Therapies to Restore Consciousness in Patients with Severe Brain Injuries: A Gap Analysis and Future Directions

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Abstract

Background/Objective

For patients with disorders of consciousness (DoC) and their families, the search for new therapies has been a source of hope and frustration. Almost all clinical trials in patients with DoC have been limited by small sample sizes, lack of placebo groups, and use of heterogeneous outcome measures. As a result, few therapies have strong evidence to support their use; amantadine is the only therapy recommended by current clinical guidelines, specifically for patients with DoC caused by severe traumatic brain injury. To foster and advance development of consciousness-promoting therapies for patients with DoC, the Curing Coma Campaign convened a Coma Science Work Group to perform a gap analysis.

Methods

We consider five classes of therapies: (1) pharmacologic; (2) electromagnetic; (3) mechanical; (4) sensory; and (5) regenerative. For each class of therapy, we summarize the state of the science, identify gaps in knowledge, and suggest future directions for therapy development.

Results

Knowledge gaps in all five therapeutic classes can be attributed to the lack of: (1) a unifying conceptual framework for evaluating therapeutic mechanisms of action; (2) large-scale randomized controlled trials; and (3) pharmacodynamic biomarkers that measure subclinical therapeutic effects in early-phase trials. To address these gaps, we propose a precision medicine approach in which clinical trials selectively enroll patients based upon their physiological receptivity to targeted therapies, and therapeutic effects are measured by complementary behavioral, neuroimaging, and electrophysiologic endpoints.

Conclusions

This personalized approach can be realized through rigorous clinical trial design and international collaboration, both of which will be essential for advancing the development of new therapies and ultimately improving the lives of patients with DoC.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12028-021-01227-y.

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Most cited references 244

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The organization of the human cerebral cortex estimated by intrinsic functional connectivity.

B. Yeo, Fenna M. Krienen, Jorge Sepulcre … (2011)

Information processing in the cerebral cortex involves interactions among distributed areas. Anatomical connectivity suggests that certain areas form local hierarchical relations such as within the visual system. Other connectivity patterns, particularly among association areas, suggest the presence of large-scale circuits without clear hierarchical relations. In this study the organization of networks in the human cerebrum was explored using resting-state functional connectivity MRI. Data from 1,000 subjects were registered using surface-based alignment. A clustering approach was employed to identify and replicate networks of functionally coupled regions across the cerebral cortex. The results revealed local networks confined to sensory and motor cortices as well as distributed networks of association regions. Within the sensory and motor cortices, functional connectivity followed topographic representations across adjacent areas. In association cortex, the connectivity patterns often showed abrupt transitions between network boundaries. Focused analyses were performed to better understand properties of network connectivity. A canonical sensory-motor pathway involving primary visual area, putative middle temporal area complex (MT+), lateral intraparietal area, and frontal eye field was analyzed to explore how interactions might arise within and between networks. Results showed that adjacent regions of the MT+ complex demonstrate differential connectivity consistent with a hierarchical pathway that spans networks. The functional connectivity of parietal and prefrontal association cortices was next explored. Distinct connectivity profiles of neighboring regions suggest they participate in distributed networks that, while showing evidence for interactions, are embedded within largely parallel, interdigitated circuits. We conclude by discussing the organization of these large-scale cerebral networks in relation to monkey anatomy and their potential evolutionary expansion in humans to support cognition.

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A multi-modal parcellation of human cerebral cortex

Matthew Glasser, Timothy Coalson, Emma Robinson … (2016)

Understanding the amazingly complex human cerebral cortex requires a map (or parcellation) of its major subdivisions, known as cortical areas. Making an accurate areal map has been a century-old objective in neuroscience. Using multi-modal magnetic resonance images from the Human Connectome Project (HCP) and an objective semi-automated neuroanatomical approach, we delineated 180 areas per hemisphere bounded by sharp changes in cortical architecture, function, connectivity, and/or topography in a precisely aligned group average of 210 healthy young adults. We characterized 97 new areas and 83 areas previously reported using post-mortem microscopy or other specialized study-specific approaches. To enable automated delineation and identification of these areas in new HCP subjects and in future studies, we trained a machine-learning classifier to recognize the multi-modal ‘fingerprint’ of each cortical area. This classifier detected the presence of 96.6% of the cortical areas in new subjects, replicated the group parcellation, and could correctly locate areas in individuals with atypical parcellations. The freely available parcellation and classifier will enable substantially improved neuroanatomical precision for studies of the structural and functional organization of human cerebral cortex and its variation across individuals and in development, aging, and disease.

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Dissociable intrinsic connectivity networks for salience processing and executive control.

William Seeley, Vinod Menon, Alan F. Schatzberg … (2007)

Variations in neural circuitry, inherited or acquired, may underlie important individual differences in thought, feeling, and action patterns. Here, we used task-free connectivity analyses to isolate and characterize two distinct networks typically coactivated during functional MRI tasks. We identified a "salience network," anchored by dorsal anterior cingulate (dACC) and orbital frontoinsular cortices with robust connectivity to subcortical and limbic structures, and an "executive-control network" that links dorsolateral frontal and parietal neocortices. These intrinsic connectivity networks showed dissociable correlations with functions measured outside the scanner. Prescan anxiety ratings correlated with intrinsic functional connectivity of the dACC node of the salience network, but with no region in the executive-control network, whereas executive task performance correlated with lateral parietal nodes of the executive-control network, but with no region in the salience network. Our findings suggest that task-free analysis of intrinsic connectivity networks may help elucidate the neural architectures that support fundamental aspects of human behavior.

