Transient brain activity dynamics discriminate levels of consciousness during anesthesia.
Journal
Communications biology
ISSN: 2399-3642
Titre abrégé: Commun Biol
Pays: England
ID NLM: 101719179
Informations de publication
Date de publication:
10 Jun 2024
10 Jun 2024
Historique:
received:
20
10
2023
accepted:
15
05
2024
medline:
11
6
2024
pubmed:
11
6
2024
entrez:
10
6
2024
Statut:
epublish
Résumé
The awake mammalian brain is functionally organized in terms of large-scale distributed networks that are constantly interacting. Loss of consciousness might disrupt this temporal organization leaving patients unresponsive. We hypothesize that characterizing brain activity in terms of transient events may provide a signature of consciousness. For this, we analyze temporal dynamics of spatiotemporally overlapping functional networks obtained from fMRI transient activity across different anesthetics and levels of anesthesia. We first show a striking homology in spatial organization of networks between monkeys and humans, indicating cross-species similarities in resting-state fMRI structure. We then track how network organization shifts under different anesthesia conditions in macaque monkeys. While the spatial aspect of the networks is preserved, their temporal dynamics are highly affected by anesthesia. Networks express for longer durations and co-activate in an anesthetic-specific configuration. Additionally, hierarchical brain organization is disrupted with a consciousness-level-signature role of the default mode network. In conclusion, large-scale brain network temporal dynamics capture differences in anesthetic-specific consciousness-level, paving the way towards a clinical translation of these cortical signature.
Identifiants
pubmed: 38858589
doi: 10.1038/s42003-024-06335-x
pii: 10.1038/s42003-024-06335-x
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
716Informations de copyright
© 2024. The Author(s).
Références
Barttfeld, P. et al. Signature of consciousness in the dynamics of resting-state brain activity. Proc. Natl Acad. Sci. USA 112, 887–892 (2015).
pubmed: 25561541
pmcid: 4311826
doi: 10.1073/pnas.1418031112
Uhrig, L. et al. Resting-state dynamics as a cortical signature of anesthesia in monkeys. Anesthesiology 129, 942–958 (2018).
pubmed: 30028727
doi: 10.1097/ALN.0000000000002336
Tarun, A. et al. NREM sleep stages specifically alter dynamical integration of large-scale brain networks. iScience 24, 101923 (2021).
pubmed: 33409474
doi: 10.1016/j.isci.2020.101923
Hahn, G. et al. Signature of consciousness in brain-wide synchronization patterns of monkey and human fMRI signals. Neuroimage 226, 117470 (2021).
pubmed: 33137478
doi: 10.1016/j.neuroimage.2020.117470
Nir, T. et al. Transient subcortical functional connectivity upon emergence from propofol sedation in human male volunteers: evidence for active emergence. Br. J. Anaesth. 123, 298–308 (2019).
pubmed: 31277837
doi: 10.1016/j.bja.2019.05.038
Del Pozo, S. M. et al. Unconsciousness reconfigures modular brain network dynamics. Chaos 31, 093117 (2021).
pubmed: 34598477
doi: 10.1063/5.0046047
Preti, M. G., Bolton, T. A. & Van De Ville, D. The dynamic functional connectome: state-of-the-art and perspectives. Neuroimage 160, 41–54 (2017).
pubmed: 28034766
doi: 10.1016/j.neuroimage.2016.12.061
Demertzi, A. et al. Human consciousness is supported by dynamic complex patterns of brain signal coordination. Sci. Adv. 5, eaat7603 (2019).
pubmed: 30775433
pmcid: 6365115
doi: 10.1126/sciadv.aat7603
Tasserie, J. et al. Deep brain stimulation of the thalamus restores signatures of consciousness in a nonhuman primate model. Sci. Adv. 8, eabl5547 (2022).
pubmed: 35302854
pmcid: 8932660
doi: 10.1126/sciadv.abl5547
Crone, J. S. et al. Impaired consciousness is linked to changes in effective connectivity of the posterior cingulate cortex within the default mode network. Neuroimage 110, 101–109 (2015).
