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Record W4312209355 · doi:10.1101/2022.12.22.521654

Motor adaptation does not differ when a perturbation is introduced abruptly or gradually

2022· preprint· en· W4312209355 on OpenAlexaff
Ambika Bansal, Bernard Marius ’t Hart, Udai Chauhan, Thomas Eggert, Andreas Straube, Denise Y. P. Henriques

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsYork University
Fundersnot available
KeywordsPsychologyAtaxiaMotor learningAdaptation (eye)Physical medicine and rehabilitationPerturbation (astronomy)Cognitive psychologyMotor skillMotor systemRehabilitationAudiologyDevelopmental psychologyNeurosciencePhysicsMedicine

Abstract

fetched live from OpenAlex

ABSTRACT People continuously adapt their movements to ever-changing circumstances, and particularly in skills training and rehabilitation, it is crucial that we understand how to optimize implicit adaptation in order for these processes to require as little conscious effort as possible. Although it is generally assumed that the way to do this is by introducing perturbations gradually, the literature is ambivalent on the effectiveness of this approach. Here we test whether there are differences in motor performance when adapting to an abrupt compared to a ramped visuomotor rotation. Using a within-subjects design, we test this question under 3 different rotation sizes: 30°, 45°, and 60°, as well as in 3 different populations: younger adults, older adults, and patients with mild cerebellar ataxia. We find no significant differences in either the behavioural outcomes, or model fits, between abrupt and gradual learning across any of the different conditions. Neither age, nor cerebellar ataxia had any significant effect on motor adaptation either. These findings together indicate that motor adaptation is not modulated by introducing a perturbation abruptly compared to gradually, and is also unaffected by age or mild cerebellar ataxia.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0020.000

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 head0.035
GPT teacher head0.235
Teacher spread0.201 · 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 designBench or experimental
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

Citations2
Published2022
Admission routes1
Has abstractyes

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