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Signature of consciousness in the dynamics of resting-state brain activity
Open accessAbstract
Significance: What are the origins of resting-state functional connectivity patterns? One dominating view is that they index ongoing cognitive processes. However, this conclusion is in conflict with studies showing that long-range functional connectivity persists after loss of consciousness, possibly reflecting structural connectivity maps. In this work we respond to this question showing that in fact both sources have a clear and separable contribution to resting-state patterns. We show that under anesthesia, the dominating functional configurations have low information capacity and lack negative correlations. Importantly, they are rigid, tied to the anatomical map. Conversely, wakefulness is characterized by the dynamical exploration of a rich, flexible repertoire of functional configurations. These dynamical properties constitute a signature of consciousness.
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“simulations show that the GNW is subject to a continuous stream of stochastic spontaneous activity”
From Conscious Processing and the Global Neuronal Workspace Hypothesis (2020) · cites this paper as Barttfeld et al., 2015
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“Recent work in non-human primates demonstrates that the functional relationships between critical nodes in the GNW—such as prefrontal, posterior parietal, and cingulate cortices—are stereotypically altered during propofol, sevoflurane, and ketamine anesthesia (Barttfeld et al., 2015; Uhrig et al., 2018).”
From Conscious Processing and the Global Neuronal Workspace Hypothesis (2020) · cites this paper as Barttfeld et al., 2015
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“This dynamic signature of conscious processing was initially discovered in fMRI studies of awake versus anesthetized monkeys (Barttfeld et al., 2015) and later found to generalize to humans in vegetative or minimally conscious states (Demertzi et al., 2019).”
From Conscious Processing and the Global Neuronal Workspace Hypothesis (2020) · cites this paper as Barttfeld et al., 2015
In the citing paper
“As previously demonstrated in rats (Bettinardi et al. 2015) and monkeys (Barttfeld et al. 2015), modulating the depth of anesthesia correlates with changes in BOLD variability and reduces the overall connectivity strength.”
From Dysfunctional Autism Risk Genes Cause Circuit-Specific Connectivity Deficits With Distinct Developmental Trajectories (2018) · cites this paper as Barttfeld et al. 2015
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Cites
Collective dynamics of ‘small-world’ networks
Watts, D. J., & Strogatz, S. H. (1998) · Nature · doi:10.1038/30918 · Cited by 43,060
An Introduction to the Bootstrap
Efron, B., & Tibshirani, R. J. (1994) · doi:10.1201/9780429246593 · Cited by 40,500
Least squares quantization in PCM
Lloyd, S. (1982) · IEEE Transactions on Information Theory · doi:10.1109/tit.1982.1056489 · Cited by 15,836
A default mode of brain function
Raichle, M. E., MacLeod, A. M., Snyder, A. Z., Powers, W. J., Gusnard, D. A., & Shulman, G. L. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.98.2.676 · Cited by 12,190
Complex network measures of brain connectivity: Uses and interpretations
Rubinov, M., & Sporns, O. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.10.003 · Cited by 11,522
The Brain's Default Network: Anatomy, Function, and Relevance to Disease
Buckner, R. L., Andrews‐Hanna, J. R., & Schacter, D. L. (2008) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1440.011 · Cited by 9,761
The human brain is intrinsically organized into dynamic, anticorrelated functional networks
Fox, M. D., Snyder, A. Z., Vincent, J. L., Corbetta, M., Van Essen, D. C., & Raichle, M. E. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0504136102 · Cited by 8,553
