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Simulation in the ‘Blind’ mind: Examining unconscious mental imagery in aphantasia

2025· article· en· W4412456973 on OpenAlexafffund
Emiko J. Muraki, Penny M. Pexman

Bibliographic record

VenueNeuropsychologia · 2025
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsWestern UniversityUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMental imagePsychologyUnconscious mindEmbodied cognitionCognitive psychologyMotor imageryAuditory imageryCognitionElectroencephalographyArtificial intelligenceNeuroscience

Abstract

fetched live from OpenAlex

Aphantasia is the absence of conscious mental imagery, but it is unclear to what extent aphantasia also implicates unconscious mental imagery. Embodied theories of concept knowledge propose that word meaning involves simulation of sensory and motor experiences; thus, examining simulation can refine our understanding of imagery deficits in aphantasia and clarify whether simulation shares mechanisms with conscious and/or unconscious mental imagery. In the present study we examined whether individuals with aphantasia show sensorimotor simulation effects during language processing. We recruited 104 aphantasics and 104 age-, gender-, and education-matched controls who completed two semantic processing tasks, a parity judgement task, and a series of mental imagery questionnaires. We observed simulation effects (i.e., faster responses to words associated with more sensorimotor experience) with both aphantasia and control participants. Our results suggest that simulation during semantic processing can occur in the absence of conscious mental imagery. The findings show that unconscious mental imagery, by way of simulation, may be preserved in aphantasia. The findings also limit the extent to which conscious mental imagery and sensorimotor simulation are likely to share underlying mechanisms.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.136
Threshold uncertainty score0.593

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.075
GPT teacher head0.392
Teacher spread0.317 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2025
Admission routes2
Has abstractyes

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