Tagliazucchi, E. & van Someren, E. J. W. The large-scale functional connectivity correlates of consciousness and arousal during the healthy and pathological human sleep cycle. Neuroimage 160, 55–72. 10.1016/j.neuroimage.2017.06.026 (2017). DOI: 10.1016/j.neuroimage.2017.06.026
Andrade, K. C. et al. Sleep spindles and hippocampal functional connectivity in human NREM sleep. J. Neurosci. 31, 10331–10339. 10.1523/JNEUROSCI.5660-10.2011 (2011). DOI: 10.1523/JNEUROSCI.5660-10.2011
Boly, M. et al. Hierarchical clustering of brain activity during human nonrapid eye movement sleep. Proc. Natl. Acad. Sci. U.S.A. 109, 5856–5861. 10.1073/pnas.1111133109 (2012). DOI: 10.1073/pnas.1111133109
Hale, J. R. et al. Altered thalamocortical and intra-thalamic functional connectivity during light sleep compared with wake. Neuroimage 125, 657–667. 10.1016/j.neuroimage.2015.10.041 (2016). DOI: 10.1016/j.neuroimage.2015.10.041
Larson-Prior, L. J. et al. Modulation of the brain’s functional network architecture in the transition from wake to sleep. Prog. Brain Res. 193, 277–294. 10.1016/B978-0-444-53839-0.00018-1 (2011). DOI: 10.1016/B978-0-444-53839-0.00018-1
Laufs, H., Walker, M. C. & Lund, T. E. Brain activation and hypothalamic functional connectivity during human non-rapid eye movement sleep: An EEG/fMRI study—Its limitations and an alternative approach. Brain 130, e75. 10.1093/brain/awm084 (2007). DOI: 10.1093/brain/awm084
Massimini, M. et al. Breakdown of cortical effective connectivity during sleep. Science 309, 2228–2232. 10.1126/science.1117256 (2005). DOI: 10.1126/science.1117256
Picchioni, D. et al. Decreased connectivity between the thalamus and the neocortex during human nonrapid eye movement sleep. Sleep 37, 387–397. 10.5665/sleep.3422 (2014). DOI: 10.5665/sleep.3422
Spoormaker, V. I., Gleiser, P. M. & Czisch, M. Frontoparietal connectivity and Hierarchical structure of the brain’s functional network during sleep. Front. Neurol. 3, 80. 10.3389/fneur.2012.00080 (2012). DOI: 10.3389/fneur.2012.00080
Spoormaker, V. I. et al. Development of a large-scale functional brain network during human non-rapid eye movement sleep. J. Neurosci. 30, 11379–11387. 10.1523/JNEUROSCI.2015-10.2010 (2010). DOI: 10.1523/JNEUROSCI.2015-10.2010
Tagliazucchi, E. et al. Large-scale brain functional modularity is reflected in slow electroencephalographic rhythms across the human non-rapid eye movement sleep cycle. Neuroimage 70, 327–339. 10.1016/j.neuroimage.2012.12.073 (2013). DOI: 10.1016/j.neuroimage.2012.12.073
Horovitz, S. G. et al. Low frequency BOLD fluctuations during resting wakefulness and light sleep: A simultaneous EEG-fMRI study. Hum. Brain Mapp. 29, 671–682. 10.1002/hbm.20428 (2008). DOI: 10.1002/hbm.20428
Larson-Prior, L. J. et al. Cortical network functional connectivity in the descent to sleep. Proc. Natl. Acad. Sci. U.S.A. 106, 4489–4494. 10.1073/pnas.0900924106 (2009). DOI: 10.1073/pnas.0900924106
Carrier, J. et al. Effects of caffeine on daytime recovery sleep: A double challenge to the sleep-wake cycle in aging. Sleep Med. 10, 1016–1024. 10.1016/j.sleep.2009.01.001 (2009). DOI: 10.1016/j.sleep.2009.01.001
Carrier, J. et al. Sleep slow wave changes during the middle years of life. Eur. J. Neurosci. 33, 758–766. 10.1111/j.1460-9568.2010.07543.x (2011). DOI: 10.1111/j.1460-9568.2010.07543.x
