意识测量“金标准”的路径重审：从闭环脑机接口到形而上学基础

doi:10.3785/j.issn.1008-942X.CN33-6000/C.2026.07.091

Abstract
Figure/Table
References
Related Citation (1)

Download: PDF (815 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract Consciousness measurement aims to detect the presence and degree of first-person subjective experience through objective and reproducible third-person means. It stands as a fundamental core challenge in consciousness science and holds particularly significant importance in the clinical diagnosis and treatment of disorders of consciousness (DoC). Approximately 40% of patients behaviorally diagnosed with vegetative state/unresponsive wakefulness syndrome (VS/UWS) actually retain residual consciousness. This phenomenon of cognitive-motor dissociation (CMD) clearly reveals a fundamental flaw in traditional diagnostic paradigms reliant on external behavioral output: behavioral negativity does not equate to the absence of consciousness. The academic community has successively developed measurement approaches such as verbal reports, behavioral scales, and passive neuroimaging. However, these paradigms all lack built-in verification mechanisms to actively distinguish the source of signals: verbal reports and the Coma Recovery Scale-Revised (CRS-R) can only provide clinically sufficient evidence for the presence of consciousness, with negative results yielding numerous false negatives; fMRI, EEG, and other passive neuroimaging techniques bypass the limitations of peripheral motor pathways but cannot differentiate the sources of neural activity, making positive results questionable in sufficiency and negative results unable to confirm the absence of consciousness.In contrast, closed-loop brain-computer interfaces (closed-loop BCIs) establish a bidirectional real-time feedback pathway between the brain and the computer, achieving three methodological leaps: by employing active task design, they significantly enhance the confidence that positive results indicate the presence of consciousness; they replace transient state judgments with a multi-trial capacity-testing logic, providing a cautious interpretive framework for negative results; and they introduce feedback intervention mechanisms, upgrading correlational inference to intention-driven behavioral testing. Nevertheless, closed-loop BCIs still have several limitations: positive results are reliable but not logically necessary, while negative results cannot distinguish between “absence of consciousness” and “failure to manifest ability”; detecting neural modulation does not equate to achieving effective bidirectional communication, thereby failing to address the deeper metaphysical question of “why neural modulation necessarily corresponds to phenomenal consciousness”; and all measurement indicators are theory-laden, with the validity interpretation of the same result inevitably varying across different theoretical frameworks of consciousness.Thus, bridging the epistemological gaps requires ontological support. Dual-perspective monism proposes that conscious experience and neural dynamics are presentations of the same reality under the first-person experiential perspective and the third-person observational perspective, respectively, providing an ontological framework for consciousness measurement. Integrated Information Theory (IIT) adopts this stance, operationalizing it through the Perturbational Complexity Index (PCI), which directly probes the intrinsic causal structure of the brain independent of sensory input and motor output. Encouraging clinical data show that this indicator effectively distinguishes between conscious and unconscious brain states and identifies residual consciousness in behaviorally unresponsive patients. In summary, the “gold standard” for consciousness measurement is not a fixed technical tool but a dynamic complex formed through continuous calibration among metaphysical presuppositions, theories of consciousness science, and measurement methods. Future efforts should clarify the theoretical premises and applicable boundaries of various technologies, promote collaborative multi-scheme assessment, and ultimately advance precise clinical diagnosis of disorders of consciousness.

Key words： consciousness measurement cognitive motor dissociation closed-loop brain-computer interface gold standard theory-ladenness dual-perspective monism

Received: 09 July 2026

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Li Hengwei
	Kong Zijia

Cite this article:

Li Hengwei,Kong Zijia. Re-examining the Path to the “Gold Standard” of Consciousness Measurement: From Closed-Loop Brain-Computer Interfaces to Metaphysical Foundations[J]. JOURNAL OF ZHEJIANG UNIVERSITY, 2026, 56(9): 20-35.

URL:

https://www.zjujournals.com/soc/EN/10.3785/j.issn.1008-942X.CN33-6000/C.2026.07.091 OR https://www.zjujournals.com/soc/EN/Y2026/V56/I9/20

