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Record W2029739695 · doi:10.1007/s00221-009-1721-9

Natural facial motion enhances cortical responses to faces

2009· article· en· W2029739695 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

VenueExperimental Brain Research · 2009
Typearticle
Languageen
FieldNeuroscience
TopicFace Recognition and Perception
Canadian institutionsMcMaster University
Fundersnot available
KeywordsBiological motionFusiform gyrusNeurosciencePsychologyMotion (physics)Face perceptionFusiform face areaFace (sociological concept)Functional magnetic resonance imagingComputer visionCommunicationComputer sciencePerception

Abstract

fetched live from OpenAlex

The ability to perceive facial motion is important to successfully interact in social environments. Previously, imaging studies have investigated neural correlates of facial motion primarily using abstract motion stimuli. Here, we studied how the brain processes natural non-rigid facial motion in direct comparison to static stimuli and matched phase-scrambled controls. As predicted from previous studies, dynamic faces elicit higher responses than static faces in lateral temporal areas corresponding to hMT+/V5 and STS. Interestingly, individually defined, static-face-sensitive regions in bilateral fusiform gyrus and left inferior occipital gyrus also respond more to dynamic than static faces. These results suggest integration of form and motion information during the processing of dynamic faces even in ventral temporal and inferior lateral occipital areas. In addition, our results show that dynamic stimuli are a robust tool to localize areas related to the processing of static and dynamic face information.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.015
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0010.002

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 head0.166
GPT teacher head0.479
Teacher spread0.313 · 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