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Record W1972693886 · doi:10.1080/09541440340000475

Brain rCBF and performance in visual imagery tasks: Common and distinct processes

2004· article· en· W1972693886 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe European Journal of Cognitive Psychology · 2004
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPsychologyMental imageTask (project management)Cerebral blood flowCognitive psychologyBrain activity and meditationSulcusMotor imageryPosterior parietal cortexArtificial intelligenceNeuroimagingCognitionNeuroscienceAudiologyElectroencephalographyComputer science

Abstract

fetched live from OpenAlex

The present study was designed to discover whether variations in normalised regional cerebral blood flow (rCBF) in different brain areas predict variations in performance of different imagery tasks. Positron emission tomography (PET) was used to assess brain activity as 16 participants performed four imagery tasks. These tasks were designed so that performance was particularly sensitive to the participant's ability to form images with high resolution, to generate images from distinct segments, to parse imaged forms into parts while inspecting them, or to transform (rotate) images. Response times and error rates were recorded. Multiple regression analyses revealed that variations in most brain areas predicted variations in performance of only one task, thus demonstrating that the four tasks tap largely independent imagery processes. However, we also found that some underlying processes were recruited by more than one task, particularly those implemented in the occipito‐parietal sulcus, the medial frontal cortex, and Area 18.

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.

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)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.715
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.037
GPT teacher head0.323
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