Skip to main content
SpringerLink
Log in

Aberrant temporal correlations of ongoing oscillations in disorders of consciousness on multiple time scales

  • Research Article
  • Published:
Cognitive Neurodynamics Aims and scope Submit manuscript

Abstract

Changes in neural oscillation amplitude across states of consciousness has been widely reported, but little is known about the link between temporal dynamics of these oscillations on different time scales and consciousness levels. To address this question, we analyzed amplitude fluctuation of the oscillations extracted from spontaneous resting-state EEG recorded from the patients with disorders of consciousness (DOC) and healthy controls. Detrended fluctuation analysis (DFA) and measures of life-time and waiting-time were employed to characterize the temporal structure of EEG oscillations on long time scales (1–20 s) and short time scales (< 1 s), in groups with different consciousness states: patients in minimally conscious state (MCS), patients with unresponsive wakefulness syndrome (UWS) and healthy subjects. Results revealed increased DFA exponents that implies higher long-range temporal correlations (LRTC), especially in the central brain area in alpha and beta bands. On short time scales, declined bursts of oscillations were also observed. All the metrics exhibited lower individual variability in the UWS or MCS group, which may be attributed to the reduced spatial variability of oscillation dynamics. In addition, the temporal dynamics of EEG oscillations showed significant correlations with the behavioral responsiveness of patients. In summary, our findings shows that loss of consciousness is accompanied by alternation of temporal structure in neural oscillations on multiple time scales, and thus may help uncover the mechanism of underlying neuronal correlates of consciousness.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  • Bai Y, Xia X, Li X (2017) A review of resting-state electroencephalography analysis in disorders of consciousness. Front Neurol 8:471

    Article  PubMed  PubMed Central  Google Scholar 

  • Bao Y, Pöppel E, Wang L et al (2015) Synchronization as a biological, psychological and social mechanism to create common time: a theoretical frame and a single case study. PsyCh Journal 4(4):243–254

    Article  PubMed  Google Scholar 

  • Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc 57(1):289–300

    Google Scholar 

  • Bernat JL (2006) Chronic disorders of consciousness. The Lancet 367(9517):1181–1192

    Article  Google Scholar 

  • Berthouze L, James LM, Farmer SF (2010) Human EEG shows long-range temporal correlations of oscillation amplitude in Theta, Alpha and Beta bands across a wide age range. Clin Neurophysiol 121(8):1187–1197

    Article  PubMed  Google Scholar 

  • Bryce RM, Sprague KB (2012) Revisiting detrended fluctuation analysis. Sci Rep 2(1):1–6

    Article  Google Scholar 

  • Buzsáki G, Draguhn A (2004) Neuronal oscillations in cortical networks. Science 304(5679):1926–1929

    Article  PubMed  Google Scholar 

  • Cai L, Wang J, Guo Y et al (2020a) Altered inter-frequency dynamics of brain networks in disorder of consciousness. J Neural Eng 17(3):036006

    Article  PubMed  Google Scholar 

  • Cai L, Wei X, Wang J et al (2020b) Characterization of network switching in disorder of consciousness at multiple time scales. J Neural Eng 17(2):026024

    Article  PubMed  Google Scholar 

  • Calabrò RS, Cacciola A, Bramanti P et al (2015) Neural correlates of consciousness: what we know and what we have to learn! Neurol Sci 36(4):505–513

    Article  PubMed  Google Scholar 

  • Canuet L, Tellado I, Couceiro V et al (2012) Resting-state network disruption and APOE genotype in Alzheimer's disease: a lagged functional connectivity study

  • Casali AG, Gosseries O, Rosanova M et al (2013) A theoretically based index of consciousness independent of sensory processing and behavior. Sci Transl Med 5(198):198ra105

    Article  PubMed  Google Scholar 

  • Chennu S, Finoia P, Kamau E et al (2014) Spectral signatures of reorganised brain networks in disorders of consciousness. PLoS Comput Biol 10(10):e1003887

    Article  PubMed  PubMed Central  Google Scholar 

  • Desikan RS, Ségonne F, Fischl B et al (2006) An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 31(3):968–980

    Article  PubMed  Google Scholar 

  • Di Perri C, Stender J, Laureys S et al (2014) Functional neuroanatomy of disorders of consciousness. Epilepsy Behav 30:28–32

    Article  PubMed  Google Scholar 

  • Dimitriadis SI, Laskaris NA, Simos PG et al (2013) Altered temporal correlations in resting-state connectivity fluctuations in children with reading difficulties detected via MEG. Neuroimage 83:307–317

    Article  CAS  PubMed  Google Scholar 

  • Demertzi A, Antonopoulos G, Heine L et al (2015) Intrinsic functional connectivity differentiates minimally conscious from unresponsive patients. Brain 138(9):2619–2631

    Article  PubMed  Google Scholar 

  • Edelman BJ, Baxter B, He B (2015) EEG source imaging enhances the decoding of complex right-hand motor imagery tasks. IEEE Trans Biomed Eng 63(1):4–14

