Hostname: page-component-78c5997874-ndw9j Total loading time: 0 Render date: 2024-11-16T09:20:58.620Z Has data issue: false hasContentIssue false
  • English
  • Français

EEG Power spectra and subcortical pathology in chronic disorders of consciousness

Published online by Cambridge University Press:  23 September 2020

Evan S. Lutkenhoff ,
Anna Nigri ,
Davide Rossi Sebastiano ,
Davide Sattin ,
Elisa Visani ,
Cristina Rosazza ,
Ludovico D'Incerti ,
Maria Grazia Bruzzone ,
Silvana Franceschetti  and
Matilde Leonardi
...Show all authors
Evan S. Lutkenhoff
Affiliation:
Department of Psychology, University of California Los Angeles, Los Angeles, CA, USA Brain Injury Research Center (BIRC), Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
Anna Nigri
Affiliation:
Department of Neuroradiology, Fondazione IRCCS Istituto Neurologico ‘Carlo Besta’, Milan, Italy
Davide Rossi Sebastiano
Affiliation:
Department of Neurophysiology, Fondazione IRCCS Istituto Neurologico ‘Carlo Besta’, Milan, Italy
Davide Sattin
Affiliation:
Neurology, Public Health, Disability Unit and Coma Research Centre, Fondazione IRCCS Istituto Neurologico ‘Carlo Besta’, Milan, Italy
Elisa Visani
Affiliation:
Department of Neurophysiology, Fondazione IRCCS Istituto Neurologico ‘Carlo Besta’, Milan, Italy
Cristina Rosazza
Affiliation:
Scientific Direction, Fondazione IRCCS Istituto Neurologico ‘Carlo Besta’, Milan, Italy
Ludovico D'Incerti
Affiliation:
Department of Neuroradiology, Fondazione IRCCS Istituto Neurologico ‘Carlo Besta’, Milan, Italy
Maria Grazia Bruzzone
Affiliation:
Department of Neuroradiology, Fondazione IRCCS Istituto Neurologico ‘Carlo Besta’, Milan, Italy
Silvana Franceschetti
Affiliation:
Department of Neurophysiology, Fondazione IRCCS Istituto Neurologico ‘Carlo Besta’, Milan, Italy
Matilde Leonardi
Affiliation:
Neurology, Public Health, Disability Unit and Coma Research Centre, Fondazione IRCCS Istituto Neurologico ‘Carlo Besta’, Milan, Italy
Stefania Ferraro*
Affiliation:
Department of Neuroradiology, Fondazione IRCCS Istituto Neurologico ‘Carlo Besta’, Milan, Italy School of Life Science and Technology, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China: On the behalf of the Coma Research Center, Fondazione IRCCS Istituto Neurologico ‘Carlo Besta’, Milan, Italy
Martin M. Monti
Affiliation:
Department of Psychology, University of California Los Angeles, Los Angeles, CA, USA Brain Injury Research Center (BIRC), Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
*
Author for correspondence: Stefania Ferraro, E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

Despite a growing understanding of disorders of consciousness following severe brain injury, the association between long-term impairment of consciousness, spontaneous brain oscillations, and underlying subcortical damage, and the ability of such information to aid patient diagnosis, remains incomplete.

Methods

Cross-sectional observational sample of 116 patients with a disorder of consciousness secondary to brain injury, collected prospectively at a tertiary center between 2011 and 2013. Multimodal analyses relating clinical measures of impairment, electroencephalographic measures of spontaneous brain activity, and magnetic resonance imaging data of subcortical atrophy were conducted in 2018.

Results

In the final analyzed sample of 61 patients, systematic associations were found between electroencephalographic power spectra and subcortical damage. Specifically, the ratio of beta-to-delta relative power was negatively associated with greater atrophy in regions of the bilateral thalamus and globus pallidus (both left > right) previously shown to be preferentially atrophied in chronic disorders of consciousness. Power spectrum total density was also negatively associated with widespread atrophy in regions of the left globus pallidus, right caudate, and in the brainstem. Furthermore, we showed that the combination of demographics, encephalographic, and imaging data in an analytic framework can be employed to aid behavioral diagnosis.

