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Record W2263854435 · doi:10.1123/mcj.16.3.353

Reduced Cortical Motor Potentials Underlie Reductions in Memory-Guided Reaching Performance

2012· article· en· W2263854435 on OpenAlexaff
Olav Krigolson, Jon Bell, Courtney M. Kent, Matthew Heath, Clay B. Holroyd

Bibliographic record

VenueMotor Control · 2012
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsUniversity of VictoriaDalhousie UniversityWestern University
Fundersnot available
KeywordsNeuroscienceMotor cortexPsychologyMovement (music)Physics

Abstract

fetched live from OpenAlex

We used the event-related potential (ERP) methodology to examine differences in neural processing between visually and memory-guided reaches. Consistent with previous findings (e.g., Westwood, Heath, & Roy, 2003), memory-guided reaches undershot veridical target location to a greater extent than their visually guided counterparts. Analysis of the ERP data revealed that memory-guided reaches were associated with reduced potentials over medial-frontal cortex at target presentation and following movement onset. Further, we found that the amplitudes of the potentials over medial-frontal cortex for visually and memory-guided reaches were significantly correlated with the peak accelerations and decelerations of the reaching movements. Our results suggest that memory-guided reaches are mediated by a motor plan that is generated while a target is visible, and then stored in memory until needed--a result counter to recent behavioral theories asserting that memory-guided reaches are planned just before movement onset via a stored, sensory-based target representation.

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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.051
GPT teacher head0.275
Teacher spread0.225 · 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

Citations10
Published2012
Admission routes1
Has abstractyes

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