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Report

Teaser, summary, work performed and final results

Periodic Reporting for period 1 - MIDOC (Multimodal Imaging of Disorders of Consciousness)

Teaser

Summary

Advances in critical care have dramatically improved the likelihood of survival after severe head injury. However, a disorder of consciousness can follow survival after a period of coma. A patient suffering from a disorder of consciousness is seemingly vigilant; he or she can open the eyes, move sporadically and vocalize. However, deeper neurological examination may reveal that the patient is unable to establish functional communication indicating capacity for conscious awareness. Disorders of consciousness are graded along a continuum of severity, with certain cases (those labeled as minimally conscious patients) presenting relatively higher likelihood of recovery. Since clinical neurological examination relies on behavior, the rate of misdiagnosis is very high (reaching up to 40% in certain cases).It is an imperative to devise better understanding of the neurophysiological processes supporting healthy conscious wakefulness to develop new tools that assist neurologists and other health case professionals in the identification of consciousness in brain injured patients. The objective of the present action is to leverage a large collaborative set of neuroimaging data acquired from multiple recording modalities (functional resonance magnetic imaging, electroencephalography) to train machine learning classifiers that will, based on complementary neuroimaging data, output the likelihood of finding residual consciousness in each individual patient. The research stemming from this action will deliver proof-of-concept algorithms applied to state-of-the-art neuroimaging data acquired at several world-renowned institutions aiming to serve, eventually, as powerful tools to assist neurologists with the difficult task of diagnosing patients with disorders of consciousness. Furthermore, the extraction of features from the neuroimaging data that are relevant to detect consciousness will improve our knowledge on the neuroscience of this fundamental but highly elusive phenomenon.

Work performed

This summary consists of the work performed throughout the whole action. That work has been crystallized in a shared first-author publication by the grantee:

Demertzi*, E. Tagliazucchi*, S. Dehaene, G. Deco, P. Barttfeld, F. Raimondo, C. Martial, D. FernÃ¡ndez-Espejo, B. Rohaut, H. U. Voss, N. D. Schiff, A. M. Owen, S. Laureys, L. Naccache, & J. D. Sitt (* equal contribution) (2019). Human consciousness is supported by dynamic complex patterns of brain signal coordination. Science Advances, 5,:2, eaat7603.

This work represents a large collaborative effort coordinated, in large part, by the grantee. It is a complete milestone in the field, involving functional magnetic resonance (fMRI) on patients with disorders of consciousness (unresponsive wakefulness syndrome: UWS, and minimally conscious state: MCS) from the following centers: Paris (ICM - INSERM, the beneficiary institution), Liege (the Coma Research Group, PI: Steven Laureys), New York (Cornell University, PI: Nicholas Schiff), and Canada (The Brain and Mind Institute, University of Western Ontario, PI: Adrian Owen). The grantee has worked on processing the data, implementing computational algorithms, obtaining results, creating all figures, and drafting several versions of the manuscript, including the final version. This work provides evidence of certain time-resolved events in the inter-areal coordination of brain activity whose prevalence correlates with the level of conscious awareness, as inferred by expert neurological examination. Different validation sets were used to show that these events represent robust and generalizable signatures of consciousness.

This work was disseminated to a broad audience by means of press releases issued by all the participating institutions, and was covered by different news portals, magazines and radios throughout the english speaking world. Some illustrative examples are the following:

https://www.statnews.com/2019/02/06/detecting-consciousness-in-flickering-brain-signals/

https://www.news.uliege.be/cms/c_10717369/en/the-way-our-brains-self-organize-across-time-determines-our-state-of-consciousness

Two yet unpublished studies related to the aims of the present action are underway. In the first, we combine offline EEG and fMRI multimodal recordings to investigate whether the spectral changes in the EEG that are frequently used as markers of consciousness in brain injured patients correlate with region-specific changes in large-scale functional connectivity. In the second, we implement computational models of large-scale brain activity with the purpose of inferring â€œhidden parametersâ€œ in the neuroimaging recordings (e.g. levels of excitation/inhibition) that have diagnostic power.

Final results

Having reached the end of the project, the expected results after its finalization include the aforementioned two projects related to the aims of the proposal, as well as future collaborations with neurologists and technologists at the ICM to develop prototype algorithms for the automatic assessment of levels of consciousness in brain injured patients. The main progress beyond state of the art achieved in this action relates to new insights on the neurobiological mechanisms underlying persistent loss of consciousness in brain injured patients, robust insights as they were obtained using a very large cohort of patients (>150) from different research centers in Europe and USA.