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Assessing residual motor function in patients with disorders of consciousness by brain network properties of task-state EEG

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Abstract

Recent achievements in evaluating the residual consciousness of patients with disorders of consciousness (DOCs) have demonstrated that spontaneous or evoked electroencephalography (EEG) could be used to improve consciousness state diagnostic classification. Recent studies showed that the EEG signal of the task-state could better characterize the conscious state and cognitive ability of the brain, but it has rarely been used in consciousness assessment. A cue-guide motor task experiment was designed, and task-state EEG were collected from 18 patients with unresponsive wakefulness syndrome (UWS), 29 patients in a minimally conscious state (MCS), and 19 healthy controls. To obtain the markers of residual motor function in patients with DOC, the event-related potential (ERP), scalp topography, and time–frequency maps were analyzed. Then the coherence (COH) and debiased weighted phase lag index (dwPLI) networks in the delta, theta, alpha, beta, and gamma bands were constructed, and the correlations of network properties and JFK Coma Recovery Scale-Revised (CRS-R) motor function scores were calculated. The results showed that there was an obvious readiness potential (RP) at the Cz position during the motor preparation process in the MCS group, but no RP was observed in the UWS group. Moreover, the node degree properties of the COH network in the theta and alpha bands and the global efficiency properties of the dwPLI network in the theta band were significantly greater in the MCS group compared to the UWS group. The above network properties and CRS-R motor function scores showed a strong linear correlation. These findings demonstrated that the brain network properties of task-state EEG could be markers of residual motor function of DOC patients.

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References

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

    Article  PubMed  PubMed Central  Google Scholar 

  • Bai Y, **a X, Kang J et al (2017b) TDCS modulates cortical excitability in patients with disorders of consciousness. Neuroimage Clin 15:702–709

    Article  PubMed  PubMed Central  Google Scholar 

  • Bai Y, Lin Y, Ziemann U (2020) Managing disorders of consciousness: the role of electroencephalography. J Neurol 268(11):4033–4065

    Article  PubMed  PubMed Central  Google Scholar 

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

    Google Scholar 

  • Bodart O, Gosseries O, Wannez S et al (2017) Measures of metabolism and complexity in the brain of patients with disorders of consciousness. Neuroimage Clin 14:354–362

    Article  PubMed  PubMed Central  Google Scholar 

  • Cruse D, Chennu S, Chatelle C et al (2011) Bedside detection of awareness in the vegetative state: a cohort study. Lancet 378(9809):2088–2094

    Article  PubMed  Google Scholar 

  • Delorme A, Makeig S (2004) Eeglab: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Methods 134(1):9–21

    Article  PubMed  Google Scholar 

  • di Russo F, Berchicci M, Bozzacchi C et al (2017) Beyond the “Bereitschaftspotential”: action preparation behind cognitive functions. Neurosci Biobehav Rev 78:57–81

    Article  PubMed  Google Scholar 

  • Giacino JI, Ashwal S, Childs N et al (2002) The minimally conscious state: definition and diagnostic criteria - Reply. Neurology 59(9):1473–1474

    Article  Google Scholar 

  • Giacino JT, Kalmar K, Whyte J (2004) The JFK coma recovery scale-revised: measurement characteristics and diagnostic utility. Arch Phys Med Rehab 85(12):2020–2029

    Article  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 

  • Gui P, Jiang Y, Zang D et al (2020) Assessing the depth of language processing in patients with disorders of consciousness. Nat Neurosci 23(6):761–770

    Article  CAS  PubMed  Google Scholar 

  • Hu Y, Zhang L, Chen M et al (2017) How electroencephalogram reference influences the movement readiness potential? Front Neurosci 11:683

    Article  PubMed  PubMed Central  Google Scholar 

  • Jung TP, Makeig S, Westerfield M et al (2000) Removal of eye activity artifacts from visual event-related potentials in normal and clinical subjects. Clin Neurophysiol 111(10):1745–1758

    Article  CAS  PubMed  Google Scholar 

  • Klimkeit EI, Mattingley JB, Sheppard DM et al (2005) Motor preparation, motor execution, attention, and executive functions in attention deficit/hyperactivity disorder (ADHD). Child Neuropsychol 11(2):153–173

