncir.2015.00088
10.1016/j.neuron.2011.02.043
10.1093/sleep/30.12.1617
10.1016/j.neuron.2016.03.036
10.1038/nrn3208
10.1016/j.lfs.2015.10.025
10.1371/journal.pone.0050677
10.1523/JNEUROSCI.3956-14.2015
10.1016/S0079-6123(02)38086-5
10.1038/nature08983
10.1016/j.neuron.2017.05.015
10.1093/geronj/41.5.579
10.1126/science.aad1023
10.1523/ENEURO.0064-15.2015
10.1111/j.1460-9568.2010.07543.x
10.1016/0006-8993(71)90358-1
10.1212/01.WNL.0000161871.83614.BB
10.1523/JNEUROSCI.1318-04.2004
10.1016/j.neurobiolaging.2010.05.010
10.1111/j.1558-5646.2008.00392.x
10.1016/j.conb.2014.09.001
10.1111/j.1460-9568.2009.06722.x
10.1016/j.neuron.2017.02.004
10.1111/j.1460-9568.2004.03580.x
10.1016/j.smrv.2015.08.005
10.1523/JNEUROSCI.5685-07.2008
10.1098/rspb.2015.1853
10.1038/nrn2402
10.1152/ajpregu.1993.265.5.R1216
10.1016/j.tips.2005.09.009
10.1038/srep43656
10.1152/jn.2000.84.4.1888
10.1007/s12035-011-8164-6
10.1007/s00335-016-9639-6
10.1523/JNEUROSCI.6410-09.2010
10.1016/j.conb.2017.05.002
10.1007/s12017-012-8175-0
10.3389/fpsyg.2013.00863
10.1523/JNEUROSCI.2306-12.2012
10.1038/nrn3230
10.1016/j.cub.2008.06.047
10.1016/j.neurobiolaging.2012.05.020
10.1196/annals.1417.030
10.1007/s11357-009-9102-7
10.1093/sleep/26.2.192
10.1093/sleep/16.1.40
10.1016/j.arr.2014.01.003
10.1523/JNEUROSCI.19-11-04595.1999
10.1002/cne.10714
10.1016/j.neurobiolaging.2014.07.040
10.1016/0013-4694(71)90271-9
10.1016/S0197-4580(03)00043-5
10.1152/ajpregu.2000.278.1.R125
10.1016/j.neuroscience.2007.07.014
10.1523/JNEUROSCI.1156-13.2014
10.1038/nature10009
10.1016/j.neuron.2009.08.024
10.1016/0013-4694(86)90044-1
10.1038/nn.3324
10.1002/(SICI)1099-1166(199912)14:12<1050::AID-GPS56>3.0.CO;2-Z
10.1016/B978-0-444-53702-7.00011-7
10.1038/nrn3200
10.12871/000298292014239
10.1016/j.brainres.2012.12.047
10.1152/jn.91157.2008
10.1371/journal.pone.0043224
10.1093/sleep/30.12.1643
10.1016/j.bbr.2005.09.001
10.1038/nrn2521
10.1016/j.neuron.2013.12.025
10.1038/nrm3025
10.1073/pnas.1218731110
10.1111/ejn.12238
10.1038/nrn3086
10.4449/aib.v139i3.503
10.1038/ncomms13138
10.1126/science.982039
10.1093/sleep/27.7.1255
10.1111/j.1365-2869.2005.00456.x
10.1053/smrv.2002.0252
10.1111/j.1365-2826.2006.01452.x
10.1038/emboj.2011.162
10.1113/jphysiol.1980.sp013521
10.1371/journal.pone.0081880
10.1073/pnas.1423136112
10.1016/0197-4580(89)90004-3
10.1155/2016/6936381
10.1016/j.tins.2009.12.003
10.1016/j.neuron.2015.09.012
10.1523/JNEUROSCI.21-08-02610.2001
10.1016/j.conb.2017.05.008
10.1159/000124330
10.1016/j.smrv.2011.02.003
10.1093/sleep/30.12.1631
10.1016/S0006-8993(02)02925-6
10.1038/nature14622
10.1038/nature10243
10.1109/TIT.1982.1056489
10.1016/j.neuron.2012.08.034
10.1073/pnas.1424706112
10.1016/j.neuron.2008.09.014
10.1111/j.1753-4887.2010.00343.x
10.1016/j.tins.2007.04.006
10.1016/S0006-8993(96)00770-6
10.1016/j.smrv.2009.01.001
10.1126/science.1241224
10.1152/jn.00858.2013
10.1016/S0306-4522(97)00186-3
10.1523/JNEUROSCI.1614-16.2016
ContentType Journal Article
Copyright Copyright © 2018 McKillop et al.
