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Record W2100135473 · doi:10.1027/0269-8803.19.4.281

External Behavior Monitoring Mirrors Internal Behavior Monitoring

2005· article· en· W2100135473 on OpenAlexfundno aff
Alan Bates, Tina Patel, Peter F. Liddle

Bibliographic record

VenueJournal of Psychophysiology · 2005
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAction (physics)ImitationNegativity effectError-related negativityTask (project management)PsychologyMirror neuronKey (lock)NeuroscienceCognitive psychologyComputer scienceCognitionPhysicsAnterior cingulate cortexComputer security

Abstract

fetched live from OpenAlex

Abstract: The discovery of mirror neurons in monkeys has reshaped thinking about how the brain processes observed actions. There is growing evidence that these neurons, which show similar firing patterns for action execution and observation, also exist in humans. Many parts of the motor system required to perform a specific action are activated during the observation of the same action. We hypothesized that behavior monitoring that occurs during action execution is mirrored during action observation. To test this, we measured error negativity/error-related negativity (Ne/ERN) while participants performed and observed a Go/NoGo task. The Ne/ERN is an event-related potential that is thought to reflect an error detection process in the brain. In addition to finding an Ne/ERN for performed errors, we found that an Ne/ERN was also generated for observed errors. The Ne/ERN for observed errors may reflect a system that plays a key role in imitation and observational learning.

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)0.003
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
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)0.0010.000

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 head0.067
GPT teacher head0.395
Teacher spread0.328 · 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

Citations75
Published2005
Admission routes1
Has abstractyes

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