    Article  PubMed  Google Scholar 

  • Kornhuber HH, Deecke L (1965) Changes in the brain potential in voluntary movements and passive movements in man: readiness potential and reafferent potentials. Pflugers Arch Gesamte Physiol Menschen Tiere 284(6):1–17

    Article  CAS  PubMed  Google Scholar 

  • Latora V, Marchiori M (2001) Efficient behavior of small-world networks. Phys Rev Lett 87(19):198701

    Article  CAS  PubMed  Google Scholar 

  • Laureys S, Celesia GG, Cohadon F et al (2010) Unresponsive wakefulness syndrome: a new name for the vegetative state or apallic syndrome. Bmc Med. https://doi.org/10.1186/1741-7015-8-68

    Article  PubMed  PubMed Central  Google Scholar 

  • Li R, Song WQ, Du JB et al (2015) Connecting the P300 to the diagnosis and prognosis of unconscious patients. Neural Regen Res 10(3):473–480

    Article  PubMed  PubMed Central  Google Scholar 

  • Liu TJ, Li FL, Jiang Y et al (2017) cortical dynamic causality network for auditory-motor tasks. IEEE Trans Neural Sys Rehabil Eng 25(8):1092–1099

    Google Scholar 

  • Malagurski B, Peran P, Sarton B et al (2019) Topological disintegration of resting state functional connectomes in coma. Neuroimage 195:354–361

    Article  PubMed  Google Scholar 

  • Mohseni M, Shalchyan V, Jochumsen M et al (2020) Upper limb complex movements decoding from pre-movement EEG signals using wavelet common spatial patterns. Comput Methods Progr Biomed 183:105076

    Article  Google Scholar 

  • Mouthon AL, van Hedel HJA, Meyer-Heim A et al (2016) High-density electroencephalographic recordings during sleep in children with disorders of consciousness. Neuroimage Clin 11:468–475

    Article  PubMed  PubMed Central  Google Scholar 

  • Naro A, Bramanti P, Leo A et al (2016) Transcranial alternating current stimulation in patients with chronic disorder of consciousness: a possible way to cut the diagnostic Gordian knot? Brain Topogr 29(4):623–644

    Article  PubMed  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 

  • Nguyen VT, Breakspear M, Cunnington R (2014) Reciprocal interactions of the SMA and cingulate cortex sustain premovement activity for voluntary actions. J Neurosci 34(49):16397–16407

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Oostenveld R, Fries P, Maris E et al (2011) FieldTrip: open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data. Comput Intell Neurosci 2011:156869

    Article  PubMed  Google Scholar 

  • Pan J, **e Q, Qin P et al (2020) Prognosis for patients with cognitive motor dissociation identified by brain-computer interface. Brain 143(4):1177–1189

    Article  PubMed  PubMed Central  Google Scholar 

  • Peraza LR, Aziz URA, Gary G et al (2012) Volume conduction effects in brain network inference from electroencephalographic recordings using phase lag index. J Neurosci Methods 207(2):189–199

    Article  PubMed  Google Scholar 

  • Pereda E, Quiroga RQ, Bhattacharya J (2005) Nonlinear multivariate analysis of neurophysiological signals. Prog Neurobiol 77(1–2):1–37

    Article  PubMed  Google Scholar 

  • Pfurtscheller G, da Silva FHL (1999) Event-related EEG/MEG synchronization and desynchronization: basic principles. Clin Neurophysiol 110(11):1842–1857

    Article  CAS  PubMed  Google Scholar 

  • Ragazzoni A, Pirulli C, Veniero D et al (2013) Vegetative versus minimally conscious states: a study using TMS-EEG, sensory and event-related potentials. PLoS ONE 8(2):e57069

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Risetti M, Formisano R, Toppi J et al (2013) On ERPs detection in disorders of consciousness rehabilitation [J]. Front Human Neurosci. https://doi.org/10.3389/fnhum.2013.00775

    Article  Google Scholar 

  • Rohaut B, Faugeras F, Chausson N et al (2015) Probing ERP correlates of verbal semantic processing in patients with impaired consciousness. Neuropsychologia 66:279–292

    Article  PubMed  Google Scholar 

  • Rossi Sebastiano D, Visani E, Panzica F et al (2018) Sleep patterns associated with the severity of impairment in a large cohort of patients with chronic disorders of consciousness. Clin Neurophysiol 129(3):687–693