Sparse inverse covariance estimation with the graphical lasso
Friedman, J., Hastie, T., & Tibshirani, R. (2008) · Biostatistics · doi:10.1093/biostatistics/kxm045 · Cited by 6,355
Tracking whole-brain connectivity dynamics in the resting state
Allen, E. A., Damaraju, E., Plis, S. M., Erhardt, E. B., Eichele, T., & Calhoun, V. D. (2014) · Cerebral Cortex · doi:10.1093/cercor/bhs352 · Cited by 2,992
Dynamic functional connectivity: Promise, issues, and interpretations
Hutchison, R. M., Womelsdorf, T., Allen, E. A., Bandettini, P. A., Calhoun, V. D., Corbetta, M., Della Penna, S., Duyn, J. H., Glover, G. H., Gonzalez-Castillo, J., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.079 · Cited by 2,962
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Fu, Z., Han, S., Tan, A., Tu, Y., & Zhang, Z. (2015) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2015.7318654 · Cited by 3
Brain-State Transitions, Responsibility, and Personal Identity
Rainey, S., Dague, K. O., & Crisp, R. (2022) · Cambridge Quarterly of Healthcare Ethics · doi:10.1017/s096318012100092x · Cited by 2
Revisiting the standard for modeling functional brain network activity: Application to consciousness
Grigis, A., Gomez, C., Frouin, V., Duchesnay, É., Uhrig, L., & Jarraya, B. (2024) · PLoS ONE · doi:10.1371/journal.pone.0314598 · Cited by 3
Self-citationChen, D., Yao, L., Liu, M., Shen, Z., Hu, Y., Song, Z., Wang, Q., & Zhang, L. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72120-5_57 · Cited by 3
An Integration of Deep Learning and Neuroscience for Machine Consciousness
Mallakin, A. (2019) · Global Journal of Computer Science and Technology · doi:10.34257/gjcstdvol19is1pg21 · Cited by 3
Psychologie cognitive expérimentale
Dehaene, S. (2016) · L’annuaire du Collège de France · doi:10.4000/annuaire-cdf.12564 · Cited by 3
Self-citationBrain activity on a hyperspherePreprint
Tozzi, A., & Peters, J. F. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1512.00036 · Cited by 3
Slow cortico-cortical connectivity (2-5Hz) is a new robust signature of conscious statesPreprint
Bourdillon, P., Hermann, B., Guénot, M., Bastuji, H., Isnard, J., King, J.-R., Sitt, J. D., & Naccache, L. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/692970 · Cited by 3
Self-citationLuppi, A. I., Mediano, P. A. M., Rosas, F. E., Harrison, D. J., Carhart-Harris, R. L., Bor, D., & Stamatakis, E. A. (2021) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/g9p3r · Cited by 5
Dynamic Cortical Connectivity During Propofol Sedation in Glioma Patients
Yang, W., Jian, M., Wang, X., Zhou, Y., Liang, Y., Chen, Y., Li, Y., Li, K., Ma, B., Liu, H., et al. (2024) · Journal of Neurosurgical Anesthesiology · doi:10.1097/ana.0000000000000964 · Cited by 2
From Speech Semantics to Brain Activity—Timescales Are Key in Their Information Transfer
Kumar, S., Klar, P., Çatal, Y., Chang, H., Friedemann Pulvermüller, A., & Northoff, G. (2025) · Human Brain Mapping · doi:10.1002/hbm.70379 · Cited by 1
Brain dynamic organization at the acute stage of severe brain injury
Bella, G. A. D., Sarton, B., Mattia, G. M., Péran, P., Lamberti, W., Barttfeld, P., & Silva, S. (2025) · NeuroImage · doi:10.1016/j.neuroimage.2025.121657 · Cited by 2
Self-citationQian, X., Yue, W. L., Ng, K. K., Leong, R. L. F., Ji, F., Venketasubramanian, N., Hilal, S., Chen, C., Chee, M. W. L., Bassett, D. S., et al. (2026) · PLoS Biology · doi:10.1371/journal.pbio.3003738 · Cited by 2
Comprehensive profiling of brain dynamics during anesthesia across phylogeny
Luppi, A. I., Uhrig, L., Tasserie, J., Shafiei, G., Légaré, A., Muta, K., Hata, J., Okano, H., Golkowski, D., Ranft, A., et al. (2026) · Nature Neuroscience · doi:10.1038/s41593-026-02460-4 · Cited by 6
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Kim, K. M., Lee, K.-H., & Park, J.-H. (2021) · Medicina · doi:10.3390/medicina57101034 · Cited by 2