Copyright Society for Neuroscience Apr 18, 2018
Copyright © 2018 McKillop et al. 2018
Copyright_xml – notice: Copyright © 2018 McKillop et al.
– notice: Copyright Society for Neuroscience Apr 18, 2018
– notice: Copyright © 2018 McKillop et al. 2018
DBID AAYXX
CITATION
CGR
CUY
CVF
ECM
EIF
NPM
7QG
7QR
7TK
7U7
7U9
8FD
C1K
FR3
H94
P64
7X8
5PM
DOI 10.1523/JNEUROSCI.2513-17.2018
DatabaseName CrossRef
Medline
MEDLINE
MEDLINE (Ovid)
MEDLINE
MEDLINE
PubMed
Animal Behavior Abstracts
Chemoreception Abstracts
Neurosciences Abstracts
Toxicology Abstracts
Virology and AIDS Abstracts
Technology Research Database
Environmental Sciences and Pollution Management
Engineering Research Database
AIDS and Cancer Research Abstracts
Biotechnology and BioEngineering Abstracts
MEDLINE - Academic
PubMed Central (Full Participant titles)
DatabaseTitle CrossRef
MEDLINE
Medline Complete
MEDLINE with Full Text
PubMed
MEDLINE (Ovid)
Virology and AIDS Abstracts
Technology Research Database
Toxicology Abstracts
Animal Behavior Abstracts
AIDS and Cancer Research Abstracts
Chemoreception Abstracts
Engineering Research Database
Neurosciences Abstracts
Biotechnology and BioEngineering Abstracts
Environmental Sciences and Pollution Management
MEDLINE - Academic
DatabaseTitleList MEDLINE - Academic
CrossRef
Virology and AIDS Abstracts
MEDLINE

Database_xml – sequence: 1
  dbid: NPM
  name: PubMed
  url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed
  sourceTypes: Index Database
– sequence: 2
  dbid: EIF
  name: MEDLINE
  url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search
  sourceTypes: Index Database
DeliveryMethod fulltext_linktorsrc
Discipline Anatomy & Physiology
Architecture
EISSN 1529-2401
EndPage 3928
ExternalDocumentID PMC5907054
29581380
10_1523_JNEUROSCI_2513_17_2018
Genre Research Support, Non-U.S. Gov't
Journal Article
GrantInformation_xml – fundername: Wellcome Trust
– fundername: Biotechnology and Biological Sciences Research Council
  grantid: BB/K011847/1
– fundername: Wellcome Trust
  grantid: 098461/Z/12/Z
– fundername: Medical Research Council
  grantid: MR/L003635/1
GroupedDBID ---
-DZ
-~X
.55
18M
2WC
34G
39C
53G
5GY
5RE
5VS
AAFWJ
AAJMC
AAYXX
ABBAR
ABIVO
ACGUR
ACNCT
ADBBV
ADCOW
ADHGD
AENEX
AFCFT
AFOSN
AFSQR
AHWXS
ALMA_UNASSIGNED_HOLDINGS
AOIJS
BAWUL
BTFSW
CITATION
CS3
DIK
DU5
E3Z
EBS
EJD
F5P
GX1
H13
HYE
H~9
KQ8
L7B
OK1
P0W
P2P
QZG
R.V
RHI
RPM
TFN
TR2
W8F
WH7
WOQ
X7M
YBU
YHG
YKV
YNH
YSK
CGR
CUY
CVF
ECM
EIF
NPM
7QG
7QR
7TK
7U7
7U9
8FD
C1K
FR3
H94
P64
7X8
5PM
ID FETCH-LOGICAL-c508t-3fe48ec9ccc534a03ac48c6cc18c2c2a2b1eebe1889f0077c95b256468ac56a53
ISSN 0270-6474
1529-2401
IngestDate Thu Aug 21 17:55:25 EDT 2025
Fri Jul 11 12:25:53 EDT 2025
Mon Jun 30 16:43:31 EDT 2025
Sat May 31 02:09:26 EDT 2025
Tue Jul 01 03:47:44 EDT 2025
Thu Apr 24 23:02:21 EDT 2025
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 16
Keywords sleep
neocortex
aging
mice
Language English
License https://creativecommons.org/licenses/by-nc-sa/4.0
Copyright © 2018 McKillop et al.
This is an open-access article distributed under the terms of the Creative Commons Attribution License Creative Commons Attribution 4.0 International, which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.
