Measuring the Complexity of Consciousness
Open accessAbstract
The grand quest for a scientific understanding of consciousness has given rise to many new theoretical and empirical paradigms for investigating the phenomenology of consciousness as well as clinical disorders associated to it. A major challenge in this field is to formalize computational measures that can reliably quantify global brain states from data. In particular, information-theoretic complexity measures such as integrated information have been proposed as measures of conscious awareness. This suggests a new framework to quantitatively classify states of consciousness. However, it has proven increasingly difficult to apply these complexity measures to realistic brain networks. In part, this is due to high computational costs incurred when implementing these measures on realistically large network dimensions. Nonetheless, complexity measures for quantifying states of consciousness are important for assisting clinical diagnosis and therapy. This article is meant to serve as a lookup table of measures of consciousness, with particular emphasis on clinical applicability. We consider both, principle-based complexity measures as well as empirical measures tested on patients. We address challenges facing these measures with regard to realistic brain networks, and where necessary, suggest possible resolutions.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Quantum effects have been implicated in photosynthesis.
“Quantum effects have been implicated in photosynthesis, a process fundamental to life on earth.”
From Quantum effects in the brain: A review (2020) · cites this paper as [50]
The efficacy of energy transfer and charge separation in photosynthesis might be enhanced by quantum effects.
“In particular the study of photosynthesis has revealed that the efficacy of energy transfer and charge separation might be enhanced by quantum effects [49][50][51][52][53][54] .”
From Quantum effects in the brain: A review (2020) · cites this paper as [50]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
The citation lists haven’t been fetched yet
References 51 · Cited by 35
Research works printed but not linked: 6
- Arsiwalla X. D. Herreros I. Moulin-Frier C. Verschure P. (2017a). Consciousness as an evolutionary game-theoretic strategy, in Conference on Biomimetic and Biohybrid Systems (Cham: Springer), 509– 514.
- Arsiwalla X. D. Moulin-Frier C. Herreros I. Sanchez-Fibla M. Verschure P. F. (2017c). The morphospace of consciousness. arXiv: 1705.11190. PMC11523714 39483317 · arXiv
- Arsiwalla X. D. Verschure P. (2017). Why the brain might operate near the edge of criticality, in International Conference on Artificial Neural Networks (Cham: Springer), 326– 333.
- Arsiwalla X. D. Verschure P. F. M. J. (2013). Integrated information for large complex networks, in The 2013 International Joint Conference on Neural Networks (IJCNN), (Dallas, TX), 1– 7.
- Betella A. Bueno E. M. Kongsantad W. Zucca R. Arsiwalla X. D. Omedas P. (2014). Understanding large network datasets through embodied interaction in virtual reality, in Proceedings of the 2014 Virtual Reality International Conference, VRIC '14 (New York, NY: ACM), 23: 1– 23:7.
- Moulin-Frier C. Puigbò J.-Y. Arsiwalla X. D. Sanchez-Fibla M. Verschure P. F. (2017). Embodied artificial intelligence through distributed adaptive control: An integrated framework. arXiv: 1704.01407. · arXiv
- Authors
- Arsiwalla, X. D., & Verschure, P.
- Affiliations
- Universitat Pompeu Fabra (ES)
- Institució Catalana de Recerca i Estudis Avançats (ES)
- Corresponding author
- Arsiwalla, Xerxes D.
- Verschure, Paul
- Venue
- Frontiers in Neuroscience
- Publisher
- Frontiers Media SA
- Published
- 2018-06-27
- Volume
- 12
- Pages
- 424-424
- ISSN
- 1662-453X (ISSN-L)
- PMC
- PMC6030381
- OpenAlex
- W2783748340
- Cited by
- 35
- References
- 51
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 5 · 2023: 6 · 2022: 7 · 2021: 3 · 2020: 5 · 2019: 3 · 2018: 1 · 2017: 1
- FWCI
- 3.93
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Frontiers in Neuroscience (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Repositori digital de la UPF (Universitat Pompeu Fabra) (publishedVersion, cc-by)
- arXiv (Cornell University) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- arXiv (Cornell University)
- Funders
- European Research Council (ERC-2013- ADG 341196)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Philosophy and Theoretical Science
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- consciousness, complexity measures, integrated information, information-theoretic complexity, brain networks, computational cost
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
