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Lack of conscious recognition of one’s own actions in a haptically deafferented patient

2002· article· en· W2077905892 on OpenAlexaff
Pierre Fourneret, Jacques Paillard, Y. Lamarre, Jonathan Cole, Marc Jeannerod

Bibliographic record

VenueNeuroreport · 2002
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsProprioceptionPerceptionPsychologyEfferentConsciousnessCognitive psychologyCognitionNeuroscienceSensory systemCommunicationAfferent

Abstract

fetched live from OpenAlex

How do we become aware of our own actions? This classical question is still a matter of debate: does consciousness depend on central efferent signals or derive from peripheral information? In this paper, we had the opportunity to study a haptically deafferented patient using a well-tested experimental paradigm where a cognitive conflict is produced between motor intention, proprioception and visual feedback. Our results show that the patient was able to solve the conflict and to generate accurate movements to a target in the absence of proprioceptive feedback and with very limited visual feedback from her movements. Yet, she could not report any conscious perception of the conflict and showed no conscious knowledge of her actual performance. We suggest that information derived from efferent processes cannot in themselves be a source for conscious experience about our own actions.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.003
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.202
GPT teacher head0.295
Teacher spread0.093 · 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 designCase report
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

Citations78
Published2002
Admission routes1
Has abstractyes

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