LinkModel OpenURL
MergedId FETCHMERGED-LOGICAL-c508t-3fe48ec9ccc534a03ac48c6cc18c2c2a2b1eebe1889f0077c95b256468ac56a53
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
Author contributions: V.V.V. and K.A.W. designed research; V.V.V., L.E.M., S.P.F., and N.C. performed research; V.V.V., N.C., S.N.P., R.G.F., and K.A.W. contributed unpublished reagents/analytic tools; V.V.V. and L.E.M. analyzed data; V.V.V., and L.E.M. wrote the paper.
ORCID 0000-0002-4336-6681
0000-0003-3085-1175
0000-0002-8508-4738
OpenAccessLink https://pubmed.ncbi.nlm.nih.gov/PMC5907054
PMID 29581380
PQID 2094500144
PQPubID 2049535
PageCount 18
ParticipantIDs pubmedcentral_primary_oai_pubmedcentral_nih_gov_5907054
proquest_miscellaneous_2019044706
proquest_journals_2094500144
pubmed_primary_29581380
crossref_primary_10_1523_JNEUROSCI_2513_17_2018
crossref_citationtrail_10_1523_JNEUROSCI_2513_17_2018
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate 2018-04-18
PublicationDateYYYYMMDD 2018-04-18
PublicationDate_xml – month: 04
  year: 2018
  text: 2018-04-18
  day: 18
PublicationDecade 2010
PublicationPlace United States
PublicationPlace_xml – name: United States
– name: Baltimore
PublicationTitle The Journal of neuroscience
PublicationTitleAlternate J Neurosci
PublicationYear 2018
Publisher Society for Neuroscience
Publisher_xml – name: Society for Neuroscience
References 2023041803303841000_38.16.3911.69
2023041803303841000_38.16.3911.61
2023041803303841000_38.16.3911.62
2023041803303841000_38.16.3911.63
2023041803303841000_38.16.3911.64
2023041803303841000_38.16.3911.65
2023041803303841000_38.16.3911.66
2023041803303841000_38.16.3911.67
2023041803303841000_38.16.3911.68
2023041803303841000_38.16.3911.60
2023041803303841000_38.16.3911.72
2023041803303841000_38.16.3911.140
2023041803303841000_38.16.3911.73
2023041803303841000_38.16.3911.74
2023041803303841000_38.16.3911.75
2023041803303841000_38.16.3911.76
2023041803303841000_38.16.3911.77
2023041803303841000_38.16.3911.78
2023041803303841000_38.16.3911.79
2023041803303841000_38.16.3911.70
2023041803303841000_38.16.3911.71
2023041803303841000_38.16.3911.47
2023041803303841000_38.16.3911.48
2023041803303841000_38.16.3911.49
2023041803303841000_38.16.3911.40
2023041803303841000_38.16.3911.41
2023041803303841000_38.16.3911.42
2023041803303841000_38.16.3911.44
2023041803303841000_38.16.3911.45
2023041803303841000_38.16.3911.46
2023041803303841000_38.16.3911.58
2023041803303841000_38.16.3911.59
2023041803303841000_38.16.3911.50
2023041803303841000_38.16.3911.51
2023041803303841000_38.16.3911.52
2023041803303841000_38.16.3911.53
2023041803303841000_38.16.3911.54
2023041803303841000_38.16.3911.55
2023041803303841000_38.16.3911.56
2023041803303841000_38.16.3911.57
Ge (2023041803303841000_38.16.3911.43) 2002; 23
2023041803303841000_38.16.3911.25
2023041803303841000_38.16.3911.26
2023041803303841000_38.16.3911.27
2023041803303841000_38.16.3911.28
2023041803303841000_38.16.3911.29
2023041803303841000_38.16.3911.20
2023041803303841000_38.16.3911.110
2023041803303841000_38.16.3911.21
2023041803303841000_38.16.3911.111
2023041803303841000_38.16.3911.22
2023041803303841000_38.16.3911.23
2023041803303841000_38.16.3911.113
2023041803303841000_38.16.3911.24
2023041803303841000_38.16.3911.114
2023041803303841000_38.16.3911.115
2023041803303841000_38.16.3911.116
2023041803303841000_38.16.3911.117
2023041803303841000_38.16.3911.118
2023041803303841000_38.16.3911.119
Timofeev (2023041803303841000_38.16.3911.112) 2013; 63
2023041803303841000_38.16.3911.36