Gaudreau, H., Morettini, J., Lavoie, H. B. & Carrier, J. Effects of a 25-h sleep deprivation on daytime sleep in the middle-aged. Neurobiol. Aging 22, 461–468 (2001). DOI: 10.1016/S0197-4580(00)00251-7
Mander, B. A., Winer, J. R. & Walker, M. P. Sleep and human aging. Neuron 94, 19–36. 10.1016/j.neuron.2017.02.004 (2017). DOI: 10.1016/j.neuron.2017.02.004
Lafortune, M. et al. Sleep spindles and rapid eye movement sleep as predictors of next morning cognitive performance in healthy middle-aged and older participants. J. Sleep Res. 23, 159–167. 10.1111/jsr.12108 (2014). DOI: 10.1111/jsr.12108
Klerman, E. B. et al. Survival analysis indicates that age-related decline in sleep continuity occurs exclusively during NREM sleep. Neurobiol. Aging 34, 309–318. 10.1016/j.neurobiolaging.2012.05.018 (2013). DOI: 10.1016/j.neurobiolaging.2012.05.018
Carrier, J., Monk, T. H., Buysse, D. J. & Kupfer, D. J. Sleep and morningness-eveningness in the “middle” years of life (20–59 y). J. Sleep Res. 6, 230–237 (1997). DOI: 10.1111/j.1365-2869.1997.00230.x
Duffy, J. F., Zitting, K. M. & Chinoy, E. D. Aging and circadian rhythms. Sleep Med. Clin. 10, 423–434. 10.1016/j.jsmc.2015.08.002 (2015). DOI: 10.1016/j.jsmc.2015.08.002
Van Someren, E. J. Circadian and sleep disturbances in the elderly. Exp. Gerontol. 35, 1229–1237 (2000). DOI: 10.1016/S0531-5565(00)00191-1
Fogel, S. et al. NREM sleep oscillations and brain plasticity in aging. Front. Neurol. 3, 176. 10.3389/fneur.2012.00176 (2012). DOI: 10.3389/fneur.2012.00176
Mander, B. A. et al. beta-amyloid disrupts human NREM slow waves and related hippocampus-dependent memory consolidation. Nat. Neurosci. 18, 1051–1057. 10.1038/nn.4035 (2015). DOI: 10.1038/nn.4035
Pace-Schott, E. F. & Spencer, R. M. Sleep-dependent memory consolidation in healthy aging and mild cognitive impairment. Curr. Top. Behav. Neurosci. 25, 307–330. 10.1007/7854_2014_300 (2015). DOI: 10.1007/7854_2014_300
Bellec, P., Rosa-Neto, P., Lyttelton, O. C., Benali, H. & Evans, A. C. Multi-level bootstrap analysis of stable clusters in resting-state fMRI. Neuroimage 51, 1126–1139. 10.1016/j.neuroimage.2010.02.082 (2010). DOI: 10.1016/j.neuroimage.2010.02.082
Yeo, B. T. et al. The organization of the human cerebral cortex estimated by intrinsic functional connectivity. J. Neurophysiol. 106, 1125–1165. 10.1152/jn.00338.2011 (2011). DOI: 10.1152/jn.00338.2011
Davis, B., Tagliazucchi, E., Jovicich, J., Laufs, H. & Hasson, U. Progression to deep sleep is characterized by changes to BOLD dynamics in sensory cortices. Neuroimage 130, 293–305. 10.1016/j.neuroimage.2015.12.034 (2016). DOI: 10.1016/j.neuroimage.2015.12.034
Onoda, K. & Yamaguchi, S. Small-worldness and modularity of the resting-state functional brain network decrease with aging. Neurosci. Lett. 556, 104–108. 10.1016/j.neulet.2013.10.023 (2013). DOI: 10.1016/j.neulet.2013.10.023
Godwin, D., Barry, R. L. & Marois, R. Breakdown of the brain’s functional network modularity with awareness. Proc. Natl. Acad. Sci. U.S.A. 112, 3799–3804. 10.1073/pnas.1414466112 (2015). DOI: 10.1073/pnas.1414466112
Tononi, G. & Massimini, M. Why does consciousness fade in early sleep?. Ann. N. Y. Acad. Sci. 1129, 330–334. 10.1196/annals.1417.024 (2008). DOI: 10.1196/annals.1417.024