pubmed: 25620493
doi: 10.1016/j.neuroimage.2015.01.037
Huang, Z. et al. The self and its resting state in consciousness: an investigation of the vegetative state. Hum. Brain Mapp. 35, 1997–2008 (2014).
pubmed: 23818102
doi: 10.1002/hbm.22308
Owen, A. M. et al. Detecting awareness in the vegetative state. Science 313, 1402 (2006).
pubmed: 16959998
doi: 10.1126/science.1130197
Sitt, J. D. et al. Large scale screening of neural signatures of consciousness in patients in a vegetative or minimally conscious state. Brain 137, 2258–2270 (2014).
pubmed: 24919971
pmcid: 4610185
doi: 10.1093/brain/awu141
Fultz, N. E. et al. Coupled electrophysiological, hemodynamic, and cerebrospinal fluid oscillations in human sleep. Science 366, 628–631 (2019).
pubmed: 31672896
pmcid: 7309589
doi: 10.1126/science.aax5440
Golkowski, D. et al. Simultaneous EEG-PET-fMRI measurements in disorders of consciousness: an exploratory study on diagnosis and prognosis. J. Neurol. 264, 1986–1995 (2017).
pubmed: 28819796
doi: 10.1007/s00415-017-8591-z
Warbrick, T. Simultaneous EEG-fMRI: what have we learned and what does the future hold? Sensors https://doi.org/10.3390/s22062262 (2022).
Burle, B. et al. Spatial and temporal resolutions of EEG: Is it really black and white? A scalp current density view. Int. J. Psychophysiol. 97, 210–220 (2015).
pubmed: 25979156
pmcid: 4548479
doi: 10.1016/j.ijpsycho.2015.05.004
Nunez, P. L. & Westdorp, A. F. The surface Laplacian, high resolution EEG and controversies. Brain Topogr. 6, 221–226 (1994).
pubmed: 8204409
doi: 10.1007/BF01187712
Hale, J. R. et al. Altered thalamocortical and intra-thalamic functional connectivity during light sleep compared with wake. Neuroimage 125, 657–667 (2016).
pubmed: 26499809
doi: 10.1016/j.neuroimage.2015.10.041
Szaflarski, J. P. et al. Cortical and subcortical contributions to absence seizure onset examined with EEG/fMRI. Epilepsy Behav. 18, 404–413 (2010).
pubmed: 20580319
pmcid: 2922486
doi: 10.1016/j.yebeh.2010.05.009
Michel, C. M. et al. EEG source imaging. Clin. Neurophysiol. 115, 2195–2222 (2004).
pubmed: 15351361
doi: 10.1016/j.clinph.2004.06.001
Enzo, T. et al. Breakdown of long-range temporal dependence in default mode and attention networks during deep sleep. Proc. Natl Acad. Sci. USA 110, 15419–15424 (2013).
doi: 10.1073/pnas.1312848110
Chow, H. M. et al. Rhythmic alternating patterns of brain activity distinguish rapid eye movement sleep from other states of consciousness. Proc. Natl Acad. Sci. USA 110, 10300–10305 (2013).
pubmed: 23733938
pmcid: 3690889
doi: 10.1073/pnas.1217691110
Tagliazucchi, E. et al. Large-scale signatures of unconsciousness are consistent with a departure from critical dynamics. J. R. Soc. Interface 13, 20151027 (2016).
pubmed: 26819336
pmcid: 4759808
doi: 10.1098/rsif.2015.1027
Amico, E. et al. Posterior cingulate cortex-related co-activation patterns: a resting state FMRI study in propofol-induced loss of consciousness. PLoS ONE 9, e100012 (2014).
pubmed: 24979748
pmcid: 4076184
doi: 10.1371/journal.pone.0100012
Liu, X. et al. Variation of the default mode network with altered alertness levels induced by propofol. Neuropsychiatr. Dis. Treat. 11, 2573–2581 (2015).
pubmed: 26504389
pmcid: 4605232
Stamatakis, E. A., Adapa, R. M., Absalom, A. R. & Menon, D. K. Changes in resting neural connectivity during propofol sedation. PLoS ONE 5, e14224 (2010).
