Experimental Brain Research

, Volume 191, Issue 2, pp 143–155 | Cite as

The efficacy of colour cues in facilitating adaptation to opposing visuomotor rotations

  • Mark R. Hinder
  • Daniel G. Woolley
  • James R. Tresilian
  • Stephan Riek
  • Richard G. Carson
Research Article

Abstract

We investigated visuomotor adaptation using an isometric, target-acquisition task. Following trials with no rotation, two participant groups were exposed to a random sequence of 30° clockwise (CW) and 60° counter-clockwise (CCW) rotations, with (DUAL-CUE), or without (DUAL-NO CUE), colour cues that enabled each environment (non-rotated, 30° CW and 60° CCW) to be identified. A further three groups experienced only 30° CW trials or only 60° CCW trials (SINGLE rotation groups) in which each visuomotor mapping was again associated with a colour cue. During training, all SINGLE groups reduced angular deviations of the cursor path during the initial portion of the movements, indicating feedforward adaptation. Consistent with the view that the adaptation occurred automatically via recalibration of the visuomotor mapping (Krakauer et al. 1999), post-training aftereffects were observed, despite colour cues that indicated that no rotation was present. For the DUAL-CUE group, angular deviations decreased with training in the 60° trials, but were unchanged in the 30° trials, while for the DUAL-NO CUE group angular deviations decreased for the 60° CW trials but increased for the 30° CW trials. These results suggest that in a dual adaptation paradigm a colour cue can permit delineation of the two environments, with a subsequent change in behaviour resulting in improved performance in at least one of these environments. Increased reaction times within the training block, together with the absence of aftereffects in the post-training period for the DUAL-CUE group suggest an explicit cue-dependent strategy was used in an attempt to compensate for the rotations.

Keywords

Visuomotor rotation Adaptation Internal model Visuomotor mapping Interference Implicit and explicit learning Dual adaptation 