Betzel, R. F. et al. Changes in structural and functional connectivity among resting-state networks across the human lifespan. Neuroimage 102(Pt 2), 345–357. 10.1016/j.neuroimage.2014.07.067 (2014). DOI: 10.1016/j.neuroimage.2014.07.067
Song, J. et al. Age-related reorganizational changes in modularity and functional connectivity of human brain networks. Brain Connect. 4, 662–676. 10.1089/brain.2014.0286 (2014). DOI: 10.1089/brain.2014.0286
Boveroux, P. et al. Breakdown of within- and between-network resting state functional magnetic resonance imaging connectivity during propofol-induced loss of consciousness. Anesthesiology 113, 1038–1053. 10.1097/ALN.0b013e3181f697f5 (2010). DOI: 10.1097/ALN.0b013e3181f697f5
Guldenmund, P. et al. Propofol-induced frontal cortex disconnection: A study of resting-state networks, total brain connectivity, and mean BOLD signal oscillation frequencies. Brain Connect. 6, 225–237. 10.1089/brain.2015.0369 (2016). DOI: 10.1089/brain.2015.0369
Martin, N. et al. Topography of age-related changes in sleep spindles. Neurobiol. Aging 34, 468–476. 10.1016/j.neurobiolaging.2012.05.020 (2013). DOI: 10.1016/j.neurobiolaging.2012.05.020
Dube, J. et al. Cortical thinning explains changes in sleep slow waves during adulthood. J. Neurosci. 35, 7795–7807. 10.1523/JNEUROSCI.3956-14.2015 (2015). DOI: 10.1523/JNEUROSCI.3956-14.2015
Addis, D. R., Leclerc, C. M., Muscatell, K. A. & Kensinger, E. A. There are age-related changes in neural connectivity during the encoding of positive, but not negative, information. Cortex 46, 425–433. 10.1016/j.cortex.2009.04.011 (2010). DOI: 10.1016/j.cortex.2009.04.011
Grady, C. L. et al. A multivariate analysis of age-related differences in default mode and task-positive networks across multiple cognitive domains. Cereb. Cortex 20, 1432–1447. 10.1093/cercor/bhp207 (2010). DOI: 10.1093/cercor/bhp207
Marstaller, L., Williams, M., Rich, A., Savage, G. & Burianova, H. Aging and large-scale functional networks: White matter integrity, gray matter volume, and functional connectivity in the resting state. Neuroscience 290, 369–378. 10.1016/j.neuroscience.2015.01.049 (2015). DOI: 10.1016/j.neuroscience.2015.01.049
Sala-Llonch, R., Palacios, E. M., Junque, C., Bargallo, N. & Vendrell, P. Functional networks and structural connectivity of visuospatial and visuoperceptual working memory. Front. Hum. Neurosci. 9, 340. 10.3389/fnhum.2015.00340 (2015). DOI: 10.3389/fnhum.2015.00340
Turner, G. R. & Spreng, R. N. Executive functions and neurocognitive aging: Dissociable patterns of brain activity. Neurobiol. Aging 33(826), e821. 10.1016/j.neurobiolaging.2011.06.005 (2012). DOI: 10.1016/j.neurobiolaging.2011.06.005
Bouchard, M. et al. EEG connectivity across sleep cycles and age. Sleep 10.1093/sleep/zsz236 (2020). DOI: 10.1093/sleep/zsz236
Ujma, P. P. et al. Sleep EEG functional connectivity varies with age and sex, but not general intelligence. Neurobiol. Aging 78, 87–97. 10.1016/j.neurobiolaging.2019.02.007 (2019). DOI: 10.1016/j.neurobiolaging.2019.02.007
Lu, F. M. et al. Disrupted topology of frontostriatal circuits is linked to the severity of insomnia. Front. Neurosci. 11, 214. 10.3389/fnins.2017.00214 (2017). DOI: 10.3389/fnins.2017.00214
