The Utility- and Use–of Neurotechnology to Recover Consciousness: Technical and Neuroethical Considerations in Approaching the “Hard Question” of Neuroscience

In any attempt to recover a loss, it becomes important to assess what is lost, and to what extent. In clinical medicine, evaluation of loss of particular function(s) is fundamental to both diagnosis, and planning possible interventions that may be restorative. The term diagnosis is etymologically derived from the Greek diagignoskein, “to discern.” The root of the word, gignṓskein (γιγνώσκειν) means “to learn”; the implication being that one must gain knowledge about those aspects of the thing(s) that are important for it to be distinguished, identified and characterized. If, however, the focus of discernment is the clinical assessment of consciousness in a patient who is unable to respond and/or communicate through speech or overt behavior, then the act of discernment becomes complicated, given that the cardinal characteristics of consciousness are subjectivity and self-transparency, and to that extent not viable for direct objective evaluation.

Indeed, consciousness remains the elusive, proverbial “hard question” of neuroscience, and in many ways, this is exactly the point. However, it is a question and problem that cannot simply be ignored, ascribed to mere speculative explanations, or devalued. To the contrary, it must be confronted, as the discernment of consciousness is not merely a philosophical matter, but also of practical importance in, notably, neurological diagnoses, prognoses and clinical care of patients with disorders of consciousness (DoC), such as coma, minimal consciousness or persistent unresponsive states. Such considerations of diagnosis and care are not limited to the clinical milieu. They generate ethico-legal issues that conjoin other professions (e.g., law, politics) and the public in ongoing discourse and deliberation about how such patients are, or should be regarded (e.g., with respect to their capacity for sentience; ethical concerns about quality of life; legal standing, etc.,) and treated in both the short- and the long-term, inclusive of current debates about the use of brain-machine interfaces (as focal to this thematic issue), continuity and quality of care, and the justification of life-sustaining measures.

Despite considerable progress in neuroscience, the nature of consciousness (i.e., what might be viewed in Aristotelian terms as its “efficient cause”¹) remains unknown. There are numerous theories, but at best these remain hypothetical, if not wholly notional, and often focus on some particular aspect of consciousness rather than on consciousness per se (Farisco et al., 2015). But if and when taken with information that posits putative brain substrates and functions involved in conscious processes (i.e., what may be more of an attempt at describing “material” or “formal” components² of consciousness), such exploratory constructs may be useful to developing approaches to detect types of conscious and/or unconscious activity³, and in establishing possibilities methods of neurotechnological communication with patients unable to communicate through speech or overt behavior (Evers and Sigman, 2013; Farisco and Evers, 2016).

In “putting such pieces together,” we see this both as representative of “tools-to-theory-to-tools” heuristics, and as a puzzle to be solved (and suggestion of methods toward such solution), rather than an enigma simply to ponder (Gigerenzer, 1991; Wurzman and Giordano, 2009; Giordano, 2012). Toward such a goal, we offer a hypothetical equation to establish key constructs that might be methodologically engaged. Herein, let “a/e” stand for neural activities that are indicative of some efficient process(es) of consciousness; and “m” stand for material substrates (e.g., tracts, networks, and nodes) involved in particular functional domains “d” of these processes that are held to be important in and for clinical, ethico-legal, and social value. Given this, one methodological approach might be to assess key patterns (P; e.g., differential spatio-temporal arrays of tract, network and nodal engagement in the brain; behavior[s]; etc.) in specific functional domains (“m/d”) that are reflective of neural activity indicative of efficient processes of consciousness (“a/e”), such that Pm/d ≈a/e as obtained under empirically defined conditions in accordance with (the most applicably) current theoretical models of the relationship of brain function and consciousness⁴.

Still, such patterns would need to be objectively assessable. Standard clinical diagnostic criteria rely on observing patients' behaviors and characteristics in order to formulate a clinically relevant position about the type and/or level of consciousness that may be present. However, numerous studies show that, although such observations are relevant, they represent only a first step, which remains insufficient, as behaviors of patients with DoC are typically either ambiguous, or overtly absent (Farisco et al., 2015)⁴. We therefore support the view that the combined use of behavioral observations and (multiple forms of) neuroimaging could enable better conceptualization of structural and functional correlates of consciousness, which in turn could be useful to informing decisions about the kind and extent of care patients should be provided (Giordano, 2015; Evers, 2016; Farisco et al., in press)⁵. Granting that a patient with DoC may have residual consciousness to the effect that s/he experiences subjective states, and that the relevant structural and functional correlates of consciousness are identifiable, a further question arises: (how) can we adequately interpret these patients' experiences by observing brain activities (Evers and Sigman, 2013; Farisco et al., in press)?