Wang, H., Zhang, Y., Cheng, H., Yan, F., Song, D., Wang, Q., Cai, S., Wang, Y., & Huang, L. (2022) · Cognitive Neurodynamics · doi:10.1007/s11571-021-09775-x · Cited by 2
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Lake, E. M. R. (2022) · Current Biology · doi:10.1016/j.cub.2021.11.033 · Cited by 2
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Harauzov, A. K., Иванова, Л. Е., Vasil’ev, P. P., & Подвигина, Д. Н. (2022) · Journal of Evolutionary Biochemistry and Physiology · doi:10.1134/s0022093022040068 · Cited by 2
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Hartig, R., Karimi, A., & Evrard, H. (2023) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.818800 · Cited by 3
Zheng, J., Wang, C., Zhou, X., Tang, Y. R., Tang, L., Tan, Y., Zhang, J., Yu, H., Zhang, J., & Liu, D. (2025) · Brain Research Bulletin · doi:10.1016/j.brainresbull.2025.111210 · Cited by 2
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Fernandes, H. M., Deco, G., & Kringelbach, M. L. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-821861-7.00011-7 · Cited by 2
Yoo, J. H., Ok, S. Y., Kim, S. H., Chung, J. W., Park, S. Y., Kim, M. G., Cho, H. B., Song, S. H., Choi, S. J., & Oh, H. C. (2022) · Medicine · doi:10.1097/md.0000000000031191 · Cited by 2
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Gandhi, S. R., Mayner, W. G. P., Marshall, W., Billeh, Y. N., Bennett, C., Gale, S. D., Mochizuki, C., Siegle, J. H., Olsen, S. R., Tononi, G., et al. (2023) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2023.1040629 · Cited by 4
The promoting effect of vagus nerve stimulation on Lempel-Ziv complexity index of consciousness
Salemi-Mokri-Boukani, P., Karimian-Sani-Varjovi, H., & Safari, M.-S. (2021) · Physiology & Behavior · doi:10.1016/j.physbeh.2021.113553 · Cited by 2
Fukushima, M., Betzel, R. F., He, Y., Zuo, X., & Sporns, O. (2015) · arXiv (Cornell University) · Cited by 2
Unconsciousness reconfigures modular brain network dynamics
Tagliazucchi, E. (2021) · Figshare · doi:10.5281/zenodo.4483379 · Cited by 2
Functional connectivity-based attractor dynamics of the human brain in rest, task, and disease
Englert, R., Kincses, B., Kotikalapudi, R., Gallitto, G., Li, J., Hoffschlag, K., Woo, C., Wager, T. D., Timmann, D., Bingel, U., et al. (2024) · eLife · doi:10.1101/2023.11.03.565516 · Cited by 4
Maldegem, M. V., Vohryzek, J., Atasoy, S., Alnagger, N., Cardone, P., Bonhomme, V. L., Vanhaudenhuyse, A., Athena Demertzi, A., Jaquet, O., Bahri, M. A., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.06.20.599885 · Cited by 2
Hoffner, G., Castro, P., Uhrig, L., Signorelli, C. M., Dupont, M., Tasserie, J., Alain Destexhe, A., Cofré, R., Sitt, J. D., & Jarraya, B. (2024) · eLife · doi:10.7554/elife.101688 · Cited by 2
Self-citationZiaeemehr, A., Woodman, M., Domide, L., Petkoski, S., Jirsa, V., & Hashemi, M. (2025) · eLife · doi:10.7554/elife.106194.1 · Cited by 2
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Mandino, F., Kang, T., Shen, X., Horien, C. L., Papademetris, X., Strittmatter, S. M., & Lake, E. M. R. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.10.27.684863 · Cited by 2
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Sanchez-Vives, M. V., Manasanch, A., Pigorini, A., Arena, A., Camassa, A., Juel, B. E., Porta, L. D., Capone, C., Luca, C. D., Bonis, G. D., et al. (2025) · eLife · doi:10.7554/elife.108613 · Cited by 4
Correspondence of large-scale functional brain network decline across aging mice and humans
Winter-Nelson, E., Bergmann, E., Chan, M. Y., Vill, G., Han, L., Zhang, Z., Kavushansky, A., Dolgopyat, I., Asleh, J., Whitesell, J. D., et al. (2026) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2527522123 · Cited by 3
Measuring functional connectivity in frequency‐domain helps to better characterize brain function
Peng, L., Su, J., Hu, D., Yu, Y., Wei, H., & Li, M. (2024) · Human Brain Mapping · doi:10.1002/hbm.26726 · Cited by 1