1 Koch C.， Then I Am Myself the World： What Consciousness Is and How to Expand It， New York： Basic Books， 2024.
2 Tononi G. & Koch C.， “Consciousness： here， there and everywhere？” Philosophical Transactions of the Royal Society B： Biological Sciences， Vol. 370， No. 1668 （2015）， https：//doi.org/10.1098/rstb.2014.0167.
3 Nagel T.， “What is it like to be a bat？” The Philosophical Review， Vol. 83， No. 4 （1974）， pp. 435-450.
4 美］威廉·詹姆斯：《心理学原理》第一卷，方双虎等译，北京：北京师范大学出版社，2019年。
5 Block N.， “On a confusion about a function of consciousness，” Behavioral and Brain Sciences， Vol. 18， No. 2 （1995）， pp. 227-247.
6 葡］安东尼奥·达马西奥：《意识的起源》，周仁来译，杭州：浙江科学技术出版社，2026年。
7 Sellars W.， “Philosophy and the scientific image of man，” in Colodny R. （ed.）， Empiricism and the Philosophy of Mind， London： Routledge & Kegan Paul Ltd.， 1963， pp. 1-40.
8 Giacino J. T.， Kalmar K. & Whyte J.， “The JFK coma recovery scale-revised： measurement characteristics and diagnostic utility，” Archives of Physical Medicine and Rehabilitation， Vol. 85， No. 12 （2004）， pp. 2020-2029.
9 Schnakers C.， Vanhaudenhuyse A. & Giacino J. T. et al.， “Diagnostic accuracy of the vegetative and minimally conscious state： clinical consensus versus standardized neurobehavioral assessment，” BMC Neurology， Vol. 9 （2009）， https：//pubmed.ncbi.nlm.nih.gov/19622138/.
10 Bodien Y. G.， Allanson J. & Cardone P. et al.， “Cognitive motor dissociation in disorders of consciousness，” The New England Journal of Medicine， Vol. 391， No. 7 （2024）， pp. 598-608.
11 Schiff N. D.， “Cognitive motor dissociation following severe brain injuries，” JAMA Neurology， Vol. 72， No. 12 （2015）， pp. 1413-1415.
12 Owen A. M.， Coleman M. R. & Boly M. et al.， “Detecting awareness in the vegetative state，” Science， Vol. 313， No. 5792 （2006）， p. 1402.
13 Monti M. M.， Vanhaudenhuyse A. & Coleman M. R. et al.， “Willful modulation of brain activity in disorders of consciousness，” The New England Journal of Medicine， Vol. 362， No. 7 （2010）， pp. 579-589.
14 Davis M. H.， Coleman M. R. & Absalom A. R. et al.， “Dissociating speech perception and comprehension at reduced levels of awareness，” Proceedings of the National Academy of Sciences of the United States of America， Vol. 104， No. 41 （2007）， pp. 16032-16037.
15 Perrin F.， Schnakers C. & Schabus M. et al.， “Brain response to one’s own name in vegetative state， minimally conscious state， and locked-in syndrome，” Archives of Neurology， Vol. 63， No. 4 （2006）， pp. 562-569.
16 美］C.科赫：《生命本身的感觉》，李恒威译，长沙：湖南科学技术出版社，2024年。
17 Boly M.， Tshibanda L. & Vanhaudenhuyse A. et al.， “Functional connectivity in the default network during resting state is preserved in a vegetative but not in a brain dead patient，” Human Brain Mapping， Vol. 30， No. 8 （2009）， pp. 2393-2400.
18 Owen A. M. & Coleman M. R.， “Functional neuroimaging of the vegetative state，” Nature Reviews Neuroscience， Vol. 9， No. 3 （2008）， pp. 235-243.
19 美］N. R. 汉森：《发现的模式》，邢新力、周沛译，邱仁宗校，北京：中国国际广播出版社，1988年。
20 Tononi G.， Boly M. & Massimini M. et al.， “Integrated information theory： from consciousness to its physical substrate，” Nature Reviews Neuroscience， Vol. 17， No. 7 （2016）， pp. 450-461.
21 Dehaene S. & Changeux J. P.， “Experimental and theoretical approaches to conscious processing，” Neuron， Vol. 70， No. 2 （2011）， pp. 200-227.
22 Rosenthal D. M.， “Two concepts of consciousness，” Philosophical Studies， Vol. 49， No. 3 （1986）， pp. 329-359.
23 Block N.， “What is functionalism？” in Block N. （ed.）， Readings in Philosophy of Psychology， vol. 1， Cambridge： Harvard University Press， 1980， pp. 171-184.
24 Wolpaw J. R. & Wolpaw E. W.， Brain-Computer Interfaces： Principles and Practice， Oxford： Oxford University Press， 2012.
25 Owen A. M.， “When thoughts become actions： imaging disorders of consciousness，” in Dehaene S. & Christen Y. （eds.）， Characterizing Consciousness： From Cognition to the Clinic？ Berlin： Springer， 2011， pp. 99-108.
26 Seligman M. E. P.， Helplessness： On Depression， Development， and Death， San Francisco： W. H. Freeman， 1975.
27 Nagel E.， The Structure of Science： Problems in the Logic of Scientific Explanation， New York： Harcourt， Brace & World， 1961.
28 Chaudhary U.， Birbaumer N. & Ramos-Murguialday A.， “Brain-Computer interfaces for communication and rehabilitation，” Nature Reviews Neurology， Vol. 12， No. 9 （2016）， pp. 513-525.
29 Chalmers D. J.， The Conscious Mind： In Search of a Fundamental Theory， Oxford： Oxford University Press， 1996.
30 Schiff N. D.， Diringer M. & Diserens K. et al.， “Brain-Computer interfaces for communication in patients with disorders of consciousness： a gap analysis and scientific roadmap，” Neurocritical Care， Vol. 41， No. 1 （2024）， pp. 129-145.
31 Luria A. R.， The Working Brain： An Introduction to Neuropsychology， New York： Basic Books， 1973.
32 Chalmers D. J.， “Facing up to the problem of consciousness，” Journal of Consciousness Studies， Vol. 2， No. 3 （1995）， pp. 200-219.
33 李恒威：《意识的形而上学与两视一元论》，《浙江大学学报（人文社会科学版）》2012年第4期，第18-28页。
34 荷］斯宾诺莎：《伦理学》，贺麟译，北京：商务印书馆，1997年。
35 Casali A. G.， Gosseries O. & Rosanova M. et al.， “A theoretically based index of consciousness independent of sensory processing and behavior，” Science Translational Medicine， Vol. 5， No. 198 （2013）， https：//www.science.org/doi/10.1126/scitranslmed.3006294.
36 Schiff N. D.， “Making waves in consciousness research，” Science Translational Medicine， Vol. 5， No. 198 （2013）， https：//www.science.org/doi/10.1126/scitranslmed.3007004.
37 Casarotto S.， Comanducci A. & Rosanova M. et al.， “Stratification of unresponsive patients by an independently validated index of brain complexity，” Annals of Neurology， Vol. 80， No. 5 （2016）， pp. 718-729.