2023041803303841000_38.16.3911.37
2023041803303841000_38.16.3911.38
2023041803303841000_38.16.3911.39
2023041803303841000_38.16.3911.5
2023041803303841000_38.16.3911.6
2023041803303841000_38.16.3911.7
2023041803303841000_38.16.3911.30
2023041803303841000_38.16.3911.8
2023041803303841000_38.16.3911.31
2023041803303841000_38.16.3911.9
2023041803303841000_38.16.3911.32
2023041803303841000_38.16.3911.100
2023041803303841000_38.16.3911.33
2023041803303841000_38.16.3911.101
2023041803303841000_38.16.3911.34
2023041803303841000_38.16.3911.102
2023041803303841000_38.16.3911.35
2023041803303841000_38.16.3911.103
2023041803303841000_38.16.3911.104
2023041803303841000_38.16.3911.105
2023041803303841000_38.16.3911.106
2023041803303841000_38.16.3911.107
2023041803303841000_38.16.3911.1
2023041803303841000_38.16.3911.108
2023041803303841000_38.16.3911.2
Borbély (2023041803303841000_38.16.3911.13) 1982; 1
2023041803303841000_38.16.3911.109
2023041803303841000_38.16.3911.3
2023041803303841000_38.16.3911.4
2023041803303841000_38.16.3911.83
2023041803303841000_38.16.3911.84
2023041803303841000_38.16.3911.130
2023041803303841000_38.16.3911.85
2023041803303841000_38.16.3911.131
2023041803303841000_38.16.3911.86
2023041803303841000_38.16.3911.132
2023041803303841000_38.16.3911.87
2023041803303841000_38.16.3911.133
2023041803303841000_38.16.3911.88
2023041803303841000_38.16.3911.134
2023041803303841000_38.16.3911.89
2023041803303841000_38.16.3911.135
2023041803303841000_38.16.3911.136
2023041803303841000_38.16.3911.137
2023041803303841000_38.16.3911.138
2023041803303841000_38.16.3911.139
2023041803303841000_38.16.3911.80
2023041803303841000_38.16.3911.81
2023041803303841000_38.16.3911.82
2023041803303841000_38.16.3911.14
2023041803303841000_38.16.3911.15
2023041803303841000_38.16.3911.16
2023041803303841000_38.16.3911.17
2023041803303841000_38.16.3911.18
2023041803303841000_38.16.3911.19
2023041803303841000_38.16.3911.94
2023041803303841000_38.16.3911.95
2023041803303841000_38.16.3911.96
2023041803303841000_38.16.3911.120
2023041803303841000_38.16.3911.97
2023041803303841000_38.16.3911.121
2023041803303841000_38.16.3911.10
2023041803303841000_38.16.3911.98
2023041803303841000_38.16.3911.122
2023041803303841000_38.16.3911.11
2023041803303841000_38.16.3911.99
2023041803303841000_38.16.3911.123
2023041803303841000_38.16.3911.12
2023041803303841000_38.16.3911.124
2023041803303841000_38.16.3911.125
2023041803303841000_38.16.3911.126
2023041803303841000_38.16.3911.127
2023041803303841000_38.16.3911.128
2023041803303841000_38.16.3911.129
2023041803303841000_38.16.3911.90
2023041803303841000_38.16.3911.91
2023041803303841000_38.16.3911.92
2023041803303841000_38.16.3911.93
References_xml – ident: 2023041803303841000_38.16.3911.89
  doi: 10.1016/j.cub.2016.08.035
– ident: 2023041803303841000_38.16.3911.106
  doi: 10.1016/S1388-2457(99)00020-6
– ident: 2023041803303841000_38.16.3911.130
  doi: 10.1016/0006-8993(95)00713-Z
– ident: 2023041803303841000_38.16.3911.20
  doi: 10.1159/000336149
– ident: 2023041803303841000_38.16.3911.63
  doi: 10.2174/156802611797470330
– ident: 2023041803303841000_38.16.3911.113
  doi: 10.1016/B0-72-160797-7/50014-8
– ident: 2023041803303841000_38.16.3911.54
– ident: 2023041803303841000_38.16.3911.58
  doi: 10.1016/j.neurobiolaging.2012.05.018
– ident: 2023041803303841000_38.16.3911.27
  doi: 10.12871/0002982920142310
– ident: 2023041803303841000_38.16.3911.97
  doi: 10.1097/00001756-199707280-00027
– volume: 63
  start-page: 105
  year: 2013