Rest assured: Dynamic functional connectivity and the baseline state of the human brain
Tagliazucchi, E. (2024) · Imaging Neuroscience · doi:10.1162/imag_a_00365 · Cited by 1
Time Persistence of the FMRI Resting-State Functional Brain Networks
Guo, S., Levy, O., Dvir, H., Kang, R., Li, D., Havlin, S., & Axelrod, V. (2025) · Journal of Neuroscience · doi:10.1523/jneurosci.1570-24.2025 · Cited by 1
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Takagi, K. (2025) · Scientific Reports · doi:10.1038/s41598-025-96120-5 · Cited by 1
Haudry, S., Dautricourt, S., Gonneaud, J., Landeau, B., Calhoun, V. D., de Florès, R., Poisnel, G., Bougacha, S., Kuhn, E., Touron, E., et al. (2025) · Imaging Neuroscience · doi:10.1162/imag.a.33 · Cited by 1
Moon, H. S., Vo, T. T., Im, G. H., Hong, S., & Kim, S. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2505294122 · Cited by 1
Hoffner, G., Castro, P., Uhrig, L., Signorelli, C. M., Dupont, M., Tasserie, J., Alain Destexhe, A., Cofré, R., Sitt, J. D., & Jarraya, B. (2025) · eLife · doi:10.7554/elife.101688.3 · Cited by 1
Self-citationDiebolt, S., Pereira, F. C., Mariani, J.-C., Kliewer, A., Farinha‐Ferreira, M., Bertolo, A., Osmanski, B.-F., Lenkei, Z., & Deffieux, T. (2026) · Imaging Neuroscience · doi:10.1162/imag.a.1191 · Cited by 3
Resting-state fMRI dynamic functional network in young children with Tourette syndrome
Wang, H., Liu, Y., Zhang, C., Lian, J., Yang, L., & Peng, Y. (2026) · Frontiers in Neurology · doi:10.3389/fneur.2026.1758013 · Cited by 1
Hu, Y., Shi, Y., Hu, M., Jiang, L., Xing, W., Zhang, Y., & Zhang, G. (2026) · Journal of Affective Disorders · doi:10.1016/j.jad.2026.122000 · Cited by 1
Manickam, S., Giacometti, C., Dureux, A., Autran-Clavagnier, D., Wilson, C. R. E., Procyk, E., Dirheimer, M., Hadj‐Bouziane, F., & Amiez, C. (2026) · Cerebral Cortex · doi:10.1093/cercor/bhag076 · Cited by 1
Traumatismo craneoencefálico del niño
ORLIAGUET, G. A., & Uhrig, L. (2016) · EMC - Anestesia-Reanimación · doi:10.1016/s1280-4703(16)80724-0 · Cited by 1
Self-citation4. The Measurement of Consciousness
Gamez, D. (2018) · Open Book Publishers · doi:10.11647/obp.0107.04 · Cited by 1
Markovics, J. A. (2021) · Artificial intelligence · doi:10.5772/intechopen.98343 · Cited by 1
Divergences Between Resting State Networks and Meta-Analytic Maps Of Task-Evoked Brain Activity
Palmucci, M., & Tagliazucchi, E. (2022) · The Open Neuroimaging Journal · doi:10.2174/18744400-v15-e2206270 · Cited by 1
Resting state fMRI connectivity mapping across species: Challenges and opportunities
Pagani, M., Gutierrez‐Barragan, D., de Guzman, A. E., & Gozzi, A. (2023) · Elsevier eBooks · doi:10.1016/b978-0-323-91688-2.00009-6 · Cited by 1
Huang, Q., Yang, Y., Qi, N., Guan, Y., Zhao, J., Hua, F., Ren, S., & Xie, F. (2024) · Brain Connectivity · doi:10.1089/brain.2023.0070 · Cited by 2
Chen, L., Tan, S., Li, C., Lin, Z., Hu, X., Gu, T., Liu, J., Guo, X., Qu, Z., Gao, X., et al. (2024) · Brain Connectivity · doi:10.1089/brain.2023.0075 · Cited by 1
Armonaité, K., Conti, L., Laura, L., Primavera, M., & Tecchio, F. (2025) · Fractal and Fractional · doi:10.3390/fractalfract9050278 · Cited by 1
7. Information Theories of Consciousness
Gamez, D. (2018) · Open Book Publishers · doi:10.11647/obp.0107.07 · Cited by 1
Rabinovich, M. I., Varona, P., & de Madrid, U. A. (2017) · Izvestiya VUZ Applied Nonlinear Dynamics · doi:10.18500/0869-6632-2017-25-3-5-51 · Cited by 1
Designing a Communication Field with a Transformation Method
Lu, X., Ouyang, L., Sun, L., Hu, J., & Jia, L. (2018) · Journal of Robotics and Mechatronics · doi:10.20965/jrm.2018.p0943 · Cited by 1
Zhou, W., Cai, A., Nie, B., Zhang, W., Yang, T., Zheng, N., Manyande, A., Wang, X., Xu, F., Tian, X., et al. (2020) · PubMed Central · Cited by 1
Mixed Modeling Frameworks for Analyzing Whole-Brain Network Data
Simpson, S. L. (2021) · Methods in molecular biology · doi:10.1007/978-1-0716-1803-5_30 · Cited by 1