Conclusions

These results ground, for the first time, electroencephalographic presentation detected with routine clinical techniques in the underlying brain pathology of disorders of consciousness and demonstrate how multimodal combination of clinical, electroencephalographic, and imaging data can be employed in potentially mitigating the high rates of misdiagnosis typical of this patient cohort.

Keywords

Consciousnesselectroencephalographymagnetic resonance imagingsevere brain injury
Type
Original Article
Information
Psychological Medicine , Volume 52 , Issue 8 , June 2022 , pp. 1491 - 1500
Check for updates
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Adams, J. H., Graham, D. I., & Jennett, B. (2000). The neuropathology of the vegetative state after an acute brain insult. Brain, 123(Pt 7), 1327–1338. https://doi.org/10.1093/brain/123.7.1327.CrossRefGoogle ScholarPubMed
Bagnato, S., Boccagni, C., Prestandrea, C., Sant'Angelo, A., Castiglione, A., & Galardi, G. (2010). Prognostic value of standard EEG in traumatic and non-traumatic disorders of consciousness following coma. Clinical Neurophysiology, 121(3), 274–280. https://doi.org/10.1016/j.clinph.2009.11.008.CrossRefGoogle ScholarPubMed
Brenner, R. P. (2005). The interpretation of the EEG in stupor and coma. The Neurologist, 11(5), 271–284. https://doi.org/10.1097/01.nrl.0000178756.44055.f6.CrossRefGoogle ScholarPubMed
Bruno, M. A., Vanhaudenhuyse, A., Thibaut, A., Moonen, G., & Laureys, S. (2011). From unresponsive wakefulness to minimally conscious PLUS and functional locked-in syndromes: Recent advances in our understanding of disorders of consciousness. Journal of Neurology, 258(7), 1373–1384. https://doi.org/10.1007/s00415-011-6114-x.CrossRefGoogle ScholarPubMed
Chennu, S., Finoia, P., Kamau, E., Monti, M. M., Allanson, J., Pickard, J. D., … Bekinschtein, T. A. (2013). Dissociable endogenous and exogenous attention in disorders of consciousness. Neuroimage. Clinical, 3, 450–461. https://doi.org/10.1016/j.nicl.2013.10.008.CrossRefGoogle ScholarPubMed
Coleman, M. R., Bekinschtein, T., Monti, M. M., Owen, A. M., & Pickard, J. D. (2009). A multimodal approach to the assessment of patients with disorders of consciousness. Progress in Brain Research, 177, 231–248. https://doi.org/10.1016/S0079-6123(09)17716-6.CrossRefGoogle Scholar
Corchs, S., Chioma, G., Dondi, R., Gasparini, F., Manzoni, S., Markowska-Kacznar, U., … Morreale, A. (2019). Computational methods for resting-state EEG of patients with disorders of consciousness. Frontiers in Neuroscience, 13, 807. https://doi.org/10.3389/fnins.2019.00807.CrossRefGoogle ScholarPubMed
Crone, J. S., Bio, B. J., Vespa, P. M., Lutkenhoff, E. S., & Monti, M. M. (2018). Restoration of thalamo-cortical connectivity after brain injury: Recovery of consciousness, complex behavior, or passage of time? Journal of Neuroscience Research, 96(4), 671–687. https://doi.org/10.1002/jnr.24115.CrossRefGoogle ScholarPubMed
Crone, J. S., Schurz, M., Holler, Y., Bergmann, J., Monti, M., Schmid, E., … Kronbichler, M. (2015). Impaired consciousness is linked to changes in effective connectivity of the posterior cingulate cortex within the default mode network. Neuroimage, 110, 101–109. https://doi.org/10.1016/j.neuroimage.2015.01.037.CrossRefGoogle ScholarPubMed
