Evidence map›Paper›PMID 29465326›Full record

ArticleJournal of neurophysiology2018

Corrective response times in a coordinated eye-head-arm countermanding task.

Gordon Tao, Aarlenne Z Khan, Gunnar Blohm

Abstract read
In one paragraph

Article in Journal of neurophysiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Gordon TaoCentre for Neuroscience Studies, Queen's University , Kingston, Ontario , Canada.
Aarlenne Z KhanCanadian Action and Perception Network (CAPnet).
Gunnar BlohmCentre for Neuroscience Studies, Queen's University , Kingston, Ontario , Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inhibition of motor responses has been described as a race between two competing decision processes of motor initiation and inhibition, which manifest as the reaction time (RT) and the stop signal reaction time (SSRT); in the case where motor initiation wins out over inhibition, an erroneous movement occurs that usually needs to be corrected, leading to corrective response times (CRTs). Here we used a combined eye-head-arm movement countermanding task to investigate the mechanisms governing multiple effector coordination and the timing of corrective responses. We found a high degree of correlation between effector response times for RT, SSRT, and CRT, suggesting that decision processes are strongly dependent across effectors. To gain further insight into the mechanisms underlying CRTs, we tested multiple models to describe the distribution of RTs, SSRTs, and CRTs. The best-ranked model (according to 3 information criteria) extends the LATER race model governing RTs and SSRTs, whereby a second motor initiation process triggers the corrective response (CRT) only after the inhibition process completes in an expedited fashion. Our model suggests that the neural processing underpinning a failed decision has a residual effect on subsequent actions. NEW & NOTEWORTHY Failure to inhibit erroneous movements typically results in corrective movements. For coordinated eye-head-hand movements we show that corrective movements are only initiated after the erroneous movement cancellation signal has reached a decision threshold in an accelerated fashion.

Indexed as

Head MovementsPsychomotor PerformanceSaccadesAdultArmFemaleHumansMaleModels, NeurologicalReaction Timedecision makingerror correctionLATER modelpointingsaccade

Identifiers

PMID29465326
PMCPMC6032126

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.