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Record W1974622703 · doi:10.1162/jocn.2009.21211

Neural Correlates of Human Body Perception

2009· article· en· W1974622703 on OpenAlexafffund
Rosanne Aleong, Tomáš Paus

Bibliographic record

VenueJournal of Cognitive Neuroscience · 2009
Typearticle
Languageen
FieldNeuroscience
TopicFace Recognition and Perception
Canadian institutionsMcGill University
FundersCanadian Institutes of Health ResearchUniversity of Nottingham
KeywordsLateralization of brain functionPsychologyPerceptionRight hemisphereMorphingAdaptation (eye)Dominance (genetics)AudiologyDevelopmental psychologyCognitive psychologyNeuroscienceBiology

Abstract

fetched live from OpenAlex

The objective of this study was to investigate potential sex differences in the neural response to human bodies using fMRI carried out in healthy young adults. We presented human bodies in a block-design experiment to identify body-responsive regions of the brain, namely, extrastriate body area (EBA) and fusiform body area (FBA). In a separate event-related "adaptation" experiment, carried out in the same group of subjects, we presented sets of four human bodies of varying body size and shape. Varying levels of body morphing were introduced to assess the degree of morphing required for adaptation release. Analysis of BOLD signal in the block-design experiment revealed significant Sex x Hemisphere interactions in the EBA and the FBA responses to human bodies. Only women showed greater BOLD response to bodies in the right hemisphere compared with the left hemisphere for both EBA and FBA. The BOLD response in right EBA was higher in women compared with men. In the adaptation experiment, greater right versus left hemisphere response for EBA and FBA was also identified among women but not men. These findings are particularly novel in that they address potential sex differences in the lateralization of EBA and FBA responses to human body images. Although previous studies have found some degree of right hemisphere dominance in body perception, our results suggest that such a functional lateralization may differ between men and women.

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.650
Threshold uncertainty score0.496

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.057
GPT teacher head0.341
Teacher spread0.284 · 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 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

Citations47
Published2009
Admission routes2
Has abstractyes

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