Crunelli, V., Lorincz, M. L., Connelly, W. M., David, F., Hughes, S. W., Lambert, R. C., … Errington, A. C. (2018). Dual function of thalamic low-vigilance state oscillations: Rhythm-regulation and plasticity. Nature Reviews: Neuroscience, 19(2), 107–118. https://doi.org/10.1038/nrn.2017.151.CrossRefGoogle ScholarPubMed
Demertzi, A., Antonopoulos, G., Heine, L., Voss, H. U., Crone, J. S., de Los Angeles, C., … Laureys, S. (2015). Intrinsic functional connectivity differentiates minimally conscious from unresponsive patients. Brain, 138(Pt 9), 2619–2631. https://doi.org/10.1093/brain/awv169.CrossRefGoogle ScholarPubMed
Demertzi, A., Tagliazucchi, E., Dehaene, S., Deco, G., Barttfeld, P., Raimondo, F., … Sitt, J. D. (2019). Human consciousness is supported by dynamic complex patterns of brain signal coordination. Science Advances, 5(2), eaat7603. https://doi.org/10.1126/sciadv.aat7603.CrossRefGoogle ScholarPubMed
Edlow, B. L., Chatelle, C., Spencer, C. A., Chu, C. J., Bodien, Y. G., O'Connor, K. L., … Wu, O. (2017). Early detection of consciousness in patients with acute severe traumatic brain injury. Brain, 140(9), 2399–2414. https://doi.org/10.1093/brain/awx176.CrossRefGoogle ScholarPubMed
Engemann, D. A., Kozynets, O., Sabbagh, D., Lemaitre, G., Varoquaux, G., Liem, F., & Gramfort, A. (2020). Combining magnetoencephalography with magnetic resonance imaging enhances learning of surrogate-biomarkers. Elife, 9, e54055. https://doi.org/10.7554/eLife.54055.CrossRefGoogle ScholarPubMed
Estraneo, A., Loreto, V., Guarino, I., Boemia, V., Paone, G., Moretta, P., & Trojano, L. (2016). Standard EEG in diagnostic process of prolonged disorders of consciousness. Clinical Neurophysiology, 127(6), 2379–2385. https://doi.org/10.1016/j.clinph.2016.03.021.CrossRefGoogle ScholarPubMed
Fingelkurts, A. A., Fingelkurts, A. A., Bagnato, S., Boccagni, C., & Galardi, G. (2013). The value of spontaneous EEG oscillations in distinguishing patients in vegetative and minimally conscious states. Supplements to Clinical Neurophysiology, 62, 81–99. https://doi.org/10.1016/b978-0-7020-5307-8.00005-3.CrossRefGoogle ScholarPubMed
Giacino, J. T., Kalmar, K., & Whyte, J. (2004). The JFK coma recovery scale-revised: Measurement characteristics and diagnostic utility. Archives of Physical Medicine and Rehabilitation, 85(12), 2020–2029. https://doi.org/10.1016/j.apmr.2004.02.033.CrossRefGoogle ScholarPubMed
Koelman, L. A., & Lowery, M. M. (2019). Beta-band resonance and intrinsic oscillations in a biophysically detailed model of the subthalamic nucleus-globus pallidus network. Frontiers in Computational Neuroscience, 13, 77. https://doi.org/10.3389/fncom.2019.00077.CrossRefGoogle Scholar
Kumral, D., Sansal, F., Cesnaite, E., Mahjoory, K., Al, E., Gaebler, M., … Villringer, A. (2020). BOLD And EEG signal variability at rest differently relate to aging in the human brain. Neuroimage, 207, 116373. https://doi.org/10.1016/j.neuroimage.2019.116373.CrossRefGoogle ScholarPubMed
Laureys, S. (2005). The neural correlate of (un)awareness: Lessons from the vegetative state. Trends in Cognitive Sciences, 9(12), 556–559. https://doi.org/10.1016/j.tics.2005.10.010.CrossRefGoogle ScholarPubMed
Lechinger, J., Bothe, K., Pichler, G., Michitsch, G., Donis, J., Klimesch, W., & Schabus, M. (2013). CRS-R score in disorders of consciousness is strongly related to spectral EEG at rest. Journal of Neurology, 260(9), 2348–2356. https://doi.org/10.1007/s00415-013-6982-3.CrossRefGoogle ScholarPubMed