  ident: 2023041803303841000_38.16.3911.112
  article-title: Local origin of slow EEG waves during sleep
  publication-title: Zh Vyssh Nerv Deiat Im I P Pavlova
– ident: 2023041803303841000_38.16.3911.5
  doi: 10.1016/S0306-4522(01)00285-8
– ident: 2023041803303841000_38.16.3911.23
  doi: 10.1016/j.neurobiolaging.2004.03.004
– ident: 2023041803303841000_38.16.3911.42
  doi: 10.1016/j.cub.2015.11.062
– ident: 2023041803303841000_38.16.3911.99
  doi: 10.1038/nature07150
– ident: 2023041803303841000_38.16.3911.14
  doi: 10.1038/nrn1809
– ident: 2023041803303841000_38.16.3911.134
  doi: 10.1523/JNEUROSCI.5773-08.2009
– ident: 2023041803303841000_38.16.3911.109
  doi: 10.1038/nature04285
– ident: 2023041803303841000_38.16.3911.24
  doi: 10.1016/j.neurobiolaging.2008.06.003
– ident: 2023041803303841000_38.16.3911.118
  doi: 10.1038/nrn3494
– ident: 2023041803303841000_38.16.3911.139
  doi: 10.1002/hbm.21374
– ident: 2023041803303841000_38.16.3911.69
  doi: 10.1016/S1388-2457(00)00542-3
– ident: 2023041803303841000_38.16.3911.115
  doi: 10.1016/j.ceca.2009.11.013
– ident: 2023041803303841000_38.16.3911.45
  doi: 10.1016/j.neuron.2012.08.015
– ident: 2023041803303841000_38.16.3911.132
  doi: 10.1038/nature14979
– ident: 2023041803303841000_38.16.3911.19
  doi: 10.1113/jphysiol.2012.227462
– ident: 2023041803303841000_38.16.3911.22
  doi: 10.1212/WNL.42.3.527
– ident: 2023041803303841000_38.16.3911.76
  doi: 10.1093/cercor/bht188
– ident: 2023041803303841000_38.16.3911.122
  doi: 10.1093/cercor/bhi110
– ident: 2023041803303841000_38.16.3911.88
  doi: 10.3389/fncir.2015.00088
– ident: 2023041803303841000_38.16.3911.90
  doi: 10.1016/j.neuron.2011.02.043
– ident: 2023041803303841000_38.16.3911.37
  doi: 10.1093/sleep/30.12.1617
– ident: 2023041803303841000_38.16.3911.131
  doi: 10.1016/j.neuron.2016.03.036
– ident: 2023041803303841000_38.16.3911.59
  doi: 10.1038/nrn3208
– ident: 2023041803303841000_38.16.3911.35
  doi: 10.1016/j.lfs.2015.10.025
– ident: 2023041803303841000_38.16.3911.120
  doi: 10.1371/journal.pone.0050677
– ident: 2023041803303841000_38.16.3911.33
  doi: 10.1523/JNEUROSCI.3956-14.2015
– ident: 2023041803303841000_38.16.3911.111
  doi: 10.1016/S0079-6123(02)38086-5
– ident: 2023041803303841000_38.16.3911.11
  doi: 10.1038/nature08983
– ident: 2023041803303841000_38.16.3911.104
  doi: 10.1016/j.neuron.2017.05.015
– ident: 2023041803303841000_38.16.3911.133
  doi: 10.1093/geronj/41.5.579
– ident: 2023041803303841000_38.16.3911.49
  doi: 10.1126/science.aad1023
– ident: 2023041803303841000_38.16.3911.87
  doi: 10.1523/ENEURO.0064-15.2015
– ident: 2023041803303841000_38.16.3911.17
  doi: 10.1111/j.1460-9568.2010.07543.x
– ident: 2023041803303841000_38.16.3911.92
  doi: 10.1016/0006-8993(71)90358-1
– ident: 2023041803303841000_38.16.3911.36
  doi: 10.1212/01.WNL.0000161871.83614.BB
– ident: 2023041803303841000_38.16.3911.80
  doi: 10.1523/JNEUROSCI.1318-04.2004
– ident: 2023041803303841000_38.16.3911.48
  doi: 10.1016/j.neurobiolaging.2010.05.010
– ident: 2023041803303841000_38.16.3911.16
  doi: 10.1111/j.1558-5646.2008.00392.x
– ident: 2023041803303841000_38.16.3911.26
  doi: 10.1016/j.conb.2014.09.001
– ident: 2023041803303841000_38.16.3911.40
  doi: 10.1111/j.1460-9568.2009.06722.x
– ident: 2023041803303841000_38.16.3911.77
  doi: 10.1016/j.neuron.2017.02.004
– ident: 2023041803303841000_38.16.3911.84
  doi: 10.1111/j.1460-9568.2004.03580.x
– ident: 2023041803303841000_38.16.3911.66
  doi: 10.1016/j.smrv.2015.08.005
– ident: 2023041803303841000_38.16.3911.86