Li, X. et al. Increased interhemispheric resting-state functional connectivity in healthy participants with insomnia symptoms: A randomized clinical consort study. Medicine (Baltimore) 96, e7037. 10.1097/MD.0000000000007037 (2017). DOI: 10.1097/MD.0000000000007037
Zhou, S. et al. Dynamic functional connectivity states characterize NREM sleep and wakefulness. Hum. Brain Mapp. 40, 5256–5268. 10.1002/hbm.24770 (2019). DOI: 10.1002/hbm.24770
Nilsonne, G. et al. Intrinsic brain connectivity after partial sleep deprivation in young and older adults: Results from the Stockholm sleepy brain study. Sci. Rep. 7, 9422. 10.1038/s41598-017-09744-7 (2017). DOI: 10.1038/s41598-017-09744-7
Mander, B. A., Winer, J. R., Jagust, W. J. & Walker, M. P. Sleep: A novel mechanistic pathway, biomarker, and treatment target in the pathology of Alzheimer’s disease?. Trends Neurosci. 39, 552–566. 10.1016/j.tins.2016.05.002 (2016). DOI: 10.1016/j.tins.2016.05.002
Horne, J. A. & Ostberg, O. A self-assessment questionnaire to determine morningness-eveningness in human circadian rhythms. Int. J. Chronobiol. 4, 97–110 (1976).
Johns, M. W. A new method for measuring daytime sleepiness: The Epworth sleepiness scale. Sleep 14, 540–545 (1991). DOI: 10.1093/sleep/14.6.540
Buysse, D. J., Reynolds, C. F., Monk, T. H., Berman, S. R. & Kupfer, D. J. The Pittsburgh sleep quality index: A new instrument for psychiatric practice and research. Psychiatry Res. 28, 193–213 (1989). DOI: 10.1016/0165-1781(89)90047-4
Beck, A. T., Epstein, N., Brown, G. & Steer, R. A. An inventory for measuring clinical anxiety: Psychometric properties. J. Consult. Clin. Psychol. 56, 893–897 (1988). DOI: 10.1037/0022-006X.56.6.893
Steer, R. A., Ball, R., Ranieri, W. F. & Beck, A. T. Further evidence for the construct validity of the Beck depression Inventory-II with psychiatric outpatients. Psychol. Rep. 80, 443–446. 10.2466/pr0.1997.80.2.443 (1997). DOI: 10.2466/pr0.1997.80.2.443
Lafortune, M. et al. Reduced slow-wave rebound during daytime recovery sleep in middle-aged subjects. PLoS ONE 7, e43224. 10.1371/journal.pone.0043224 (2012). DOI: 10.1371/journal.pone.0043224
Munch, M. et al. The frontal predominance in human EEG delta activity after sleep loss decreases with age. Eur. J. Neurosci. 20, 1402–1410. 10.1111/j.1460-9568.2004.03580.x (2004). DOI: 10.1111/j.1460-9568.2004.03580.x
Allen, P. J., Josephs, O. & Turner, R. A method for removing imaging artifact from continuous EEG recorded during functional MRI. Neuroimage 12, 230–239. 10.1006/nimg.2000.0599 (2000). DOI: 10.1006/nimg.2000.0599
Leclercq, Y. et al. Rejection of pulse related artefact (PRA) from continuous electroencephalographic (EEG) time series recorded during functional magnetic resonance imaging (fMRI) using constraint independent component analysis (cICA). Neuroimage 44, 679–691. 10.1016/j.neuroimage.2008.10.017 (2009). DOI: 10.1016/j.neuroimage.2008.10.017
Brunner, D. P. et al. Muscle artifacts in the sleep EEG: Automated detection and effect on all-night EEG power spectra. J. Sleep Res. 5, 155–164 (1996). DOI: 10.1046/j.1365-2869.1996.00009.x
Silber, M. H. et al. The visual scoring of sleep in adults. J. Clin. Sleep Med. 3, 121–131 (2007). DOI: 10.5664/jcsm.26814