Lehembre, R., Bruno, M. A., Vanhaudenhuyse, A., Chatelle, C., Cologan, V., Leclercq, Y., … Noirhomme, Q. (2012). Resting-state EEG study of comatose patients: A connectivity and frequency analysis to find differences between vegetative and minimally conscious states. Functional Neurology, 27(1), 41–47, <Go to ISI>://WOS:000307137200007.Google ScholarPubMed
Leon-Carrion, J., Martin-Rodriguez, J. F., Damas-Lopez, J., Barroso y Martin, J. M., & Dominguez-Morales, M. R. (2008). Brain function in the minimally conscious state: A quantitative neurophysiological study. Clinical Neurophysiology, 119(7), 1506–1514. https://doi.org/10.1016/j.clinph.2008.03.030.CrossRefGoogle ScholarPubMed
Lutkenhoff, E. S., Chiang, J., Tshibanda, L., Kamau, E., Kirsch, M., Pickard, J. D., … Monti, M. M. (2015). Thalamic and extrathalamic mechanisms of consciousness after severe brain injury. Annals of Neurology, 78(1), 68–76. https://doi.org/10.1002/ana.24423.CrossRefGoogle ScholarPubMed
Lutkenhoff, E. S., McArthur, D. L., Hua, X., Thompson, P. M., Vespa, P. M., & Monti, M. M. (2013). Thalamic atrophy in antero-medial and dorsal nuclei correlates with six-month outcome after severe brain injury. Neuroimage. Clinical, 3, 396–404. https://doi.org/10.1016/j.nicl.2013.09.010.CrossRefGoogle ScholarPubMed
Lutkenhoff, E. S., Rosenberg, M., Chiang, J., Zhang, K., Pickard, J. D., Owen, A. M., & Monti, M. M. (2014). Optimized brain extraction for pathological brains (optiBET). PLoS One, 9(12), e115551. https://doi.org/10.1371/journal.pone.0115551.CrossRefGoogle Scholar
Lutkenhoff, E. S., Wright, M. J., Shrestha, V., Real, C., McArthur, D. L., Buitrago-Blanco, M., … Monti, M. M. (2020). The subcortical basis of outcome and cognitive impairment in TBI: A longitudinal cohort study. Neurology. https://doi.org/10.1212/WNL.0000000000010825.CrossRefGoogle ScholarPubMed
Masel, B. E., & DeWitt, D. S. (2010). Traumatic brain injury: A disease process, not an event. Journal of Neurotrauma, 27(8), 1529–1540. https://doi.org/10.1089/neu.2010.1358.CrossRefGoogle ScholarPubMed
Mirzaei, A., Kumar, A., Leventhal, D., Mallet, N., Aertsen, A., Berke, J., & Schmidt, R. (2017). Sensorimotor processing in the basal ganglia leads to transient beta oscillations during behavior. Journal of Neuroscience, 37(46), 11220–11232. https://doi.org/10.1523/JNEUROSCI.1289-17.2017.CrossRefGoogle ScholarPubMed
Monti, M. M. (2012). Cognition in the vegetative state. Annual Review of Clinical Psychology, 8, 431–454. https://doi.org/10.1146/annurev-clinpsy-032511-143050.CrossRefGoogle ScholarPubMed
Monti, M. M., Laureys, S., & Owen, A. M. (2010). The vegetative state. BMJ, 341(aug02 1), c3765. https://doi.org/10.1136/bmj.c3765.CrossRefGoogle ScholarPubMed
Monti, M. M., & Owen, A. M. (2010). Behavior in the brain using functional neuroimaging to assess residual cognition and awareness after severe brain injury. Journal of Psychophysiology, 24(2), 76–82. https://doi.org/10.1027/0269-8803/a000016.CrossRefGoogle Scholar
Monti, M. M., Rosenberg, M., Finoia, P., Kamau, E., Pickard, J. D., & Owen, A. M. (2015). Thalamo-frontal connectivity mediates top-down cognitive functions in disorders of consciousness. Neurology, 84(2), 167–173. https://doi.org/10.1212/WNL.0000000000001123.CrossRefGoogle ScholarPubMed
Monti, M. M., Vanhaudenhuyse, A., Coleman, M. R., Boly, M., Pickard, J. D., Tshibanda, L., … Laureys, S. (2010). Willful modulation of brain activity in disorders of consciousness. New England Journal of Medicine, 362(7), 579–589. https://doi.org/10.1056/NEJMoa0905370.CrossRefGoogle ScholarPubMed