    Article  PubMed  PubMed Central  Google Scholar 

  • Edlow BL, Claassen J, Schiff ND et al (2021) Recovery from disorders of consciousness: mechanisms, prognosis and emerging therapies. Nat Rev Neurol 17(3):135–156

    Article  PubMed  Google Scholar 

  • Giacino JT, Kalmar K, Whyte J (2004) The JFK Coma Recovery Scale-Revised: measurement characteristics and diagnostic utility. Arch Phys Med Rehabil 85(12):2020–2029

    Article  PubMed  Google Scholar 

  • Giacino JT, Fins JJ, Laureys S et al (2014) Disorders of consciousness after acquired brain injury: the state of the science. Nat Rev Neurol 10(2):99–114

    Article  PubMed  Google Scholar 

  • Gramfort A, Papadopoulo T, Olivi E et al (2010) OpenMEEG: opensource software for quasistatic bioelectromagnetics. Biomed Eng Online 9(1):1–20

    Article  Google Scholar 

  • Haldeman C, Beggs JM (2005) Critical branching captures activity in living neural networks and maximizes the number of metastable states. Phys Rev Lett 94(5):058101

    Article  PubMed  Google Scholar 

  • Hardstone R, Poil SS, Schiavone G et al (2012) Detrended fluctuation analysis: a scale-free view on neuronal oscillations. Front Physiol 3:450

    Article  PubMed  PubMed Central  Google Scholar 

  • Harris AM, Dux PE, Mattingley JB (2020) Awareness is related to reduced post-stimulus alpha power: a no-report inattentional blindness study. Eur J Neurosci 52(11):4411–4422

    Article  PubMed  Google Scholar 

  • Hassan M, Dufor O, Merlet I et al (2014) EEG source connectivity analysis: from dense array recordings to brain networks. PLoS ONE 9(8):e105041

    Article  PubMed  PubMed Central  Google Scholar 

  • Hohlefeld FU, Huebl J, Huchzermeyer C et al (2012) Long-range temporal correlations in the subthalamic nucleus of patients with Parkinson’s disease. Eur J Neurosci 36(6):2812–2821

    Article  CAS  PubMed  Google Scholar 

  • Honey CJ, Thesen T, Donner TH et al (2012) Slow cortical dynamics and the accumulation of information over long timescales. Neuron 76(2):423–434

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Kabbara A, Falou WEL, Khalil M et al (2017) The dynamic functional core network of the human brain at rest. Sci Rep 7(1):1–16

    Article  CAS  Google Scholar 

  • Kabbara A, Eid H, El Falou W et al (2018) Reduced integration and improved segregation of functional brain networks in Alzheimer’s disease. J Neural Eng 15(2):026023

    Article  CAS  PubMed  Google Scholar 

  • Kantelhardt JW, Koscielny-Bunde E, Rego HHA et al (2001) Detecting long-range correlations with detrended fluctuation analysis. Physica A 295(3–4):441–454

    Article  Google Scholar 

  • King JR, Sitt JD, Faugeras F et al (2013) Information sharing in the brain indexes consciousness in noncommunicative patients. Curr Biol 23(19):1914–1919

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Krzemiński D, Kamiński M, Marchewka A et al (2017) Breakdown of long-range temporal correlations in brain oscillations during general anesthesia. Neuroimage 159:146–158

    Article  PubMed  Google Scholar 

  • Langton CG (1990) Computation at the edge of chaos: phase transitions and emergent computation. Physica D 42(1–3):12–37

    Article  Google Scholar 

  • Lehembre R, Bruno MA, Vanhaudenhuyse A et al (2012) Resting-state EEG study of comatose patients: a connectivity and frequency analysis to find differences between vegetative and minimally conscious states. Funct Neurol 27(1):41

    PubMed  PubMed Central  Google Scholar 

  • Liang Z, Li J, Xia X et al (2018) Long-range temporal correlations of patients in minimally conscious state modulated by spinal cord stimulation. Front Physiol 9:1511

    Article  PubMed  PubMed Central  Google Scholar 

  • Linkenkaer-Hansen K, Nikouline VV, Palva JM et al (2001) Long-range temporal correlations and scaling behavior in human brain oscillations. J Neurosci 21(4):1370–1377

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Massimini M, Ferrarelli F, Huber R et al (2005) Breakdown of cortical effective connectivity during sleep. Science 309(5744):2228–2232

    Article  CAS  PubMed  Google Scholar 

  • Montez T, Poil SS, Jones BF et al (2009) Altered temporal correlations in parietal alpha and prefrontal theta oscillations in early-stage Alzheimer disease. Proc Natl Acad Sci 106(5):1614–1619

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Naro A, Bramanti A, Leo A et al (2018) Shedding new light on disorders of consciousness diagnosis: the dynamic functional connectivity. Cortex 103:316–328

    Article  PubMed  Google Scholar 

  • Nikulin VV, Brismar T (2004) Long-range temporal correlations in alpha and beta oscillations: effect of arousal level and test–retest reliability. Clin Neurophysiol 115(8):1896–1908

