Experimental Brain Research

, Volume 181, Issue 2, pp 249–265 | Cite as

Learning new perception–action solutions in virtual ball bouncing

  • Antoine H. P. Morice
  • Isabelle A. Siegler
  • Benoît G. Bardy
  • William H. Warren
Research Article

Abstract

How do humans discover stable solutions to perceptual-motor tasks as they interact with the physical environment? We investigate this question using the task of rhythmically bouncing a ball on a racket, for which a passively stable solution is defined. Previously, it was shown that participants exploit this passive stability but can also actively stabilize bouncing under perceptual control. Using a virtual ball-bouncing display, we created new behavioral solutions for rhythmic bouncing by introducing a temporal delay (45°–180°) between the motion of the physical racket and that of the virtual racket. We then studied how participants searched for and realized a new solution. In all delay conditions, participants learned to maintain bouncing just outside the passively stable region, indicating a role for active stabilization. They recovered the approximate initial phase of ball impact in the virtual racket cycle (half-way through the upswing) by adjusting the impact phase with the physical racket. With short delays (45°, 90°), the impact phase quickly shifted later in the physical racket upswing. With long delays (135°, 180°), bouncing was destabilized and phase was widely visited before a new preferred phase gradually emerged, during the physical downswing. Destabilization was likely due to the loss of spatial symmetry between the ball and physical racket motion at impact. The results suggest that new behavioral solutions may be discovered and stabilized through broad irregular sampling of variable space rather than through a systematic search.

Keywords

Bouncing ball Virtual reality Intermodal perception End-to-end latency Dynamical regimes 

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Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  • Antoine H. P. Morice
    • 1
  • Isabelle A. Siegler
    • 1
  • Benoît G. Bardy
    • 2
    • 3
  • William H. Warren
    • 4
  1. 1.UPRES EA 4042 Contrôle Moteur et PerceptionOrsay CedexFrance
  2. 2.Institut Universitaire de FranceParisFrance
  3. 3.Motor Efficiency and Deficiency LaboratoryUniversity Montpellier-1MontpellierFrance
  4. 4.Department of Cognitive and Linguistic SciencesBrown UniversityProvidenceUSA

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