Advertisement

Experimental Brain Research

, Volume 237, Issue 1, pp 273–287 | Cite as

Solo versus joint bimanual coordination

  • Peter DixonEmail author
  • Scott Glover
Research Article

Abstract

Understanding the differences between solo and joint action control is an important goal in psychology. The present study represented a novel approach in which participants performed a bimanual finger oscillation task, either alone or in pairs. It was hypothesized that performance of this task relies heavily on attention and utilizes two independent processes that differentially affect solo and joint performance. One process attempts to align the fingers correctly regardless of oscillation speed, and this is reflected in an alignment error evident even at slow oscillations. A second process attempts to minimize the time lag between the fingers as the oscillation speed increases, reflected in a temporal error indexed by the rate of error increase with increasing movement speed. In three experiments, alignment and temporal error in the finger oscillation task were compared in solo and joint actors. Overall, solo actors had much lower alignment error than joint actors. Solo actors also showed a reduction in temporal error when the fingers moved in a symmetrical rather than parallel fashion, consistent with previous research showing an increase in error with increasing movement speed. However, the effect of symmetry on temporal error did not occur with joint actors. Similar results were found with one hand inverted, suggesting that the pattern of results was not due to the use of homologous muscles. To test the role of visual feedback, we examined the effect of denying visual feedback to one of the actors in the joint condition. Paradoxically, under these conditions, there was lower temporal error in the symmetrical condition. These results are interpreted in terms of the organization of solo versus joint actions and the control of bimanual tasks in general.

Keywords

Motor control Joint action Attention Bimanual 

Notes

Acknowledgements

This research was supported by a Grant to the first author from the Natural Sciences and Engineering Research Council of Canada.