    Article  PubMed  Google Scholar 

  • Rubinov M, Sporns O (2010) Complex network measures of brain connectivity: uses and interpretations. Neuroimage 52(3):1059–1069

    Article  PubMed  Google Scholar 

  • Schiff ND, Plum F (2000) The role of arousal and “gating” systems in the neurology of impaired consciousness. J Clin Neurophysiol 17(5):438–452

    Article  CAS  PubMed  Google Scholar 

  • Schmidt S, Jo HG, Wittmann M et al (2016) “Catching the waves” - slow cortical potentials as moderator of voluntary action. Neurosci Biobehav R 68:639–650

    Article  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. https://doi.org/10.1186/1471-2377-9-35

    Article  PubMed  PubMed Central  Google Scholar 

  • Schurger A, Hu P, X, et al (2021) What is the readiness potential? Trends Cognit Sci 25(7):558–570

    Article  Google Scholar 

  • Shibasaki H, Hallett M (2006) What is the Bereitschaftspotential? Clin Neurophysiol 117(11):2341–2356

    Article  PubMed  Google Scholar 

  • Stefan S, Schorr B, Lopez-Rolon A et al (2018) Consciousness indexing and outcome prediction with resting-state EEG in severe disorders of consciousness. Brain Topogr 31(5):848–862

    Article  PubMed  Google Scholar 

  • Vinck M, Oostenveld R, van Wingerden M et al (2011) An improved index of phase-synchronization for electrophysiological data in the presence of volume-conduction, noise and sample-size bias. Neuroimage 55(4):1548–1565

    Article  PubMed  Google Scholar 

  • Wang K, Xu M, Wang Y et al (2020) Enhance decoding of pre-movement EEG patterns for brain-computer interfaces. J Neural Eng 17(1):016033

    Article  PubMed  Google Scholar 

  • Wislowska M, Del Giudice R, Lechinger J et al (2017) Night and day variations of sleep in patients with disorders of consciousness. Sci Rep 7(1):266

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Wisniewski D, Goschke T, Haynes JD (2016) Similar coding of freely chosen and externally cued intentions in a fronto-parietal network. Neuroimage 134:450–458

    Article  PubMed  Google Scholar 

  • Yao DZ (2001) A method to standardize a reference of scalp EEG recordings to a point at infinity [J]. Physiol Meas 22(4):693–711

    Article  CAS  PubMed  Google Scholar 

  • Zhang L, Wang P, Zhang R et al (2020) The influence of different EEG references on scalp EEG functional network analysis during hand movement tasks. Front Hum Neurosci 14:367

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This research was supported by the Technology Project of Henan Province (No. 202102310210); the Key Project of Discipline Construction of Zhengzhou University (No. XKZDQY201905); the Chinese National Natural Science Foundation (No. 82001112); the Medical science and Technology research project of Henan Province (No. LHGJ20190409); the National Key R&D Program of China (2020YFC2006100) and the National Natural Science Foundation of China (No. 61803342). We thank LetPub (www.letpub.com) for its linguistic assistance during the preparation of this manuscript.

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Authors and Affiliations

  1. School of Electrical Engineering, Zhengzhou University, Zhengzhou, China

    Lipeng Zhang, Rui Zhang, Shizheng Li, Mingming Chen, Dezhong Yao, **feng Gao & Yuxia Hu

  2. Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology, Zhengzhou, China

    Lipeng Zhang, Rui Zhang, Shizheng Li, Mingming Chen, Dezhong Yao, **feng Gao & Yuxia Hu

  3. Institute of Neuroscience of Zhengzhou University, Zhengzhou, China

    Rui Zhang, Mingming Chen & Yuxia Hu

  4. The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, China

    Yongkun Guo, Dexiao Zhao & **njun Wang

  5. Department of Automation, Tsinghua University, Bei**g, China

    Li Shi

  6. Bei**g National Research Center for Information Science and Technology, Bei**g, China

    Li Shi

  7. The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China

    Dezhong Yao

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  1. Lipeng Zhang
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Correspondence to Yuxia Hu.

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Zhang, L., Zhang, R., Guo, Y. et al. Assessing residual motor function in patients with disorders of consciousness by brain network properties of task-state EEG. Cogn Neurodyn 16, 609–620 (2022). https://doi.org/10.1007/s11571-021-09741-7

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