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Record W2068769677 · doi:10.1080/17470910801938023

Disturbances of self–other distinction after stimulation of the extrastriate body area in the human brain

2008· article· en· W2068769677 on OpenAlexaff
Nicole David, Marije Jansen, Michael X Cohen, Katja Osswald, Istvan Molnar-Szakacs, Albert Newen, Kai Vogeley, Tomáš Paus

Bibliographic record

VenueSocial Neuroscience · 2008
Typearticle
Languageen
FieldNeuroscience
TopicFace Recognition and Perception
Canadian institutionsMcGill University
Fundersnot available
KeywordsTranscranial magnetic stimulationPsychologyNeuroscienceStimulationExtrastriate cortexFunctional magnetic resonance imagingMotor areaBrain activity and meditationCognitive psychologyElectroencephalographyVisual cortex

Abstract

fetched live from OpenAlex

In a recent experiment with functional magnetic-resonance imaging, we found that brain activity in the extrastriate body area (EBA) distinguished between observed self- and other-generated movements, being significantly higher during observation of someone else's movement. Here, we investigated further the role of EBA in self-other distinctions using low-frequency repetitive transcranial magnetic stimulation (rTMS). As compared with rTMS applied over a control site, rTMS applied over the EBA increased reaction times, without affecting accuracy, for the detection of other-generated movements. Performance on a control motion-direction detection task was unaffected. These findings provide additional evidence for the role of the EBA in processing information necessary for identifying ourselves as agents of self-generated movements.

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 score0.006

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 head0.073
GPT teacher head0.308
Teacher spread0.235 · 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

Citations22
Published2008
Admission routes1
Has abstractyes

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