References

  1. Akaike H (1973) Information theory and an extension of the maximum likelihood principle. In: Petrove BN, Csaki F (eds) Second international symposium on information theory. Academiai Kiado, Budapest, pp 267–281Google Scholar
  2. Atmaca S, Sebanz N, Prinz W, Knoblich G (2008) Action co-representation: the joint SNARC effect. Soc Neurosci 3:410–420CrossRefGoogle Scholar
  3. Bingham GP (2004) A perceptually-driven dynamical model of bimanual rhythmic movement (and phase perception). Ecol Psychol 16:45–53CrossRefGoogle Scholar
  4. Burnham KP, Anderson DR (2002) Model selection and multi-model inference: a practical information-theoretic approach. Springer, New YorkGoogle Scholar
  5. Camponogara I, Rodger M, Craig C, Cesari P (2017) Expert players accurately detect an opponent’s movement intentions through sound alone. J Exp Psychol Hum Percept Perform 43:348–359CrossRefGoogle Scholar
  6. Carson RG (1996) Neuromuscular-skeletal constraints upon the dynamics of perception–action coupling. Exp Brain Res 110:99–110CrossRefGoogle Scholar
  7. Cattaert D, Semjen A, Summers JJ (1999) Simulating a neural cross-talk model for between-hand interference during bimanual circle drawing. Biol Cybern 81:343–358CrossRefGoogle Scholar
  8. Fine JM, Amazeen EL (2011) Interpersonal Fitts’ Law: when two perform as one. Exp Brain Res 211:459–469CrossRefGoogle Scholar
  9. Fitts PM (1954) The information capacity of the human motor system in controlling the amplitude of movement. J Exp Psychol 47:381–391CrossRefGoogle Scholar
  10. Glover S, Dixon P (2004) Likelihood ratios: a simple, intuitive statistic for empirical psychologists. Psychonom Bull Rev 11:791–806CrossRefGoogle Scholar
  11. Glover S, Dixon P (2017) The role of predictability in cooperative and competitive joint action. J Exp Psychol Hum Percept Perform 43:644–650CrossRefGoogle Scholar
  12. Glowinski D, Mancini M, Cowie R, Camurri A, Chiorri C, Doherty C (2013) The movements made by performers in a skilled quartet: a distinctive pattern and the function it serves. Front Psychol 4:841CrossRefGoogle Scholar
  13. Kelso JAS (1981) On the oscillatory nature of movement. Bull Psychonom Soc 18:63Google Scholar
  14. Kelso JAS (1984) Phase transitions and critical behavior in human bimanual coordination. Am J Physiol Regul Integr Comp Physiol 15:1000–1004CrossRefGoogle Scholar
  15. Khoramshahi M, Shukla A, Raffard S, Bardy BG, Billard A (2016) Role of gaze cues in interpersonal motor coordination: towards higher affiliation in human–robot interaction. PLoS One.  https://doi.org/10.1371/journal.pone.0156874 Google Scholar
  16. Kourtis Z, Sebanz N, Knoblich G (2013) Predictive representation of other people’s actions in joint action planning: an EEG study. Soc Neurosci 8:31–42CrossRefGoogle Scholar
  17. Kovacs AJ, Shea CH (2010) Amplitude differences, spatial assimilation, and integrated feedback in bimanual coordination. Exp Brain Res 202:519–525CrossRefGoogle Scholar
  18. Kovacs AJ, Buchanan JJ, Shea CH (2009a). Bimanual 1:1 with 90° continuous phase: difficult or easy? Exp Brain Res 193:129–136.CrossRefGoogle Scholar
  19. Lee TD, Swinnen SP, Verschueren S (1995) Relative phase alterations during bimanual skill acquisition. J Mot Behav 27:263–274CrossRefGoogle Scholar
  20. Marteniuk RG, MacKenzie CL, Baba DM (1984) Bimanual movement control: information processing and interaction effects. Q J Exp Psychol 36:335–365CrossRefGoogle Scholar
  21. Mechsner F, Knoblich G (2004) Do muscles matter for coordinated action? J Exp Psychol Hum Percept Perform 30:490–503CrossRefGoogle Scholar
  22. Mechsner F, Kerzel D, Knoblich G, Prinz W (2001) Perceptual basis of bimanual coordination. Nature 414:69–73CrossRefGoogle Scholar
  23. Meulenbroek R, Bosga J, Hulstijn M, Miedl S (2007) Joint–action coordination in transferring objects. Exp Brain Res 180:333–343CrossRefGoogle Scholar
  24. Posner MI, Snyder CR, Davidson BJ (1980) Attention and the detection of signals. J Exp Psychol Hum Percept Perform 109:160–174Google Scholar
  25. Riek S, Carson RG, Byblow WD (1992) Spatial and muscular dependencies in bimanual coordination. J Hum Mov Sci 23:251–265Google Scholar
  26. Schmidt RC, Carello C, Turvey MT (1990) Phase transitions and critical fluctuations in the visual coordination of rhythmic movement between people. J Exp Psychol Hum Percept Perform 16:227–247CrossRefGoogle Scholar
  27. Scholz JP, Kelso JAS (1989) A quantitative approach to understanding the formation and change of coordinated movement patterns. J Mot Behav 21:122–144CrossRefGoogle Scholar
  28. Sebanz N, Knoblich G, Prinz W (2003) Representing others’ actions: just like our own? Cognition 88:B11–B21CrossRefGoogle Scholar
  29. Sebanz N, Knoblich G, Prinz W (2005) How two share a task: corepresenting stimulus-response mappings. J Exp Psychol Hum Percept Perform 31:1234–1246CrossRefGoogle Scholar
  30. Sebanz N, Bekkering H, Knoblich G (2006) Joint actions: bodies and minds moving together. Trends Cogn Sci 10:70–76CrossRefGoogle Scholar
  31. Spencer RM, Ivry RB (2007) The temporal representation of in-phase and anti-phase movements. Hum Mov Sci 26:226–240CrossRefGoogle Scholar
  32. Swinnen SP (2002) Intermanual coordination: from behavioural principles to neural-network interactions. Nat Rev Neurosci 3:348–359CrossRefGoogle Scholar
  33. Swinnen SP, Dounskaia N, Verschueren S, Serrien DJ, Daelman A (1995) Relative phase destabilization during interlimb coordination: the disruptive role of kinesthetic afferences induced by passive movements. Exp Brain Res 3:439–454Google Scholar
  34. Swinnen SP, Jardin K, Meulenbroek R, Dounskaia N, Den Brandt MH (1997a) Egocentric and allocentric constraints in the expression of patterns of interlimb coordination. J Cogn Neurosci 9:348–377CrossRefGoogle Scholar
  35. Swinnen SP, Lee TD, Verschueren S, Serrien DJ, Bogaerts DJ (1997b) Interlimb coordination: learning and transfer under different feedback conditions. Hum Mov Sci 16:749–785CrossRefGoogle Scholar
  36. Swinnen SP, Jardin K, Verschueren S, Meulenbroek R, Franz L, Dounskaia N, Walter CB (1998) Exploring interlimb constraints during bimanual graphic performance: effects of muscle grouping and direction. Behav Brain Res 90:79–87CrossRefGoogle Scholar
  37. Temprado JJ, Zanone PG, Monno A, Laurent M (1999) Attentional load associated with performing and stabilizing preferred bimanual patterns. J Exp Psychol Hum Percept Perform 25:1579–1594CrossRefGoogle Scholar
  38. Vesper C, van der Wel RP, Knoblich G, Sebanz N (2011) Making oneself predictable: reduced temporal variability facilitates joint action coordination. Exp Brain Res 211:517–530CrossRefGoogle Scholar
  39. Vesper C, Knoblich G, Sebanz N (2014) Our actions in my mind: motor imagery of joint action. Neuropsychologia 55:115–121CrossRefGoogle Scholar
  40. Vesper C, Schmitz L, Safra L, Sebanz N, Knoblich G (2016) The role of shared visual information for joint action coordination. Cognition 153:118–123CrossRefGoogle Scholar
  41. Wilson AD, Collins DR, Bingham GP (2005) Human movement coordination implicates relative direction as the information for relative phase. Exp Brain Res 165:351–361CrossRefGoogle Scholar
  42. Wolpert DM, Ghahramani Z (2000) Computational principles of movement neuroscience. Nat Rev Neurosci Suppl 3:1212–1217CrossRefGoogle Scholar
  43. Wolpert DM, Doya K, Kawato M (2003) A unifying computational framework for motor control and social interaction. Philos Trans R Soc B Biol Sci 358(1431):593–602CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of PsychologyUniversity of AlbertaEdmontonCanada
  2. 2.Royal Holloway University of LondonEghamUK

Personalised recommendations