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Record W2111947480 · doi:10.1097/wnr.0b013e3282f49083

Detecting faces in pure noise images: a functional MRI study on top-down perception

2008· article· en· W2111947480 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

VenueNeuroreport · 2008
Typearticle
Languageen
FieldNeuroscience
TopicFace Recognition and Perception
Canadian institutionsUniversity of Toronto
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsFusiform face areaPsychologyFace perceptionPerceptionFace (sociological concept)NeuroscienceOccipital lobeFunctional magnetic resonance imagingAudiologyCognitive psychologyMedicine

Abstract

fetched live from OpenAlex

To assess the nature of top-down perceptual processes without contamination from bottom-up input, this functional MRI study investigated face detection in pure noise images. Greater activation was revealed for face versus nonface responses in the fusiform face area, but not in the occipital face area. Across participants, positive correlations were found for the degree of greater face-detection activation between the fusiform face area and bilateral inferior frontal gyri, suggesting a top-down pathway generating perceptual expectations. In contrast, the medial frontal, parietal, supplementary motor, parahippocampal, and striatal areas produced negative correlations between degrees of greater face-detection activation and behavioral responses, suggesting a possible role for these areas in selecting and executing appropriate responses that are based on the top-down expectations.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.758
Threshold uncertainty score0.847

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.001

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 head0.088
GPT teacher head0.302
Teacher spread0.214 · 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