pubmed: 21151992
pmcid: 2996305
doi: 10.1371/journal.pone.0014224
Hudetz, A. G., Liu, X. & Pillay, S. Dynamic repertoire of intrinsic brain states is reduced in propofol-induced unconsciousness. Brain Connect. 5, 10–22 (2015).
pubmed: 24702200
pmcid: 4313411
doi: 10.1089/brain.2014.0230
Paasonen, J., Stenroos, P., Salo, R. A., Kiviniemi, V. & Gröhn, O. Functional connectivity under six anesthesia protocols and the awake condition in rat brain. Neuroimage 172, 9–20 (2018).
pubmed: 29414498
doi: 10.1016/j.neuroimage.2018.01.014
Zhang, H. et al. Posterior cingulate cross-hemispheric functional connectivity predicts the level of consciousness in traumatic brain injury. Sci. Rep. 7, 387 (2017).
pubmed: 28341824
pmcid: 5428308
doi: 10.1038/s41598-017-00392-5
Greicius, M. D. et al. Persistent default-mode network connectivity during light sedation. Hum. Brain Mapp. 29, 839–847 (2008).
pubmed: 18219620
pmcid: 2580760
doi: 10.1002/hbm.20537
Franks, N. P. General anaesthesia: from molecular targets to neuronal pathways of sleep and arousal. Nat. Rev. Neurosci. 9, 370–386 (2008).
pubmed: 18425091
doi: 10.1038/nrn2372
Karahanoglu, F. I., Caballero-Gaudes, C., Lazeyras, F. & Van de Ville, D. Total activation: fMRI deconvolution through spatio-temporal regularization. Neuroimage 73, 121–134 (2013).
pubmed: 23384519
doi: 10.1016/j.neuroimage.2013.01.067
Karahanoğlu, F. I. & Van De Ville, D. Dynamics of large-scale fMRI networks: deconstruct brain activity to build better models of brain function. Curr. Opin. Biomed. Eng. 3, 28–36 (2017).
doi: 10.1016/j.cobme.2017.09.008
Karahanoglu, F. I. & Van De Ville, D. Transient brain activity disentangles fMRI resting-state dynamics in terms of spatially and temporally overlapping networks. Nat. Commun. 6, 7751 (2015).
pubmed: 26178017
doi: 10.1038/ncomms8751
Milham, M. P. et al. An open resource for non-human primate imaging. Neuron 100, 61–74.e62 (2018).
pubmed: 30269990
pmcid: 6231397
doi: 10.1016/j.neuron.2018.08.039
Yacoub, E. et al. Ultra-high field (10.5 T) resting state fMRI in the macaque. Neuroimage 223, 117349 (2020).
pubmed: 32898683
doi: 10.1016/j.neuroimage.2020.117349
Margulies, D. S. et al. Precuneus shares intrinsic functional architecture in humans and monkeys. Proc. Natl Acad. Sci. USA 106, 20069–20074 (2009).
pubmed: 19903877
pmcid: 2775700
doi: 10.1073/pnas.0905314106
Pirondini, E. et al. Post-stroke reorganization of transient brain activity characterizes deficits and recovery of cognitive functions. Neuroimage 255, 119201 (2022).
pubmed: 35405342
doi: 10.1016/j.neuroimage.2022.119201
Zoller, D. et al. Large-scale brain network dynamics provide a measure of psychosis and anxiety in 22q11.2 deletion syndrome. Biol. Psychiatry Cogn. Neurosci. Neuroimaging 4, 881–892 (2019).
pubmed: 31171499
Zoller, D. et al. Structural control energy of resting-state functional brain states reveals less cost-effective brain dynamics in psychosis vulnerability. Hum. Brain Mapp. 42, 2181–2200 (2021).
pubmed: 33566395
pmcid: 8046160
doi: 10.1002/hbm.25358
Zoller, D. M. et al. Robust recovery of temporal overlap between network activity using transient-informed spatio-temporal regression. IEEE Trans. Med Imaging 38, 291–302 (2019).
