Optimization in Manual Aiming: Relating Inherent Variability and Target Size, and Its Influence on Tendency

Roberts, James W.; Elliott, Digby; Burkitt, James J.

doi:10.1080/00222895.2021.2016574

Cited by 1 publication

(6 citation statements)

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“…The present study revisited previous datasets featuring a higher than typical incidence of type 1 submovements (Roberts et al 2016 , 2018 , 2022 ). The classic two-component interpretation of speed-accuracy in manual aiming would have it that these submovements are a manifestation of a correction following an initial error within the limb trajectory (Elliott et al 2001 , 2010 , 2017 ; Woodworth 1899 ).…”

Section: Discussionmentioning

confidence: 56%

“…For full details, see the Method section within Roberts et al ( 2022 ). Participants sat in front of an LCD monitor (47.5 × 27.0 cm; temporal resolution = 60 Hz, spatial resolution = 1280 × 800 pixels) and graphics digitiser (GTCO Calcomp Drawing Board VI), which were each connected to an adjacent computer that controlled the experiment using Matlab (2018b, The Mathworks Inc., Natick, MA) running Psychtoolbox (version 3.0.11).…”

Section: Methodsmentioning

confidence: 99%

“…For the purposes of the present analysis, we focussed solely on the third possible target equating to 86.64% of the spatial distribution (× 3 within-participant SD; ± 1.5), because it generally manifested in the most overshooting (see Fig. 2 A from Roberts et al 2022 ). The target sizes ranged between 6.29 and 14.35 mm across participants.…”

Section: Methodsmentioning

confidence: 99%

“…Taken together, it is of interest to further examine the datasets from our previously mentioned studies; that is, when type 1 submovements tended to dominate (Roberts et al 2016 , 2018 , 2022 ). Specifically, to further examine the function of type 1 submovements, we isolated the incidences of type 1 submovements, and further categorised them as functional and non-functional based on whether the secondary submovement moved the limb closer to the target than the primary submovement (see Khan et al 2006 ; Robinson et al 2014 ).…”

Section: Introductionmentioning

confidence: 98%

“…In this regard, there is an equal distribution of submovements that come from initially undershooting (type 2, type 3) and overshooting (type 1) the target. Alternatively, there is the minimisation model, which states that the primary submovement tends to undershoot the target so as to not completely overturn inertia, and limit the time and energy-expenditure of the subsequent correction with the secondary submovement (type 2, type 3 > type 1) (Elliott et al 2004 ; see also the multiple process model, Elliott et al 2010 , 2017 ; for a theoretical argument attempting to reconcile these two points of view, see Roberts et al 2022 ).…”

Section: Introductionmentioning

confidence: 99%

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The type 1 submovement conundrum: an investigation into the function of velocity zero-crossings within two-component aiming movements

Roberts,

Burkitt,

Elliott

2024

Exp Brain Res

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In rapid manual aiming, traditional wisdom would have it that two components manifest from feedback-based processes, where error accumulated within the primary submovement can be corrected within the secondary submovement courtesy of online sensory feedback. In some aiming contexts, there are more type 1 submovements (overshooting) compared to types 2 and 3 submovements (undershooting), particularly for more rapid movements. These particular submovements have also been attributed to a mechanical artefact involving movement termination and stabilisation. Hence, the goal of our study was to more closely examine the function of type 1 submovements by revisiting some of our previous datasets. We categorised these submovements according to whether the secondary submovement moved the limb closer (functional), or not (non-functional), to the target. Overall, there were both functional and non-functional submovements with a significantly higher proportion for the former. The displacement at the primary and secondary submovements, and negative velocity peak were significantly greater in the functional compared to non-functional. The influence of submovement type on other movement characteristics, including movement time, was somewhat less clear. These findings indicate that the majority of type 1 submovements are related to intended feedforward- and/or feedback-based processes, although there are a portion that can be attributed an indirect manifestation of a mechanical artefact. As a result, we suggest that submovements should be further categorised by their error-reducing function.

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