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Author and article information

Contributors

Brian L. Edlow:

ORCID: http://orcid.org/0000-0001-7235-8456

bedlow@mgh.harvard.edu

Journal

Journal ID (nlm-ta): Neurocrit Care

Journal ID (iso-abbrev): Neurocrit Care

Title: Neurocritical Care

Publisher: Springer US (New York )

ISSN (Print): 1541-6933

ISSN (Electronic): 1556-0961

Publication date (Electronic): 8 July 2021

Publication date PMC-release: 8 July 2021

Publication date (Print): 2021

Volume: 35

Issue: Suppl 1

Pages: 68-85

Affiliations

[1 ]GRID grid.38142.3c, ISNI 000000041936754X, Center for Neurotechnology and Neurorecovery, Department of Neurology, , Massachusetts General Hospital and Harvard Medical School, ; 175 Cambridge Street – Suite 300, Boston, MA 02114 USA

[2 ]GRID grid.38142.3c, ISNI 000000041936754X, Athinoula A. Martinos Center for Biomedical Imaging, , Massachusetts General Hospital and Harvard Medical School, ; Charlestown, MA USA

[3 ]GRID grid.4861.b, ISNI 0000 0001 0805 7253, Coma Science Group, GIGA-Consciousness, GIGA, , University of Liege, ; Liege, Belgium

[4 ]GRID grid.411374.4, ISNI 0000 0000 8607 6858, Centre du Cerveau, , University Hospital of Liege, ; Liege, Belgium

[5 ]GRID grid.268323.e, ISNI 0000 0001 1957 0327, Department of Biomedical Engineering, , Worcester Polytechnic Institute, ; Worcester, MA USA

[6 ]GRID grid.19006.3e, ISNI 0000 0000 9632 6718, Department of Neurosurgery, David Geffen School of Medicine, , University of California, Los Angeles, ; Los Angeles, CA USA

[7 ]GRID grid.223827.e, ISNI 0000 0001 2193 0096, Departments of Neurosurgery and Biomedical Engineering, , University of Utah, ; Salt Lake City, UT USA

[8 ]GRID grid.38142.3c, ISNI 000000041936754X, Department of Neurology, , Brigham and Women’s Hospital and Harvard Medical School, ; Boston, MA USA

[9 ]GRID grid.21107.35, ISNI 0000 0001 2171 9311, Departments of Anesthesiology and Critical Care Medicine, Radiology, and Neurology and Neurosurgery, School of Medicine, , Johns Hopkins University, ; Baltimore, MD USA

Author information

Brian L. Edlow http://orcid.org/0000-0001-7235-8456

Article

Publisher ID: 1227

DOI: 10.1007/s12028-021-01227-y

PMC ID: 8266715

PubMed ID: 34236624

SO-VID: daef1ef4-a3c5-4e78-9f08-4e24d6692558

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 7 February 2021

Date accepted : 4 March 2021

Funding

Funded by: Neurocritical Care Society

Funded by: National Institute of Neurological Disorders and Stroke (US)

Award ID: R21NS109627

Award Recipient : Brian L. Edlow

Funded by: FundRef http://dx.doi.org/10.13039/100000052, NIH Office of the Director;

Award ID: DP2HD101400

Award Recipient : Brian L. Edlow

Funded by: Belgian National Fund for Scientific Research

Funded by: FundRef http://dx.doi.org/10.13039/100001411, King Baudouin Foundation United States;

Funded by: FundRef http://dx.doi.org/10.13039/100010665, H2020 Marie Skłodowska-Curie Actions;

Funded by: FundRef http://dx.doi.org/10.13039/100000913, James S. McDonnell Foundation;

Funded by: Tiny Blue Dot Foundation

Funded by: Mind Science Foundation

Funded by: BIAL Foundation

Funded by: AstraZeneca Foundation

Custom metadata

issue-copyright-statement © Springer Science+Business Media, LLC, part of Springer Nature and Neurocritical Care Society 2021

ScienceOpen disciplines: Emergency medicine & Trauma

Keywords: coma,consciousness,disorders of consciousness,gap analysis,precision medicine

Data availability:

ScienceOpen disciplines: Emergency medicine & Trauma

Keywords: coma, consciousness, disorders of consciousness, gap analysis, precision medicine

Therapies to Restore Consciousness in Patients with Severe Brain Injuries: A Gap Analysis and Future Directions

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Abstract

Background/Objective

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Conclusions

Supplementary Information

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Science of nonlocal Consciousness

Most cited references 244

The organization of the human cerebral cortex estimated by intrinsic functional connectivity.

A multi-modal parcellation of human cerebral cortex

Dissociable intrinsic connectivity networks for salience processing and executive control.

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