Dang-Vu, T. T. et al. Spontaneous neural activity during human slow wave sleep. Proc. Natl. Acad. Sci U.S.A. 105, 15160–15165. 10.1073/pnas.0801819105 (2008). DOI: 10.1073/pnas.0801819105
Bellec, P. et al. The pipeline system for Octave and Matlab (PSOM): A lightweight scripting framework and execution engine for scientific workflows. Front. Neuroinform. 6, 7. 10.3389/fninf.2012.00007 (2012). DOI: 10.3389/fninf.2012.00007
Collins, D. L., Neelin, P., Peters, T. M. & Evans, A. C. Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space. J. Comput. Assist. Tomogr. 18, 192–205 (1994). DOI: 10.1097/00004728-199403000-00005
Fonov, V. S., Evans, A. C., McKinstry, R. C., Almli, C. R. & Collins, D. L. Unbiased nonlinear average age-appropriate brain templates from birth to adulthood. Neuroimage 47, S39–S41. 10.1016/S1053-8119(09)70884-5 (2009). DOI: 10.1016/S1053-8119(09)70884-5
Ad-Dab’bagh, Y. The CIVET image-processing environment: A fully automated comprehensive pipeline for anatomical neuroimaging research. In Organization for Human Brain Mapping, Conference Paper (2006).
Benhajali, Y. et al. A standardized protocol for efficient and reliable quality control of brain registration in functional MRI studies. Front. Neuroinform. 14, 7. 10.3389/fninf.2020.00007 (2020). DOI: 10.3389/fninf.2020.00007
Mowinckel, A. M., Espeseth, T. & Westlye, L. T. Network-specific effects of age and in-scanner subject motion: A resting-state fMRI study of 238 healthy adults. Neuroimage 63, 1364–1373. 10.1016/j.neuroimage.2012.08.004 (2012). DOI: 10.1016/j.neuroimage.2012.08.004
Power, J. D., Barnes, K. A., Snyder, A. Z., Schlaggar, B. L. & Petersen, S. E. Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. Neuroimage 59, 2142–2154. 10.1016/j.neuroimage.2011.10.018 (2012). DOI: 10.1016/j.neuroimage.2011.10.018
Power, J. D., Schlaggar, B. L. & Petersen, S. E. Recent progress and outstanding issues in motion correction in resting state fMRI. Neuroimage 105, 536–551. 10.1016/j.neuroimage.2014.10.044 (2015). DOI: 10.1016/j.neuroimage.2014.10.044
Van Dijk, K. R., Sabuncu, M. R. & Buckner, R. L. The influence of head motion on intrinsic functional connectivity MRI. Neuroimage 59, 431–438. 10.1016/j.neuroimage.2011.07.044 (2012). DOI: 10.1016/j.neuroimage.2011.07.044
Giove, F., Gili, T., Iacovella, V., Macaluso, E. & Maraviglia, B. Images-based suppression of unwanted global signals in resting-state functional connectivity studies. Magn. Reson. Imaging 27, 1058–1064. 10.1016/j.mri.2009.06.004 (2009). DOI: 10.1016/j.mri.2009.06.004
Spoormaker, V. I., Czisch, M., Maquet, P. & Jancke, L. Large-scale functional brain networks in human non-rapid eye movement sleep: Insights from combined electroencephalographic/functional magnetic resonance imaging studies. Philos. Trans. A Math. Phys. Eng. Sci. 369, 3708–3729. 10.1098/rsta.2011.0078 (2011). DOI: 10.1098/rsta.2011.0078
Benjamini, Y., Drai, D., Elmer, G., Kafkafi, N. & Golani, I. Controlling the false discovery rate in behavior genetics research. Behav. Brain Res. 125, 279–284 (2001). DOI: 10.1016/S0166-4328(01)00297-2
Bellec, P. et al. Impact of the resolution of brain parcels on connectome-wide association studies in fMRI. Neuroimage 123, 212–228. 10.1016/j.neuroimage.2015.07.071 (2015). DOI: 10.1016/j.neuroimage.2015.07.071