pubmed: 30188815
doi: 10.1109/TMI.2018.2863944
Piguet, C., Karahanoglu, F. I., Saccaro, L. F., Van De Ville, D. & Vuilleumier, P. Mood disorders disrupt the functional dynamics, not spatial organization of brain resting state networks. Neuroimage Clin. 32, 102833 (2021).
pubmed: 34619652
pmcid: 8498469
doi: 10.1016/j.nicl.2021.102833
Pagani, M., Gutierrez-Barragan, D., de Guzman, A. E., Xu, T. & Gozzi, A. Mapping and comparing fMRI connectivity networks across species. Commun. Biol. 6, 1238 (2023).
pubmed: 38062107
pmcid: 10703935
doi: 10.1038/s42003-023-05629-w
Mantini, D. et al. Default mode of brain function in monkeys. J. Neurosci. 31, 12954–12962 (2011).
pubmed: 21900574
pmcid: 3686636
doi: 10.1523/JNEUROSCI.2318-11.2011
Hutchison, R. M. & Everling, S. Monkey in the middle: why non-human primates are needed to bridge the gap in resting-state investigations. Front. Neuroanat. 6, 29 (2012).
pubmed: 22855672
pmcid: 3405297
doi: 10.3389/fnana.2012.00029
Bukhari, Q., Schroeter, A., Cole, D. M. & Rudin, M. Resting state fMRI in mice reveals anesthesia specific signatures of brain functional networks and their interactions. Front. Neural Circuits https://doi.org/10.3389/fncir.2017.00005 (2017).
Nallasamy, N. & Tsao, D. Y. Functional connectivity in the brain: effects of anesthesia. Neuroscientist 17, 94–106 (2011).
pubmed: 21343409
doi: 10.1177/1073858410374126
Catherine, J. S. & Jeremy, D. S. Evidence for topographic organization in the cerebellum of motor control versus cognitive and affective processing. Cortex 46, 831–844 (2010).
doi: 10.1016/j.cortex.2009.11.008
Dang-Vu, T. T. et al. Spontaneous neural activity during human slow wave sleep. Proc. Natl Acad. Sci. USA 105, 15160–15165 (2008).
pubmed: 18815373
pmcid: 2567508
doi: 10.1073/pnas.0801819105
Canto, C. B., Onuki, Y., Bruinsma, B., van der Werf, Y. D. & De Zeeuw, C. I. The sleeping cerebellum. Trends Neurosci. 40, 309–323 (2017).
pubmed: 28431742
doi: 10.1016/j.tins.2017.03.001
Nofzinger, E. A. et al. Regional cerebral metabolic correlates of WASO during NREM sleep in insomnia. J. Clin. Sleep Med. 2, 316–322 (2006).
pubmed: 17561544
doi: 10.5664/jcsm.26592
Cirelli, C. & Tononi, G. Is sleep essential? PLoS Biol. 6, e216 (2008).
pubmed: 18752355
pmcid: 2525690
doi: 10.1371/journal.pbio.0060216
Spoormaker, V. I. et al. The neural correlates and temporal sequence of the relationship between shock exposure, disturbed sleep and impaired consolidation of fear extinction. J. Psychiatr. Res. 44, 1121–1128 (2010).
pubmed: 20471033
doi: 10.1016/j.jpsychires.2010.04.017
Horovitz, S. G. et al. Decoupling of the brain’s default mode network during deep sleep. Proc. Natl Acad. Sci. USA 106, 11376–11381 (2009).
pubmed: 19549821
pmcid: 2708777
doi: 10.1073/pnas.0901435106
Sämann, P. G. et al. Development of the brain’s default mode network from wakefulness to slow wave sleep. Cereb. Cortex 21, 2082–2093 (2011).
pubmed: 21330468
doi: 10.1093/cercor/bhq295
Boly, M. et al. Connectivity changes underlying spectral EEG changes during propofol-induced loss of consciousness. J. Neurosci. 32, 7082–7090 (2012).
pubmed: 22593076
pmcid: 3366913
doi: 10.1523/JNEUROSCI.3769-11.2012
Velly, L. J. et al. Differential dynamic of action on cortical and subcortical structures of anesthetic agents during induction of anesthesia. Anesthesiology 107, 202–212 (2007).