Nentwich, M., Ai, L., Madsen, J., Telesford, Q. K., Haufe, S., Milham, M. P., & Parra, L. C. (2020). Functional connectivity of EEG is subject-specific, associated with phenotype, and different from fMRI. Neuroimage, 218, 117001. https://doi.org/10.1016/j.neuroimage.2020.117001.CrossRefGoogle ScholarPubMed
Nigri, A., Catricala, E., Ferraro, S., Bruzzone, M. G., D'Incerti, L., Sattin, D., … members, C. R. C. (2017). The neural correlates of lexical processing in disorders of consciousness. Brain Imaging and Behavior, 11(5), 1526–1537. https://doi.org/10.1007/s11682-016-9613-7.CrossRefGoogle ScholarPubMed
Owen, A. M., Coleman, M. R., Boly, M., Davis, M. H., Laureys, S., & Pickard, J. D. (2006). Detecting awareness in the vegetative state. Science (New York, N.Y.), 313(5792), 1402. https://doi.org/10.1126/science.1130197.CrossRefGoogle ScholarPubMed
Patenaude, B., Smith, S. M., Kennedy, D. N., & Jenkinson, M. (2011). A Bayesian model of shape and appearance for subcortical brain segmentation. Neuroimage, 56(3), 907–922. https://doi.org/10.1016/j.neuroimage.2011.02.046.CrossRefGoogle ScholarPubMed
Qiu, M. H., Vetrivelan, R., Fuller, P. M., & Lu, J. (2010). Basal ganglia control of sleep-wake behavior and cortical activation. European Journal of Neuroscience, 31(3), 499–507. https://doi.org/10.1111/j.1460-9568.2009.07062.x.CrossRefGoogle ScholarPubMed
Rosazza, C., Andronache, A., Sattin, D., Bruzzone, M. G., Marotta, G., Nigri, A., … Coma Research Center, B. I. (2016). Multimodal study of default-mode network integrity in disorders of consciousness. Annals of Neurology, 79(5), 841–853. https://doi.org/10.1002/ana.24634.CrossRefGoogle ScholarPubMed
Rossi Sebastiano, D., Panzica, F., Visani, E., Rotondi, F., Scaioli, V., Leonardi, M., … Franceschetti, S. (2015). Significance of multiple neurophysiological measures in patients with chronic disorders of consciousness. Clinical Neurophysiology, 126(3), 558–564. https://doi.org/10.1016/j.clinph.2014.07.004.CrossRefGoogle ScholarPubMed
Rossi Sebastiano, D., Visani, E., Panzica, F., Sattin, D., Bersano, A., Nigri, A., … Franceschetti, S. (2018). Sleep patterns associated with the severity of impairment in a large cohort of patients with chronic disorders of consciousness. Clinical Neurophysiology, 129(3), 687–693. https://doi.org/10.1016/j.clinph.2017.12.012.CrossRefGoogle Scholar
Sacco, S., Altobelli, E., Pistarini, C., Cerone, D., Cazzulani, B., & Carolei, A. (2011). Validation of the Italian version of the Coma Recovery Scale-Revised (CRS-R). Brain Injury, 25(5), 488–495. https://doi.org/10.3109/02699052.2011.558043.CrossRefGoogle Scholar
Schiff, N. D. (2006). Multimodal neuroimaging approaches to disorders of consciousness. Journal of Head Trauma Rehabilitation, 21(5), 388–397. https://doi.org/10.1097/00001199-200609000-00003.CrossRefGoogle ScholarPubMed
Schiff, N. D. (2010). Recovery of consciousness after brain injury: A mesocircuit hypothesis. Trends in Neurosciences, 33(1), 1–9. https://doi.org/10.1016/j.tins.2009.11.002.CrossRefGoogle ScholarPubMed
Schiff, N. D. (2016). Mesocircuit mechanisms underlying recovery of consciousness following severe brain injuries: Model and predictions. In Monti, M. M. & Sannita, W. G., Brain function and responsiveness in disorders of consciousness (pp. 195–204). Cham: Springer. https://doi.org/10.1007/978-3-319-21425-2Google Scholar