References

  1. Caithness G, Osu R, Bays P, Chase H, Klassen J, Kawato M, Wolpert DM, Flanagan JR (2004) Failure to consolidate the consolidation theory of learning for sensorimotor adaptation tasks. J Neurosci 24:8662–8671PubMedCrossRefGoogle Scholar
  2. Cohen J (1969) Statistical power analysis for the behavioral sciences. Academic Press, New YorkGoogle Scholar
  3. Cunningham HA (1989) Aiming error under transformed spatial mappings suggests a structure for visual-motor maps. J Exp Psychol Hum Percept Perform 15:493–506PubMedCrossRefGoogle Scholar
  4. Diedrichsen J, Hashambhoy Y, Rane T, Shadmehr R (2005) Neural correlates of reach errors. J Neurosci 25:9919–9931PubMedCrossRefGoogle Scholar
  5. Flanagan JR, Rao AK (1995) Trajectory adaptation to a nonlinear visuomotor transformation—evidence of motion planning in visually perceived space. J Neurophysiol 74:2174–2178PubMedGoogle Scholar
  6. Gandolfo F, Mussa-Ivaldi FA, Bizzi E (1996) Motor learning by field approximation. Proc Natl Acad Sci USA 93:3843–3846PubMedCrossRefGoogle Scholar
  7. Ghahramani Z, Wolpert DM (1997) Modular decomposition in visuomotor learning. Nature 286:392–395CrossRefGoogle Scholar
  8. Gupta R, Ashe J (2007) Lack of adaptation to random conflicting force fields of variable magnitude. J Neurophysiol 97:738–745PubMedCrossRefGoogle Scholar
  9. Hinder MR, Walk L, Woolley DG, Riek S, Carson RG (2007) The interference effects of non-rotated versus counter-rotated trials in visuomotor adaptation. Exp Brain Res 180:629–640PubMedCrossRefGoogle Scholar
  10. Hinder MR, Tresilian JR, Riek S, Carson RG (2008) The contribution of visual feedback to visuomotor adaptation: How much and when? Brain Res 1197:123–134PubMedCrossRefGoogle Scholar
  11. Kawato M (1999) Internal models for motor control and trajectory planning. Curr Opin Neurobiol 9:718–727PubMedCrossRefGoogle Scholar
  12. Keppel G (1982) Design and analysis: a researcher’s handbook, 2nd edn. Prentice-Hill, New JerseyGoogle Scholar
  13. Krakauer JW, Ghilardi MF, Ghez C (1999) Independent learning of internal models for kinematic and dynamic control of reaching. Nat Neurosci 2:1026–1031PubMedCrossRefGoogle Scholar
  14. Krouchev N, Kalaska J (2003) Context-dependent anticipation of different task dynamics: rapid recall of appropriate motor skills using visual cues. J Neurophysiol 89:1165–1175PubMedCrossRefGoogle Scholar
  15. Mazzoni P, Krakauer JW (2006) An implicit plan overrides an explicit strategy during visuomotor adaptation. J Neurosci 26:3642–3645PubMedCrossRefGoogle Scholar
  16. Miall RC, Jenkinson N, Kulkarni K (2004) Adaptation to rotated visual feedback: a re-examination of motor interference. Exp Brain Res 154:201–210PubMedCrossRefGoogle Scholar
  17. Osu R, Hirai S, Yoshioka T, Kawato M (2004) Random presentation enables subjects to adapt to two opposing forces on the hand. Nat Neurosci 7:111–112PubMedCrossRefGoogle Scholar
  18. Pellegrini JJ, Flanders M (1996) Force path curvature and conserved features of muscle activation. Exp Brain Res 110:80–90PubMedCrossRefGoogle Scholar
  19. Scheidt RA, Dingwell JB, Mussa-Ivaldi FA (2001) Learning to move amid uncertainty. J Neurophysiol 86:971–985PubMedGoogle Scholar
  20. Shadmehr R, Mussa-Ivaldi FA (1994) Adaptive representation of dynamics during learning of a motor task. J Neurosci 14:3208–3224PubMedGoogle Scholar
  21. Teasdale N, Bard C, Fleury M, Young DE, Proteau L (1993) Determining movement onsets from time series. J Motor Behav 25:97–106Google Scholar
  22. Tong C, Wolpert DM, Flanagan JR (2002) Kinematics and dynamics are not represented independently in motor working memory: evidence from an interference study. J Neurosci 22:1108–1113PubMedGoogle Scholar
  23. Wada Y, Kawabata Y, Kotosaka S, Yamamoto K, Kitazawa S, Kawato M (2003) Acquisition and contextual switching of multiple internal models for different viscous force fields. Neurosci Res 46:319–331PubMedCrossRefGoogle Scholar
  24. Wainscott SK, Donchin O, Shadmehr R (2005) Internal models and contextual cues: encoding serial order and direction of movement. J Neurophysiol 93:786–800PubMedCrossRefGoogle Scholar
  25. Wigmore V, Tong C, Flanagan JR (2002) Visuomotor rotations of varying size and direction compete for a single internal model in motor working memory. J Exp Psychol Hum Percept Perform 28:447–457PubMedCrossRefGoogle Scholar
  26. Wolpert DM, Ghahramani Z, Jordan MI (1995) An internal model for sensorimotor integration. Science 269:1880–1882PubMedCrossRefGoogle Scholar
  27. Woolley DG, Tresilian JR, Carson RG, Riek S (2007) Dual adaptation to two opposing visuomotor rotations when each is associated with different regions of workspace. Exp Brain Res 179:155–165PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  • Mark R. Hinder
    • 1
    • 2
  • Daniel G. Woolley
    • 1
    • 3
  • James R. Tresilian
    • 1
    • 4
  • Stephan Riek
    • 1
  • Richard G. Carson
    • 1
    • 5
  1. 1.Perception and Motor Systems Laboratory, School of Human Movement StudiesUniversity of QueenslandBrisbaneAustralia
  2. 2.School of PsychologyUniversity of TasmaniaHobartAustralia
  3. 3.Motor Control Laboratory, Research Centre for Movement Control and Neuroplasticity, Department of Biomedical KinesiologyKatholieke Universiteit LeuvenLeuvenBelgium
  4. 4.Department of PsychologyUniversity of WarwickCoventryUK
  5. 5.School of PsychologyQueen’s University of BelfastBelfastNorthern Ireland, UK

Personalised recommendations