This question is not purely technical, or philosophical. In addition to the conceptual and technical challenges to which it gives rise, it raises important neuroethico-legal and social issues focal to procedural limitations and inadequacies, liabilities inherent to the interpretation of proxy-derivative information, and inappropriate use and/or frank misuse of technology (Uttal, 2001). Acknowledging these combined challenges, we note that resolving ambiguities in neuroimaging data remains a work-in-progress. Observations of behaviors and characteristics would be instrumental to accumulating and assimilating various types of information important to further validating the viability and value of neuroimaging approaches to demonstrate structural and functional patterns of brain activity that could be signatures of consciousness⁶. Big data tools and techniques will be essential to realizing the synthesis and utility of these multi-modal and multi-leveled data; but employing computational systems and methods in these ways is not without (present and potential) problems, as well (DiEuliis and Giordano, 2016).

Such problems demand attention, and we advocate that any employment of neuroimaging should prudently assess benefit, burden and risk of the technology in specific contexts and under particular conditions (Giordano, 2017). To these ends, we call for organized efforts toward consensus in defining the patterns of neuroimaging and behavioral data that provide meaningful value in assessing DoC. This would necessitate establishment and effort of groups that are dedicated to addressing and resolving the issues that impede the clinical use of neuroimaging. Obviously, this is not a trivial task. Yet, we believe that if progress, and realistic return on the investment of time, money and expectation in neurotechnology as promoted by large scale, international efforts (e.g., the EU Human Brain Project; United States' Brain Research through Advancing Innovative Neurotechnology—BRAIN—initiative, and other, more nascent enterprises, such as the China Brain Project; Japanese Brain/MINDS Project, etc.,) are to be achieved and sustained, then efforts to translate these tools to safe and beneficial clinical applications are essential⁷. We assert that the difficulty of assessing (and treating) patients with DoC creates a viable need, and valuable opportunity to engage such technologies, which, with acknowledgement of their relative capabilities and constraints (and endeavors toward iteratively de-limiting such capabilities), could enthuse ethically sound patient-centered care.

Within an ethical perspective, patients' previously expressed values and desires are paramount in formulating best interests' standards for the use of any technique or technology in the assessment and treatment of DoC (as in any medical condition which renders the patient unable to provide consent). We have previously emphasized the importance and need for patients (and the public; i.e., as the population of potential future patients) to be knowledgeable about what technologies are available and their possible uses, allowing them to express advance directives to state whether and which neurotechnologies they, should the situation arise, would wish to be used to define—and perhaps attempt to restore—their neurological integrity (Giordano, 2015; Pascalev and Giordano, 2015).

In any case, current difficulties in correctly diagnosing DoCs should prompt new tools to be developed that decrease error or uncertainty, inclusive of assessment neurotechnologies, and more sensitive, standardized neurobehavioral metrics. But we suggest that an additional goal is not just to assess brain functions of patients with DoC, but to access them, and thereby engage the person in whom this brain~mind⁸ is embodied. In this context, we advocate the development and use of the ever more sophisticated forms of neurotechnological communication with DoC patients who are otherwise unable to express themselves overtly or behaviorally. To re-iterate, these approaches represent a major challenge, but the possibility and potential they hold for assessing, treating, and engaging patients with DoC are promising and ethically imperative. It is in this light—and spirit—that we view the merit of further research, innovation and discourse.

Author Contributions

All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

Funding

This work was supported in part by funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement 720270: HBP SGA1 (KE and JG); federal funds UL1TR001409 from the National Center for Advancing Translational Sciences (NCATS), National Institutes of Health, through the Clinical and Translational Science Awards Program (CTSA), a trademark of the Department of Health and Human Services, part of the Roadmap Initiative, “Re-Engineering the Clinical Research Enterprise” (JG), and by the AEHS Foundation (JG).

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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