Schiff, N. D., Nauvel, T., & Victor, J. D. (2014). Large-scale brain dynamics in disorders of consciousness. Current Opinion in Neurobiology, 25, 7–14. https://doi.org/10.1016/j.conb.2013.10.007.CrossRefGoogle ScholarPubMed
Schnakers, C., Giacino, J., Kalmar, K., Piret, S., & Lopez, E. (2006). Does the FOUR score correctly diagnose the vegetative and minimally conscious states? Tomographic visualization of cholinesterase. Annals of Neurology, 60(6), 2005–2006.CrossRefGoogle Scholar
Schnakers, C., Lutkenhoff, E. S., Bio, B. J., McArthur, D. L., Vespa, P. M., & Monti, M. M. (2019). Acute EEG spectra characteristics predict thalamic atrophy after severe TBI. Journal of Neurology. Neurosurgery and Psychiatry, 90(5), 617–619. https://doi.org/10.1136/jnnp-2017-317829.CrossRefGoogle Scholar
Schnakers, C., & Monti, M. M. (2017). Disorders of consciousness after severe brain injury: Therapeutic options. Current Opinion in Neurology, 30(6), 573–579. https://doi.org/10.1097/WCO.0000000000000495.CrossRefGoogle ScholarPubMed
Schnakers, C., Perrin, F., Schabus, M., Majerus, S., Ledoux, D., Damas, P., … Laureys, S. (2008). Voluntary brain processing in disorders of consciousness. Neurology, 71(20), 1614–1620. https://doi.org/10.1212/01.wnl.0000334754.15330.69.CrossRefGoogle ScholarPubMed
Schnakers, C., Vanhaudenhuyse, A., Giacino, J., Ventura, M., Boly, M., Majerus, S., … Laureys, S. (2009). Diagnostic accuracy of the vegetative and minimally conscious state: Clinical consensus versus standardized neurobehavioral assessment. BMC Neurology, 9, 35. https://doi.org/10.1186/1471-2377-9-35.CrossRefGoogle ScholarPubMed
Smith, S. M., & Nichols, T. E. (2009). Threshold-free cluster enhancement: Addressing problems of smoothing, threshold dependence and localisation in cluster inference. Neuroimage, 44(1), 83–98. https://doi.org/10.1016/j.neuroimage.2008.03.061.CrossRefGoogle ScholarPubMed
Smith, S. M., Zhang, Y., Jenkinson, M., Chen, J., Matthews, P. M., Federico, A., & De Stefano, N. (2002). Accurate, robust, and automated longitudinal and cross-sectional brain change analysis. Neuroimage, 17(1), 479–489. https://doi.org/10.1006/nimg.2002.1040.CrossRefGoogle ScholarPubMed
Stender, J., Gosseries, O., Bruno, M. A., Charland-Verville, V., Vanhaudenhuyse, A., Demertzi, A., … Laureys, S. (2014). Diagnostic precision of PET imaging and functional MRI in disorders of consciousness: A clinical validation study. Lancet (London, England), 384(9942), 514–522. https://doi.org/10.1016/S0140-6736(14)60042-8.CrossRefGoogle ScholarPubMed
Vanhaudenhuyse, A., Noirhomme, Q., Tshibanda, L. J., Bruno, M. A., Boveroux, P., Schnakers, C., … Boly, M. (2010). Default network connectivity reflects the level of consciousness in non-communicative brain-damaged patients. Brain, 133(Pt 1), 161–171. https://doi.org/10.1093/brain/awp313.CrossRefGoogle ScholarPubMed
Zheng, Z. S., Reggente, N., Lutkenhoff, E., Owen, A. M., & Monti, M. M. (2017). Disentangling disorders of consciousness: Insights from diffusion tensor imaging and machine learning. Human Brain Mapping, 38(1), 431–443. https://doi.org/10.1002/hbm.23370.CrossRefGoogle ScholarPubMed
Supplementary material: File

Lutkenhoff et al. Supplementary Materials

Lutkenhoff et al. Supplementary Materials 1

Download Lutkenhoff et al. Supplementary Materials(File)
File 182 KB
Supplementary material: File

Lutkenhoff et al. Supplementary Materials

Lutkenhoff et al. Supplementary Materials 2

Download Lutkenhoff et al. Supplementary Materials(File)
File 1.7 MB