pubmed: 17667563
doi: 10.1097/01.anes.0000270734.99298.b4
Müller, E. J. et al. The non-specific matrix thalamus facilitates the cortical information processing modes relevant for conscious awareness. Cell Rep. 42, 112844 (2023).
pubmed: 37498741
doi: 10.1016/j.celrep.2023.112844
Redinbaugh, M. J. et al. Thalamus modulates consciousness via layer-specific control of cortex. Neuron 106, 66–75.e12 (2020).
pubmed: 32053769
pmcid: 7243351
doi: 10.1016/j.neuron.2020.01.005
Edlow, B. L. et al. Sustaining wakefulness: brainstem connectivity in human consciousness. bioRxiv https://doi.org/10.1101/2023.07.13.548265 (2023).
Boly, M. et al. Are the neural correlates of consciousness in the front or in the back of the cerebral cortex? Clinical and neuroimaging evidence. J. Neurosci. 37, 9603–9613 (2017).
pubmed: 28978697
pmcid: 5628406
doi: 10.1523/JNEUROSCI.3218-16.2017
Fabio, F. et al. Breakdown in cortical effective connectivity during midazolam-induced loss of consciousness. Proc. Natl Acad. Sci. USA 107, 2681–2686 (2010).
doi: 10.1073/pnas.0913008107
D’Angelo, E. & Casali, S. Seeking a unified framework for cerebellar function and dysfunction: from circuit operations to cognition. Front. Neural Circuits https://doi.org/10.3389/fncir.2012.00116 (2013).
Xiaolin, L. et al. Propofol attenuates low-frequency fluctuations of resting-state fMRI BOLD signal in the anterior frontal cortex upon loss of consciousness. NeuroImage 147, 295–301 (2017).
doi: 10.1016/j.neuroimage.2016.12.043
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 (2010).
pubmed: 20885292
doi: 10.1097/ALN.0b013e3181f697f5
Schrouff, J. et al. Brain functional integration decreases during propofol-induced loss of consciousness. Neuroimage 57, 198–205 (2011).
pubmed: 21524704
doi: 10.1016/j.neuroimage.2011.04.020
Huang, Z. et al. Altered temporal variance and neural synchronization of spontaneous brain activity in anesthesia. Hum. Brain Mapp. 35, 5368–5378 (2014).
pubmed: 24867379
pmcid: 6869449
doi: 10.1002/hbm.22556
Larson-Prior, L. J. et al. Cortical network functional connectivity in the descent to sleep. Proc. Natl Acad. Sci. USA 106, 4489–4494 (2009).
pubmed: 19255447
pmcid: 2657465
doi: 10.1073/pnas.0900924106
Schüttler, J. et al. Pharmacodynamic modeling of the EEG effects of ketamine and its enantiomers in man. J. Pharmacokinet. Biopharm. 15, 241–253 (1987).
pubmed: 3668802
doi: 10.1007/BF01066320
Murphy, M. et al. Propofol anesthesia and sleep: a high-density EEG study. Sleep 34, 283–291a (2011).
pubmed: 21358845
pmcid: 3041704
doi: 10.1093/sleep/34.3.283
Gugino, L. D. et al. Quantitative EEG changes associated with loss and return of consciousness in healthy adult volunteers anaesthetized with propofol or sevoflurane. Br. J. Anaesth. 87, 421–428 (2001).
pubmed: 11517126
doi: 10.1093/bja/87.3.421
Annabelle, M. B. et al. Large-scale brain networks in the awake, truly resting marmoset monkey. J. Neurosci. 33, 16796 (2013).
doi: 10.1523/JNEUROSCI.3146-13.2013
Vincent, J. L. et al. Intrinsic functional architecture in the anaesthetized monkey brain. Nature 447, 83–86 (2007).
pubmed: 17476267
doi: 10.1038/nature05758
Upadhyay, J. et al. Default-mode-like network activation in awake rodents. PLoS ONE 6, e27839 (2011).
pubmed: 22125628
pmcid: 3220684
doi: 10.1371/journal.pone.0027839
Lu, H. et al. Rat brains also have a default mode network. Proc. Natl Acad. Sci. USA 109, 3979–3984 (2012).