    Article  PubMed  Google Scholar 

  • Nikulin VV, Jönsson EG, Brismar T (2012) Attenuation of long-range temporal correlations in the amplitude dynamics of alpha and beta neuronal oscillations in patients with schizophrenia. Neuroimage 61(1):162–169

    Article  PubMed  Google Scholar 

  • Noirhomme Q, Kitney RI, Macq B (2008) Single-trial EEG source reconstruction for brain–computer interface. IEEE Trans Biomed Eng 55(5):1592–1601

    Article  PubMed  Google Scholar 

  • Northoff G (2017) “Paradox of slow frequencies”—are slow frequencies in upper cortical layers a neural predisposition of the level/state of consciousness (NPC)? Conscious Cogn 54:20–35

    Article  PubMed  Google Scholar 

  • Palva JM, Zhigalov A, Hirvonen J et al (2013) Neuronal long-range temporal correlations and avalanche dynamics are correlated with behavioral scaling laws. Proc Natl Acad Sci 110(9):3585–3590

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Rosanova M, Gosseries O, Casarotto S et al (2012) Recovery of cortical effective connectivity and recovery of consciousness in vegetative patients. Brain 135(4):1308–1320

    Article  PubMed  PubMed Central  Google Scholar 

  • Sarasso S, Boly M, Napolitani M et al (2015) Consciousness and complexity during unresponsiveness induced by propofol, xenon, and ketamine. Curr Biol 25(23):3099–3105

    Article  CAS  PubMed  Google Scholar 

  • Schnakers C, Vanhaudenhuyse A, Giacino J et al (2009) Diagnostic accuracy of the vegetative and minimally conscious state: clinical consensus versus standardized neurobehavioral assessment. BMC Neurol 9(1):1–5

    Article  Google Scholar 

  • Seth AK, Izhikevich E, Reeke GN et al (2006) Theories and measures of consciousness: an extended framework. Proc Natl Acad Sci 103(28):10799–10804

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Shew WL, Yang H, Petermann T et al (2009) Neuronal avalanches imply maximum dynamic range in cortical networks at criticality. J Neurosci 29(49):15595–15600

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Signorelli CM, Meling D (2021) Towards new concepts for a biological neuroscience of consciousness. Cogn Neurodyn 15(5):783–804

    Article  PubMed  PubMed Central  Google Scholar 

  • Signorelli CM, Uhrig L, Kringelbach M et al (2021b) Hierarchical disruption in the cortex of anesthetized monkeys as a new signature of consciousness loss. Neuroimage 227:117618

    Article  PubMed  Google Scholar 

  • Smit DJA, Linkenkaer-Hansen K, de Geus EJC (2013) Long-range temporal correlations in resting-state alpha oscillations predict human timing-error dynamics. J Neurosci 33(27):11212–11220

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Sun J, Tang Y, Lim KO et al (2014) Abnormal dynamics of EEG oscillations in schizophrenia patients on multiple time scales. IEEE Trans Bio Med Eng 61(6):1756–1764

  • Thiery T, Lajnef T, Combrisson E et al (2018) Long-range temporal correlations in the brain distinguish conscious wakefulness from induced unconsciousness. Neuroimage 179:30–39

    Article  PubMed  Google Scholar 

  • Vidaurre D, Quinn AJ, Baker AP et al (2016) Spectrally resolved fast transient brain states in electrophysiological data. Neuroimage 126:81–95

    Article  PubMed  Google Scholar 

  • Wade DT (2018) How often is the diagnosis of the permanent vegetative state incorrect? A review of the evidence. Eur J Neurol 25(4):619–625

    Article  CAS  PubMed  Google Scholar 

  • Zhuang W, Wang J, Chu C et al (2022) Disrupted control architecture of brain network in disorder of consciousness. IEEE Trans Neural Syst Rehabil Eng 30:400–409

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

This work was supported by the Major Project of “Brain Science and Brain-like Research” on the Sci-Tech Innovation 2030 Agenda under Grant 2021ZD0204300, the National Natural Science Foundation of China under Grant 61771330, 62071324, the Tianjin Municipal Natural Science Foundation under Grant 18JCZDJC32000, 19JCQNJC01200, and China Postdoctoral Science Foundation under Grant 2021M692387.

Author information

Authors and Affiliations

  1. School of Electrical and Information Engineering, Tianjin University, Tianjin, China

    Xile Wei, Zhuang Yan, Lihui Cai, Guosheng Yi & Jiang Wang

  2. School of Information Technology Engineering, Tianjin University of Technology and Education, Tianjin, 300222, China

    Meili Lu

  3. Xincheng Hospital of Tianjin University, Tianjin, China

    Yueqing Dong

Authors
  1. Xile Wei
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zhuang Yan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lihui Cai
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Meili Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Guosheng Yi
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Jiang Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Yueqing Dong
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Lihui Cai or Yueqing Dong.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 78 kb)

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wei, X., Yan, Z., Cai, L. et al. Aberrant temporal correlations of ongoing oscillations in disorders of consciousness on multiple time scales. Cogn Neurodyn 17, 633–645 (2023). https://doi.org/10.1007/s11571-022-09852-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11571-022-09852-9

Keywords

Search

Navigation