  doi: 10.1523/JNEUROSCI.5685-07.2008
– ident: 2023041803303841000_38.16.3911.50
  doi: 10.1098/rspb.2015.1853
– volume: 23
  start-page: 1327
  year: 2002
  ident: 2023041803303841000_38.16.3911.43
  article-title: Age-related total gray matter and white matter changes in normal adult brain: I. Volumetric MR imaging analysis
  publication-title: AJNR Am J Neuroradiol
– ident: 2023041803303841000_38.16.3911.4
  doi: 10.1038/nrn2402
– ident: 2023041803303841000_38.16.3911.105
  doi: 10.1152/ajpregu.1993.265.5.R1216
– ident: 2023041803303841000_38.16.3911.55
  doi: 10.1016/j.tips.2005.09.009
– ident: 2023041803303841000_38.16.3911.93
  doi: 10.1038/srep43656
– ident: 2023041803303841000_38.16.3911.53
  doi: 10.1152/jn.2000.84.4.1888
– ident: 2023041803303841000_38.16.3911.8
  doi: 10.1007/s12035-011-8164-6
– ident: 2023041803303841000_38.16.3911.7
  doi: 10.1007/s00335-016-9639-6
– ident: 2023041803303841000_38.16.3911.34
  doi: 10.1523/JNEUROSCI.6410-09.2010
– ident: 2023041803303841000_38.16.3911.128
  doi: 10.1016/j.conb.2017.05.002
– ident: 2023041803303841000_38.16.3911.102
  doi: 10.1007/s12017-012-8175-0
– ident: 2023041803303841000_38.16.3911.68
  doi: 10.3389/fpsyg.2013.00863
– ident: 2023041803303841000_38.16.3911.51
  doi: 10.1523/JNEUROSCI.2306-12.2012
– ident: 2023041803303841000_38.16.3911.137
  doi: 10.1038/nrn3230
– ident: 2023041803303841000_38.16.3911.57
  doi: 10.1016/j.cub.2008.06.047
– ident: 2023041803303841000_38.16.3911.79
  doi: 10.1016/j.neurobiolaging.2012.05.020
– ident: 2023041803303841000_38.16.3911.74
  doi: 10.1196/annals.1417.030
– ident: 2023041803303841000_38.16.3911.10
  doi: 10.1007/s11357-009-9102-7
– ident: 2023041803303841000_38.16.3911.38
  doi: 10.1093/sleep/26.2.192
– ident: 2023041803303841000_38.16.3911.12
  doi: 10.1093/sleep/16.1.40
– ident: 2023041803303841000_38.16.3911.96
  doi: 10.1016/j.arr.2014.01.003
– ident: 2023041803303841000_38.16.3911.29
  doi: 10.1523/JNEUROSCI.19-11-04595.1999
– ident: 2023041803303841000_38.16.3911.78
  doi: 10.1002/cne.10714
– ident: 2023041803303841000_38.16.3911.6
  doi: 10.1016/j.neurobiolaging.2014.07.040
– ident: 2023041803303841000_38.16.3911.52
  doi: 10.1016/0013-4694(71)90271-9
– ident: 2023041803303841000_38.16.3911.98
  doi: 10.1016/S0197-4580(03)00043-5
– ident: 2023041803303841000_38.16.3911.107
  doi: 10.1152/ajpregu.2000.278.1.R125
– ident: 2023041803303841000_38.16.3911.95
  doi: 10.1016/j.neuroscience.2007.07.014
– ident: 2023041803303841000_38.16.3911.71
  doi: 10.1523/JNEUROSCI.1156-13.2014
– ident: 2023041803303841000_38.16.3911.127
  doi: 10.1038/nature10009
– ident: 2023041803303841000_38.16.3911.126
  doi: 10.1016/j.neuron.2009.08.024
– ident: 2023041803303841000_38.16.3911.114
  doi: 10.1016/0013-4694(86)90044-1
– ident: 2023041803303841000_38.16.3911.75
  doi: 10.1038/nn.3324
– ident: 2023041803303841000_38.16.3911.82
  doi: 10.1002/(SICI)1099-1166(199912)14:12<1050::AID-GPS56>3.0.CO;2-Z
– ident: 2023041803303841000_38.16.3911.3
  doi: 10.1016/B978-0-444-53702-7.00011-7
– volume: 1
  start-page: 195
  year: 1982
  ident: 2023041803303841000_38.16.3911.13
  article-title: A two process model of sleep regulation
  publication-title: Hum Neurobiol
– ident: 2023041803303841000_38.16.3911.83
  doi: 10.1038/nrn3200
– ident: 2023041803303841000_38.16.3911.103
  doi: 10.12871/000298292014239
– ident: 2023041803303841000_38.16.3911.47
  doi: 10.1016/j.brainres.2012.12.047
– ident: 2023041803303841000_38.16.3911.125
  doi: 10.1152/jn.91157.2008