pubmed: 22355129
pmcid: 3309754
doi: 10.1073/pnas.1200506109
Francesco, S., Adam, J. S., Alberto, G., Angelo, B. & Alessandro, G. Distributed BOLD and CBV-weighted resting-state networks in the mouse brain. NeuroImage 87, 403–415 (2014).
doi: 10.1016/j.neuroimage.2013.09.050
Uhrig, L., Janssen, D., Dehaene, S. & Jarraya, B. Cerebral responses to local and global auditory novelty under general anesthesia. Neuroimage 141, 326–340 (2016).
pubmed: 27502046
doi: 10.1016/j.neuroimage.2016.08.004
Absalom, A. & Kenny, G. Paedfusor’ pharmacokinetic data set. Br. J. Anaesth. 95, 110 (2005).
pubmed: 15941735
doi: 10.1093/bja/aei567
Schroeder, K. E. et al. Disruption of corticocortical information transfer during ketamine anesthesia in the primate brain. Neuroimage 134, 459–465 (2016).
pubmed: 27095309
doi: 10.1016/j.neuroimage.2016.04.039
Logothetis, N. K., Pauls, J., Augath, M., Trinath, T. & Oeltermann, A. Neurophysiological investigation of the basis of the fMRI signal. Nature 412, 150–157 (2001).
pubmed: 11449264
doi: 10.1038/35084005
Pinault, D. N-methyl d-aspartate receptor antagonists ketamine and MK-801 induce wake-related aberrant gamma oscillations in the rat neocortex. Biol. Psychiatry 63, 730–735 (2008).
pubmed: 18022604
doi: 10.1016/j.biopsych.2007.10.006
Feshchenko, V. A., Veselis, R. A. & Reinsel, R. A. Propofol-induced alpha rhythm. Neuropsychobiology 50, 257–266 (2004).
pubmed: 15365226
doi: 10.1159/000079981
Purdon, P. L. et al. Electroencephalogram signatures of loss and recovery of consciousness from propofol. Proc. Natl Acad. Sci. USA 110, E1142–E1151 (2013).
pubmed: 23487781
pmcid: 3607036
doi: 10.1073/pnas.1221180110
Uhrig, L., Dehaene, S. & Jarraya, B. A hierarchy of responses to auditory regularities in the macaque brain. J. Neurosci. 34, 1127 (2014).
pubmed: 24453305
pmcid: 5635960
doi: 10.1523/JNEUROSCI.3165-13.2014
Jordy, T. et al. Pypreclin: an automatic pipeline for macaque functional MRI preprocessing. NeuroImage 207, 116353 (2020).
doi: 10.1016/j.neuroimage.2019.116353
Smith, S. M. et al. Advances in functional and structural MR image analysis and implementation as FSL. NeuroImage 23, S208–S219 (2004).
pubmed: 15501092
doi: 10.1016/j.neuroimage.2004.07.051
Farouj, Y., Karahanoglu, F. I. & Van De Ville, D. Bold Signal Deconvolution Under Uncertain HÆModynamics: A Semi-Blind Approach (IEEE, 2019).
Monti, S., Tamayo, P., Mesirov, J. & Golub, T. Consensus clustering: a resampling-based method for class discovery and visualization of gene expression microarray data. Mach. Learn. 52, 91–118 (2003).
doi: 10.1023/A:1023949509487
Efron, B. & Tibshirani, R. J. An introduction to the bootstrap. (Chapman & Hall, 1993).
doi: 10.1007/978-1-4899-4541-9
Benjamin, J. et al. A comprehensive macaque fMRI pipeline and hierarchical atlas. bioRxiv https://doi.org/10.1101/2020.08.05.237818 (2020).
Hartig, R. et al. The subcortical atlas of the rhesus macaque (SARM) for neuroimaging. Neuroimage 235, 117996 (2021).
pubmed: 33794360
doi: 10.1016/j.neuroimage.2021.117996
Reveley, C. et al. Three-dimensional digital template atlas of the macaque brain. Cereb. Cortex 27, 4463–4477 (2017).
pubmed: 27566980