The Dream Catcher experiment: blinded analyses failed to detect markers of dreaming consciousness in EEG spectral power
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Abstract
The Dream Catcher test defines the criteria for a genuine discovery of the neural constituents of phenomenal consciousness. Passing the test implies that some patterns of purely brain-based data directly correspond to the subjective features of phenomenal experience, which would help to bridge the explanatory gap between consciousness and brain. Here, we conducted the Dream Catcher test for the first time in a step-wise and simplified form, capturing its core idea. The Dream Catcher experiment involved a Data Team, which measured participants' brain activity during sleep and collected dream reports, and a blinded Analysis Team, which was challenged to predict, based solely on brain measurements, whether or not a participant had a dream experience. Using a serial-awakening paradigm, the Data Team prepared 54 1-min polysomnograms of non-rapid eye movement sleep-27 of dreamful sleep and 27 of dreamless sleep (three of each condition from each of the nine participants)-redacting from them all associated participant and dream information. The Analysis Team attempted to classify each recording as either dreamless or dreamful using an unsupervised machine learning classifier, based on hypothesis-driven, extracted features of electroencephalography (EEG) spectral power and electrode location. The procedure was repeated over five iterations with a gradual removal of blindness. At no level of blindness did the Analysis Team perform significantly better than chance, suggesting that EEG spectral power could not be utilized to detect signatures specific to phenomenal consciousness in these data. This study marks the first step towards realizing the Dream Catcher test in practice.
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A "dream catcher" experiment involving separate data gathering and analysis teams failed to predict dreams from the EEG better than chance at various levels of blinding.
“A “dream catcher” experiment involving separate data gathering and analysis teams, also failed to predict dreams from the EEG better than chance at various levels of blinding.41”
From We are the Sensors of Consciousness! A Review and Analysis on How Awakenings During Sleep Influence Dream Recall (2025) · cites this paper as [41]
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The Constitution of Phenomenal Consciousness
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Evidence accumulation clustering using combinations of features
Wong, W., & Tsuchiya, N. (2020) · MethodsX · doi:10.1016/j.mex.2020.100916 · Cited by 6 · see citing works
Self-citation
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Seth, A. K., & Bayne, T. (2022) · Nature Reviews Neuroscience · doi:10.1038/s41583-022-00587-4 · Cited by 880 · see citing works
Consciousness among delta waves: a paradox?
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Andrillon, T., Windt, J., Silk, T. J., Drummond, S. P. A., Bellgrove, M. A., & Tsuchiya, N. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00949 · Cited by 124 · see citing works
Self-citationApical drive-A cellular mechanism of dreaming?
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What about dreams ? State of the art and open questions
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EEG Lempel-Ziv complexity varies with sleep stage, but does not seem to track dream experience
Aamodt, A., Sevenius Nilsen, A., Markhus, R., Kusztor, A., HasanzadehMoghadam, F., Kauppi, N., Thürer, B., Storm, J. F., & Juel, B. E. (2023) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2022.987714 · Cited by 30 · see citing works
Investigation on Neurobiological Mechanisms of Dreaming in the New Decade
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Windt, J. (2020) · Philosophy Compass · doi:10.1111/phc3.12661 · Cited by 28 · see citing works
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Mudrik, L., Hirschhorn, R., & Korisky, U. (2024) · Neuron · doi:10.1016/j.neuron.2024.03.031 · Cited by 18 · see citing works
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Unsupervised machine learning in sleep research: a scoping review
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Spectrally and temporally resolved estimation of neural signal diversityPreprint
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- Authors
- Wong, W., Noreika, V., Móró, L., Revonsuo, A., Windt, J., Valli, K., & Tsuchiya, N.
- Affiliations
- Monash University (AU)
- University of Turku (FI)
- Advanced Telecommunications Research Institute International (JP)
- Corresponding author
- Wong, William
- Tsuchiya, Naotsugu
- ORCID
- Venue
- Neuroscience of Consciousness
- Publisher
- Oxford University Press (OUP)
- Published
- 2020-01-01
- Volume
- 2020
- Issue
- 1
- Pages
- niaa006-niaa006
- ISSN
- 2057-2107 (ISSN-L)
- PMC
- PMC7362719
- OpenAlex
- W3043596444
- Cited by
- 40
- References
- 112
- Citations by year
- 2026: 2 · 2025: 8 · 2024: 2 · 2023: 10 · 2022: 4 · 2021: 5 · 2020: 7 · 2019: 1 · 2017: 1
- FWCI
- 3.49
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Neuroscience of Consciousness (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- UTUPub (University of Turku) (submittedVersion)
- Diva portal (Dalarna University Library) (submittedVersion, other-oa)
- Funders
- Australian Government Research Training Program Scholarship
- Signe and Ane Gyllenberg Foundation
- Australian Research Council Discovery Early Career Researcher (DE170101254)
- Academy of Finland (266434)
- Australian Research Council Future (FT120100619)
- Discovery Project (DP130100194, DP180104128, DP180100396)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Sleep and Wakefulness Research
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Philosophy and Theoretical Science
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Keywords
- phenomenal consciousness, dreams, EEG spectral power, NREM sleep, explanatory gap, machine learning classification, blind analysis, subjective experience
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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.
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