Fukushima, M., Betzel, R. F., He, Y., de Reus, M. A., van den Heuvel, M. P., Zuo, X., & Sporns, O. (2015) · arXiv (Cornell University) · Cited by 1
Teng, J., Ong, J. L., Patanaik, A., Tandi, J., Zhou, J. H., Chee, M. W. L., & Lim, J. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/509745 · Cited by 1
Dynamic Connectivity without Sliding WindowsPreprint
Huang, S.-G., Chung, M. K., Carroll, I. C., & Goldsmith, H. H. (2019) · arXiv (Cornell University) · Cited by 1
Bachmann, T. (2020) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2020.00195 · Cited by 1
Toscano, F. S., Galadí, J. A., Escrichs, A., Perl, Y. S., López‐González, A., Sitt, J. D., Annen, J., Gosseries, O., Thibaut, A., Panda, R., et al. (2021) · Research Square · doi:10.21203/rs.3.rs-1093655/v2 · Cited by 1
Self-citationReproducible patterns of neural activity without attractors in cortical networksPreprint
Guarino, D., Filipchuk, A., & Alain Destexhe, A. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.05.24.493230 · Cited by 1
Hierarchical Fluctuation Shapes a Dynamic Flow Linked to States of ConsciousnessPreprint
Li, A., Liu, H., Lei, X., He, Y., Wu, Q., Yan, Y., Zhou, X., Tian, X., Peng, Y., Yan, H., et al. (2022) · Research Square · doi:10.21203/rs.3.rs-1750692/v1 · Cited by 1
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Krause, B. M., Campbell, D. I., Kovach, C. K., Mueller, R. N., Kawasaki, H., Nourski, K. V., & Banks, M. I. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.11.15.516653 · Cited by 1
Song, I., & Lee, T. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.01.26.525765 · Cited by 2
Huang, Q., Yang, Y., Qi, N., Guan, Y., Zhao, J., Hua, F., Ren, S., & Xie, F. (2023) · doi:10.32388/duos00 · Cited by 1
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Luppi, A. I., Mediano, P. A. M., Rosas, F. E., Allanson, J. E., Pickard, J. D., Carhart-Harris, R. L., Williams, G. B., Craig, M. M., Finoia, P., Owen, A. M., et al. (2024) · eLife · doi:10.7554/elife.88173.2 · Cited by 1
Hoffner, G., Castro, P., Uhrig, L., Signorelli, C. M., Dupont, M., Tasserie, J., Alain Destexhe, A., Cofré, R., Sitt, J. D., & Jarraya, B. (2024) · eLife · doi:10.7554/elife.101688.1 · Cited by 1
Self-citationLuppi, A. I., Milisav, F., Suárez, L. E., Shafiei, G., Vohryzek, J., Perl, Y. S., Ali, H., Rosas, F. E., Mediano, P. A. M., Mišić, B., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.04.05.647237 · Cited by 2
Ziaeemehr, A., Woodman, M., Domide, L., Petkoski, S., Jirsa, V., & Hashemi, M. (2025) · eLife · doi:10.7554/elife.106194.2 · Cited by 1
Ziaeemehr, A., Woodman, M., Domide, L., Petkoski, S., Jirsa, V., & Hashemi, M. (2025) · eLife · doi:10.7554/elife.106194.3 · Cited by 2
Cholinergic heterogeneity facilitates synchronization and information flow in a whole-brain modelPreprint
Porta, L. D., Fousek, J., Alain Destexhe, A., & Sanchez-Vives, M. V. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.10.28.685048 · Cited by 1
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Englert, R., Kincses, B., Kotikalapudi, R., Gallitto, G., Li, J., Hoffschlag, K., Woo, C., Wager, T. D., Timmann, D., Bingel, U., et al. (2025) · eLife · doi:10.7554/elife.98725.2 · Cited by 1
ORLIAGUET, G. A., & Uhrig, L. (2016) · EMC - Anestesia-Rianimazione · doi:10.1016/s1283-0771(16)80802-6
Self-citationDynamics and network structure in neuroimaging data
Papadopoulou, M. (2015) · Ghent University Academic Bibliography (Ghent University)
The Rediscovery of Slowness: Exploring the Timing of
Kringelbach, C. L., McIntosh, A. R., & Ritter, P. (2015)
A knowledge based approach to science and technology of mind, consciousness and reality
Majumder, D. D., Datta, A., Dattamajumder, D., Chakraborty, A., & Karan, S. (2015) · International Conference on Soft Computing Techniques and Implementations (ICSCTI) · doi:10.1109/icscti.2015.7489627
A Topological Theory of Knowledge in the Human BrainPreprint
