Literature DB >> 26979439

The violation of Fitts' Law: an examination of displacement biases and corrective submovements.

James W Roberts1, Jarrod Blinch2, Digby Elliott1,3,4, Romeo Chua2, James L Lyons5,6, Timothy N Welsh7,4.   

Abstract

Fitts' Law holds that, to maintain accuracy, movement times of aiming movements must change as a result of varying degrees of movement difficulty. Recent evidence has emerged that aiming to a target located last in an array of placeholders results in a shorter movement time than would be expected by the Fitts' equation-a violation of Fitts' Law. It has been suggested that the violation emerges because the performer adopts an optimized movement strategy in which they partially pre-plan an action to the closest placeholder (undershoot the last placeholder) and rely on a secondary acceleration to propel the limb toward the last location when it is selected as the target (Glazebrook et al. in Hum Mov Sci 39:163-176, 2015). In the current study, we examine this proposal and further elucidate the processes underlying the violation by examining limb displacement and corrective submovements that occur when performers aim to different target locations. For our Main Study, participants executed discrete aiming movements in a five-placeholder array. We also reanalyzed data from a previously reported study in which participants aimed in placeholder and no-placeholder conditions (Blinch et al. in Exp Brain Res 223:505-515, 2012). The results showed the violation of Fitts' Law unfolded following peak velocity (online control). Further, the analysis showed that movements to the last target tended to overshoot and had a higher proportion of secondary submovements featuring a reversal than other categories of submovement (secondary accelerations, discontinuities). These findings indicate that the violation of Fitts' Law may, in fact, result from a strategic bias toward planning farther initial displacements of the limb which accommodates a shorter time in online control.

Entities:  

Keywords:  Fitts’ Law; Movement optimization; Online control; Pre-planning; Reversal submovements

Mesh:

Year:  2016        PMID: 26979439     DOI: 10.1007/s00221-016-4618-4

Source DB:  PubMed          Journal:  Exp Brain Res        ISSN: 0014-4819            Impact factor:   1.972


  42 in total

1.  INFORMATION CAPACITY OF DISCRETE MOTOR RESPONSES.

Authors:  P M FITTS; J R PETERSON
Journal:  J Exp Psychol       Date:  1964-02

2.  Learning to optimize speed, accuracy, and energy expenditure: a framework for understanding speed-accuracy relations in goal-directed aiming.

Authors:  Digby Elliott; Steven Hansen; Jocelyn Mendoza; Luc Tremblay
Journal:  J Mot Behav       Date:  2004-09       Impact factor: 1.328

3.  Common vs. independent limb control in sequential vertical aiming: The cost of potential errors during extensions and reversals.

Authors:  James W Roberts; Digby Elliott; James L Lyons; Spencer J Hayes; Simon J Bennett
Journal:  Acta Psychol (Amst)       Date:  2015-11-18

4.  Programming strategies for rapid aiming movements under simple and choice reaction time conditions.

Authors:  Michael A Khan; Gavin P Lawrence; Eric Buckolz; Ian M Franks
Journal:  Q J Exp Psychol (Hove)       Date:  2006-03       Impact factor: 2.143

5.  The effect of the Müller-Lyer illusion on the planning and control of manual aiming movements.

Authors:  Jocelyn E Mendoza; Digby Elliott; Daniel V Meegan; James L Lyons; Timothy N Welsh
Journal:  J Exp Psychol Hum Percept Perform       Date:  2006-04       Impact factor: 3.332

6.  Moving farther but faster: an exception to Fitts's law.

Authors:  Jos J Adam; Robin Mol; Jay Pratt; Martin H Fischer
Journal:  Psychol Sci       Date:  2006-09

7.  On the timing of reference frames for action control.

Authors:  Martin H Fischer; Jay Pratt; Jos J Adam
Journal:  Exp Brain Res       Date:  2007-09-08       Impact factor: 1.972

8.  Visual layout modulates Fitts's law: the importance of first and last positions.

Authors:  Jay Pratt; Jos J Adam; Martin H Fischer
Journal:  Psychon Bull Rev       Date:  2007-04

9.  Internal models in the cerebellum.

Authors:  D M Wolpert; R C Miall; M Kawato
Journal:  Trends Cogn Sci       Date:  1998-09-01       Impact factor: 20.229

10.  How one breaks Fitts's Law and gets away with it: Moving further and faster involves more efficient online control.

Authors:  Cheryl M Glazebrook; Dovin Kiernan; Timothy N Welsh; Luc Tremblay
Journal:  Hum Mov Sci       Date:  2014-12-08       Impact factor: 2.161

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  1 in total

1.  Online control of reach accuracy in mice.

Authors:  Matthew I Becker; Dylan J Calame; Julia Wrobel; Abigail L Person
Journal:  J Neurophysiol       Date:  2020-09-30       Impact factor: 2.714

  1 in total

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