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Record W4399771669 · doi:10.32920/26052913

The Influence of Stimulus Speed and Cognitive Factors on Cortical Responses to Vection-inducing Stimuli

2024· preprint· en· W4399771669 on OpenAlexaff
Polina Andrievskaia

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldNeuroscience
TopicEEG and Brain-Computer Interfaces
Canadian institutionsMcMaster UniversityCarleton University
Fundersnot available
KeywordsStimulus (psychology)NeuroscienceCognitionPsychologyCognitive psychology

Abstract

fetched live from OpenAlex

Vection is the illusion of self-motion elicited by visual cues without corresponding physical movement. Using electroencephalography, alpha activity has been found to increase in the parieto-occipital regions following vection onset. Variability in individuals' perception of upright has been reported to affect vection. Yet objective measures of this phenomenon are missing, and our understanding of how cognitive factors influence vection is limited. In this study, vection onset, offset, and neurophysiological data were recorded while participants viewed vection-inducing stimuli. Participants completed depersonalization and anxiety questionnaires and a field dependence test. Only state anxiety accounted for a substantial amount of variance in vection intensity scores. Alpha power varied as across time and stimulus speed, decreasing after vection onset and only in response to the slow-moving stimulus. This suggests that stimulus intensity may cause variation in neural responses. The results of this study can aid in the development of an objective measure of vection.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.058
GPT teacher head0.344
Teacher spread0.286 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations1
Published2024
Admission routes1
Has abstractyes

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