Tozzi, A., & Peters, J. F. (2016) · viXra
8. Computation Theories of Consciousness
Gamez, D. (2018) · Open Book Publishers · doi:10.11647/obp.0107.08
2. The Emergence of the Concept of Consciousness
Gamez, D. (2018) · Open Book Publishers · doi:10.11647/obp.0107.02
Appendix: Definitions, Assumptions, Lemmas and Constraints
Gamez, D. (2018) · Open Book Publishers · doi:10.11647/obp.0107.13
9. Predictions and Deductions about Consciousness
Gamez, D. (2018) · Open Book Publishers · doi:10.11647/obp.0107.09
6. Physical Theories of Consciousness
Gamez, D. (2018) · Open Book Publishers · doi:10.11647/obp.0107.06
10. Modification and Enhancement of Consciousness
Gamez, D. (2018) · Open Book Publishers · doi:10.11647/obp.0107.10
3. The Philosophy and Science of Consciousness
Gamez, D. (2018) · Open Book Publishers · doi:10.11647/obp.0107.03
5. From Correlates to Theories of Consciousness
Gamez, D. (2018) · Open Book Publishers · doi:10.11647/obp.0107.05
Coordinated Activity Across Resting-State Brain Areas May Serve as ‘Fingerprint of Consciousness’
Hurley, D. (2019) · Neurology Today · doi:10.1097/01.nt.0000554416.75768.40
Huang, Z. (2019) · Physics of Life Reviews · doi:10.1016/j.plrev.2019.09.009
Neuro-PC: Causal Functional Connectivity from Neural DynamicsPreprint
Biswas, R., & Shlizerman, E. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2011.03913 · Cited by 2
Maschke, C., & Blain‐Moraes, S. (2020) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc42975.2020.9282979
Palmucci, M., & Tagliazucchi, E. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.05.05.442861
Villavicencio, M. D. L. L. P. (2020) · Repositorio Institucional Zaloamati (Universidad Autónoma Metropolitana) · doi:10.24275/uama.5813.7498
Toscano, F. S., Galadí, J. A., Escrichs, A., Perl, Y. S., López‐González, A., Sitt, J. D., Annen, J., Gosseries, O., Thibaut, A., Panda, R., et al. (2021) · Research Square · doi:10.21203/rs.3.rs-1093655/v1
Self-citationToscano, F. S., Galadí, J. A., Escrichs, A., Perl, Y. S., López‐González, A., Sitt, J. D., Annen, J., Gosseries, O., Thibaut, A., Panda, R., et al. (2021) · Research Square · doi:10.21203/rs.3.rs-1093655/v3
Self-citationJäncke, L. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.735830092.793560898
Gamez, D. (2018) · Open Book Publishers · doi:10.11647/obp.0107.14
Gamez, D. (2018) · Open Book Publishers · doi:10.11647/obp.0107.12
Gamez, D. (2018) · Open Book Publishers · doi:10.11647/obp.0107.01
Metadata
- Authors
- Barttfeld, P., Uhrig, L., Sitt, J. D., Sigman, M., Jarraya, B., & Dehaene, S.
- Affiliations
- Inserm (FR)
- Centre National de la Recherche Scientifique (FR)
- Universidad Torcuato Di Tella (AR)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2015-01-05
- Volume
- 112
- Issue
- 3
- Pages
- 887-892
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC4311826
- OpenAlex
- W2094377986
- Cited by
- 670
- References
- 76
- Citations by year
- 2026: 30 · 2025: 72 · 2024: 54 · 2023: 62 · 2022: 63 · 2021: 69 · 2020: 55 · 2019: 53 · 2018: 65 · 2017: 57 · 2016: 57 · 2015: 33
- FWCI
- 42.52
- Type
- journal article
- Language
- en
- Update notices
- correction (2015-08-31)
- Open access
- bronze
- doi.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- CONICET Digital (CONICET) (submittedVersion, cc-by-nc-sa)
- Funders
- James S. McDonnell Foundation
- Institut National de la Santé et de la Recherche Médicale
- Consejo Nacional de Investigaciones Científicas y Técnicas
- Fondation Roger de Spoelberch
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- consciousness, resting-state brain activity, anesthesia, structural connectivity, small-world property, negative correlation, long-range correlations, wakefulness, monkeys
- MeSH terms
- Animals, Brain, Brain Mapping, Consciousness, Macaca mulatta, Magnetic Resonance Imaging
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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