– ident: 2023041803303841000_38.16.3911.67
  doi: 10.1371/journal.pone.0043224
– ident: 2023041803303841000_38.16.3911.100
  doi: 10.1093/sleep/30.12.1643
– ident: 2023041803303841000_38.16.3911.60
  doi: 10.1016/j.bbr.2005.09.001
– ident: 2023041803303841000_38.16.3911.64
  doi: 10.1038/nrn2521
– ident: 2023041803303841000_38.16.3911.116
  doi: 10.1016/j.neuron.2013.12.025
– ident: 2023041803303841000_38.16.3911.140
  doi: 10.1038/nrm3025
– ident: 2023041803303841000_38.16.3911.44
  doi: 10.1073/pnas.1218731110
– ident: 2023041803303841000_38.16.3911.65
  doi: 10.1111/ejn.12238
– ident: 2023041803303841000_38.16.3911.25
  doi: 10.1038/nrn3086
– ident: 2023041803303841000_38.16.3911.32
  doi: 10.4449/aib.v139i3.503
– ident: 2023041803303841000_38.16.3911.39
  doi: 10.1038/ncomms13138
– ident: 2023041803303841000_38.16.3911.2
  doi: 10.1126/science.982039
– ident: 2023041803303841000_38.16.3911.91
  doi: 10.1093/sleep/27.7.1255
– ident: 2023041803303841000_38.16.3911.119
  doi: 10.1111/j.1365-2869.2005.00456.x
– ident: 2023041803303841000_38.16.3911.28
  doi: 10.1053/smrv.2002.0252
– ident: 2023041803303841000_38.16.3911.123
  doi: 10.1111/j.1365-2826.2006.01452.x
– ident: 2023041803303841000_38.16.3911.61
  doi: 10.1038/emboj.2011.162
– ident: 2023041803303841000_38.16.3911.9
  doi: 10.1113/jphysiol.1980.sp013521
– ident: 2023041803303841000_38.16.3911.135
  doi: 10.1371/journal.pone.0081880
– ident: 2023041803303841000_38.16.3911.117
  doi: 10.1073/pnas.1423136112
– ident: 2023041803303841000_38.16.3911.31
  doi: 10.1016/0197-4580(89)90004-3
– ident: 2023041803303841000_38.16.3911.21
  doi: 10.1155/2016/6936381
– ident: 2023041803303841000_38.16.3911.15
  doi: 10.1016/j.tins.2009.12.003
– ident: 2023041803303841000_38.16.3911.81
  doi: 10.1016/j.neuron.2015.09.012
– ident: 2023041803303841000_38.16.3911.41
  doi: 10.1523/JNEUROSCI.21-08-02610.2001
– ident: 2023041803303841000_38.16.3911.108
  doi: 10.1016/j.conb.2017.05.008
– ident: 2023041803303841000_38.16.3911.138
  doi: 10.1159/000124330
– ident: 2023041803303841000_38.16.3911.94
  doi: 10.1016/j.smrv.2011.02.003
– ident: 2023041803303841000_38.16.3911.124
  doi: 10.1093/sleep/30.12.1631
– ident: 2023041803303841000_38.16.3911.121
  doi: 10.1016/S0006-8993(02)02925-6
– ident: 2023041803303841000_38.16.3911.62
  doi: 10.1038/nature14622
– ident: 2023041803303841000_38.16.3911.129
  doi: 10.1038/nature10243
– ident: 2023041803303841000_38.16.3911.73
  doi: 10.1109/TIT.1982.1056489
– ident: 2023041803303841000_38.16.3911.18
  doi: 10.1016/j.neuron.2012.08.034
– ident: 2023041803303841000_38.16.3911.46
  doi: 10.1073/pnas.1424706112
– ident: 2023041803303841000_38.16.3911.110
  doi: 10.1016/j.neuron.2008.09.014
– ident: 2023041803303841000_38.16.3911.56
  doi: 10.1111/j.1753-4887.2010.00343.x
– ident: 2023041803303841000_38.16.3911.30
  doi: 10.1016/j.tins.2007.04.006
– ident: 2023041803303841000_38.16.3911.70
  doi: 10.1016/S0006-8993(96)00770-6
– ident: 2023041803303841000_38.16.3911.85
  doi: 10.1016/j.smrv.2009.01.001
– ident: 2023041803303841000_38.16.3911.136
  doi: 10.1126/science.1241224
– ident: 2023041803303841000_38.16.3911.72
  doi: 10.1152/jn.00858.2013
– ident: 2023041803303841000_38.16.3911.1
  doi: 10.1016/S0306-4522(97)00186-3
– ident: 2023041803303841000_38.16.3911.101
  doi: 10.1523/JNEUROSCI.1614-16.2016
SSID ssj0007017
Score 2.4838688
Snippet Healthy aging is associated with marked effects on sleep, including its daily amount and architecture, as well as the specific EEG oscillations. Neither the...
