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Record W4286008447 · doi:10.31234/osf.io/v7u3n

The role of PMd in voluntary motor control: insights from TMS research.

2022· preprint· en· W4286008447 on OpenAlexafffund
Ronan Denyer, Ian Greenhouse, Lara A. Boyd

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsTranscranial magnetic stimulationNeuroscienceContext (archaeology)PsychologyCognitionInhibitory postsynaptic potentialTask (project management)EffectorComputer scienceStimulationCognitive psychologyBiologyEngineering

Abstract

fetched live from OpenAlex

Transcranial magnetic stimulation (TMS) research has furthered understanding of human PMd function due to its unrivalled ability to measure the inhibitory and facilitatory influences of PMd over M1 in a temporally precise manner. Findings from TMS research indicate that PMd transiently modulates inhibitory output to effector representations within M1 during motor preparation depending on which effectors are selected for response, and that the timing of these modulations correlates with the cognitive demands of the task. In this review, we critically assess this literature within the context of prevailing theories of PMd function borne out of single/multi unit recording research in non-human primates. Through this process we identify gaps in the literature and propose future experiments to address lingering questions.

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)0.001
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: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.065
GPT teacher head0.331
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

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

Citations3
Published2022
Admission routes2
Has abstractyes

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