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Record W3157438842 · doi:10.1002/hbm.25457

The structural and functional connectivity neural underpinnings of body image

2021· article· en· W3157438842 on OpenAlexaff
Massieh Moayedi, Nasim Noroozbahari, Georgia E. Hadjis, Kristy Themelis, Tim V. Salomons, Roger Newport, Jennifer Lewis

Bibliographic record

VenueHuman Brain Mapping · 2021
Typearticle
Languageen
FieldMedicine
TopicInfrared Thermography in Medicine
Canadian institutionsQueen's UniversityDiscovery CentreUniversity of Toronto
FundersVersus ArthritisUniversity of the West of England
KeywordsFunctional connectivityNeurosciencePsychologyNeuroimagingArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

How we perceive our bodies is fundamental to our self-consciousness and our experience in the world. There are two types of interrelated internal body representations-a subjective experience of the position of a limb in space (body schema) and the subjective experience of the shape and size of the limb (body image). Body schema has been extensively studied, but there is no evidence of the brain structure and network dynamics underpinning body image. Here, we provide the first evidence for the extrastriate body area (EBA), a multisensory brain area, as the structural and functional neural substrate for body shape and size. We performed a multisensory finger-stretch illusion that elongated the index finger. EBA volume and functional connectivity to the posterior parietal cortex are both related to the participants' susceptibility to the illusion. Taken together, these data suggest that EBA structure and connectivity encode body representation and body perception disturbances.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.023
GPT teacher head0.275
Teacher spread0.252 · 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 designObservational
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

Citations18
Published2021
Admission routes1
Has abstractyes

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