SourceID pubmedcentral
proquest
pubmed
crossref
SourceType Open Access Repository
Aggregation Database
Index Database
Enrichment Source
StartPage 3911
SubjectTerms Aging
Aging - physiology
Animals
Architecture
Cortex (motor)
Cortical Excitability
EEG
Electrophysiological recording
Eye movements
Homeostasis
Life span
Male
Mice
Mice, Inbred C57BL
Motor Cortex - cytology
Motor Cortex - growth & development
Motor Cortex - physiology
Motors
Neurons - physiology
NREM sleep
Oscillations
REM sleep
Senescence
Sleep
Sleep and wakefulness
Sleep deprivation
Sleep Stages
Title Effects of Aging on Cortical Neural Dynamics and Local Sleep Homeostasis in Mice
URI https://www.ncbi.nlm.nih.gov/pubmed/29581380
https://www.proquest.com/docview/2094500144
https://www.proquest.com/docview/2019044706
https://pubmed.ncbi.nlm.nih.gov/PMC5907054
Volume 38
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3db9MwELdgvPCCgPERGMhIiJcpW5PYqfNYVZ3GVgqordS3yHYdLVJJqpI-jL-eO-fDLavE4CWq4qSOfD-fz7673xHyUfEsM0tu_Fgr2KConvIlW2o_zGB9lUKppc2v-DKJL-fsasEXLpTXZpdU6kz_OphX8j9ShXsgV8yS_QfJdn8KN-A3yBeuIGG43kvGIxeMMaiLDWEK36Y-nkbaDdRpdcn5mop5jCvX6XRlzPoUC6SXYBsiI0leYPz8XlSQyxmz1uoO76WLltXX-WpVrtv8aunSGlxF9SmAoXBZZMNt3ij129yp5XzTJH5NKwwybfxDzWFEINCvsq8_Q-uwqeFiDtxrlG4kdsG1q0KjpNa-d3Q7txwTVxMMcZwOP5-BZYbsqhieJ9xq1nrwJ1_Ti_l4nM5Gi9lD8iiEXQSqwevvjky-37MFmbvvaxLIoZ_zw73s2y53NiR_xtXuGCqzp-RJIzM6qOHyjDwwxXNyPChkVf64pZ-ojfm1zpRj8q1BEC0zahFEy4K2CKI1gmiLIAoIohZB1CKI7iCI5gVFBL0g84vRbHjpNzU2fA2meeVHmWHC6ERrzSMme5HUTOhY60DoUIcyVIGBeR4IkWRI_aQTrmAWs1hIDZOZRy_JUVEW5jWhsUqkBEMo08yAWR6rkJkwNoleGsONlB7h7eiluiGgxzooqxQ3ojDqaTfqKY56GvRTHHWPnHfvrWsKlr--cdIKJ22m609oSBjHEwHmkQ9dMyhT9JDJwpRbfAbsY8b6vdgjr2pZdl2GCRdBJHoe6e9JuXsAidr3W4r8xhK28wSwxtmbe_T7ljx28-qEHFWbrXkHZm-l3lvw_gZIPqyN
linkProvider Colorado Alliance of Research Libraries
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Effects+of+Aging+on+Cortical+Neural+Dynamics+and+Local+Sleep+Homeostasis+in+Mice&rft.jtitle=The+Journal+of+neuroscience&rft.au=McKillop%2C+Laura+E&rft.au=Fisher%2C+Simon+P&rft.au=Cui%2C+Nanyi&rft.au=Peirson%2C+Stuart+N&rft.date=2018-04-18&rft.issn=1529-2401&rft.eissn=1529-2401&rft.volume=38&rft.issue=16&rft.spage=3911&rft_id=info:doi/10.1523%2FJNEUROSCI.2513-17.2018&rft.externalDBID=NO_FULL_TEXT
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0270-6474&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0270-6474&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0270-6474&client=summon