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Active Braking of Whole-Arm Reaching Movements Provides Single-Trial Neuromuscular Measures of Movement Cancellation

2018· article· en· W2797790466 on OpenAlexafffund
Jeroen Atsma, Femke Maij, Chao Gu, W. Pieter Medendorp, Brian D. Corneil

Bibliographic record

VenueJournal of Neuroscience · 2018
Typearticle
Languageen
FieldNeuroscience
TopicEEG and Brain-Computer Interfaces
Canadian institutionsRobarts Clinical TrialsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaNederlandse Organisatie voor Wetenschappelijk Onderzoek
KeywordsStop signalMovement (music)AntagonistSIGNAL (programming language)Physical medicine and rehabilitationPsychologyNeuroscienceComputer scienceMedicinePhysics

Abstract

fetched live from OpenAlex

Movement inhibition is an aspect of executive control that can be studied using the countermanding paradigm, wherein subjects try to cancel an impending movement following presentation of a stop signal. This paradigm permits estimation of the stop-signal reaction time or the time needed to respond to the stop signal. Numerous countermanding studies have examined fast, ballistic movements, such as saccades, even though many movements in daily life are not ballistic and can be stopped at any point during their trajectory. A benefit of studying the control of nonballistic movements is that antagonist muscle recruitment, which serves to actively brake a movement, presumably arises in response to the stop signal. Here, nine human participants (2 female) performed a center-out whole-arm reaching task with a countermanding component, while we recorded the activity of upper-limb muscles contributing to movement generation and braking. The data show a clear response on antagonist muscles to a stop signal, even for movements that have barely begun. As predicted, the timing of such antagonist recruitment relative to the stop signal covaried with conventional estimates of the stop-signal reaction time, both within and across subjects. The timing of antagonist muscle recruitment also attested to a rapid reprioritization of movement inhibition, with antagonist latencies decreasing across sequences consisting of repeated stop trials; such reprioritization also scaled with error magnitude. We conclude that antagonist muscle recruitment arises as a manifestation of a stopping process, providing a novel, accessible, and within-trial measure of the stop-signal reaction time. SIGNIFICANCE STATEMENT The countermanding or stop-signal paradigm permits estimation of how quickly subjects cancel an impending movement. Traditionally, this paradigm has been studied using simple movements, such as saccadic eye movements or button presses. Here, by measuring upper limb muscle activity while human subjects countermand whole-arm reaching movements, we show that movement cancellation often involves prominent recruitment of antagonist muscles that serves to actively brake the movement, even on movements that have barely begun. The timing of antagonist muscle recruitment correlates with traditional estimates of movement cancellation. Because they can be detected on a single-trial basis, muscle-based measures may provide a new way of characterizing movement cancellation at an unprecedented within-trial resolution.

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 head0.092
GPT teacher head0.310
Teacher spread0.218 · 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

Citations60
Published2018
Admission routes2
Has abstractyes

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