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Record W2149421973 · doi:10.1123/mcj.17.3.298

Effect of Visual Feedback on Brain Activation During Motor Tasks: An fMRI Study

2013· article· en· W2149421973 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMotor Control · 2013
Typearticle
Languageen
FieldNeuroscience
TopicEEG and Brain-Computer Interfaces
Canadian institutionsGF Strong Rehabilitation Centre
FundersCanadian Institutes of Health Research
KeywordsVisual feedbackPsychologyPhysical medicine and rehabilitationMotor learningNeuroscienceMotor imageryCognitive psychologyComputer scienceArtificial intelligenceElectroencephalographyBrain–computer interfaceMedicine

Abstract

fetched live from OpenAlex

This study examined the effect of visual feedback and force level on the neural mechanisms responsible for the performance of a motor task. We used a voxel-wise fMRI approach to determine the effect of visual feedback (with and without) during a grip force task at 35% and 70% of maximum voluntary contraction. Two areas (contralateral rostral premotor cortex and putamen) displayed an interaction between force and feedback conditions. When the main effect of feedback condition was analyzed, higher activation when visual feedback was available was found in 22 of the 24 active brain areas, while the two other regions (contralateral lingual gyrus and ipsilateral precuneus) showed greater levels of activity when no visual feedback was available. The results suggest that there is a potentially confounding influence of visual feedback on brain activation during a motor task, and for some regions, this is dependent on the level of force applied.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.107
Threshold uncertainty score0.680

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.010
GPT teacher head0.276
Teacher spread0.266 · 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