Advertisement

Integration of vestibular and proprioceptive signals for spatial updating

  • Ilja FrissenEmail author
  • Jennifer L. CamposEmail author
  • Jan L. Souman
  • Marc O. Ernst
Research Article

Abstract

Spatial updating during self-motion typically involves the appropriate integration of both visual and non-visual cues, including vestibular and proprioceptive information. Here, we investigated how human observers combine these two non-visual cues during full-stride curvilinear walking. To obtain a continuous, real-time estimate of perceived position, observers were asked to continuously point toward a previously viewed target in the absence of vision. They did so while moving on a large circular treadmill under various movement conditions. Two conditions were designed to evaluate spatial updating when information was largely limited to either proprioceptive information (walking in place) or vestibular information (passive movement). A third condition evaluated updating when both sources of information were available (walking through space) and were either congruent or in conflict. During both the passive movement condition and while walking through space, the pattern of pointing behavior demonstrated evidence of accurate egocentric updating. In contrast, when walking in place, perceived self-motion was underestimated and participants always adjusted the pointer at a constant rate, irrespective of changes in the rate at which the participant moved relative to the target. The results are discussed in relation to the maximum likelihood estimation model of sensory integration. They show that when the two cues were congruent, estimates were combined, such that the variance of the adjustments was generally reduced. Results also suggest that when conflicts were introduced between the vestibular and proprioceptive cues, spatial updating was based on a weighted average of the two inputs.

Keywords

Multisensory integration Locomotion Vestibular Proprioceptive Spatial updating Maximum likelihood estimation 

Notes

Acknowledgments

The first two authors contributed equally to this work. We thank Michael Weyel for technical assistance and Dr John Butler for valuable advice on the data analysis. We also thank Dr Jack Loomis for earlier valuable discussions and insights. We gratefully acknowledge the work done by the mechanical and electrical workshops of the Max Planck Institute for Biological Cybernetics in adapting the CTM and making it operational. This work was funded by the European 6th Framework Programme CyberWalk (FP6-511092). The writing of this paper by the first author was partially supported by a NSERC grant attributed to Catherine Guastavino (McGill University).

References

  1. Alais D, Burr D (2004) The ventriloquist effect results from near-optimal bimodal integration. Curr Biol 14:257–262PubMedGoogle Scholar
  2. Alton F, Baldey L, Caplan S, Morrisey MC (1998) A kinematic comparison between overground and treadmill walking. Clin Biomech 13:434–440CrossRefGoogle Scholar
  3. Andre J, Rogers S (2006) Using verbal and blind-walking distance estimates to investigate the two visual systems hypothesis. Percept Psychophys 68:353–361PubMedCrossRefGoogle Scholar
  4. Angelaki DE, Cullen KE (2008) Vestibular system: the many facets of a multimodal sense. Annu Rev Neurosci 31:125–150PubMedCrossRefGoogle Scholar
  5. Angelaki DE, Gu Y, DeAngelis GC (2009) Multisensory integration: psychophysics, neurophysiology, and computation. Curr Opin Neurobiol 19:452–458PubMedCrossRefGoogle Scholar
  6. Bakker NH, Werkoven PJ, Passenier PO (1999) The effects of proprioceptive and visual feedback on geographical orientation in virtual environments. Presence-Teleop Virt 8:36–53CrossRefGoogle Scholar
  7. Becker W, Nasios G, Raab S, Jürgens R (2002) Fusion of vestibular and podokinesthetic information during self-turning towards instructed targets. Exp Brain Res 144:458–474PubMedCrossRefGoogle Scholar
  8. Bentvelzen A, Leung J, Alais D (2009) Discriminating audiovisual speed: optimal integration of speed defaults to probability summation when component reliabilities diverge. Perception 38:966–987PubMedCrossRefGoogle Scholar
  9. Berthoz A, Israël I, Georges-François P, Grasso R, Tsuzuku T (1995) Spatial memory of body linear displacement: what is being stored? Science 269:95–98PubMedCrossRefGoogle Scholar
  10. Bles W (1981) Stepping around: circular vection and Coriolis effects. In: Long J, Baddeley A (eds) Attention and performance IX. Erlbaum, Hillsdale, NJGoogle Scholar
  11. Bles W, de Wit G (1978) La sensation de rotation et la march circulaire [sensation of rotation and circular walking]. Aggressologie 19(A):29–30Google Scholar
  12. Bruggeman H, Piuneu VS, Rieser JJ, Pick HL Jr (2009) Biomechanical versus inertial information: stable individual differences in perception of self-rotation. J Exp Psychol Hum Percept Perform 35:1472–1480PubMedCrossRefGoogle Scholar
  13. Bülthoff HH, Yuille AL (1996) A Bayesian framework for the integration of visual modules. In: McClelland J, Inui T (eds) Attention and performance XVI: information integration in perception and communication. MIT Press, CambridgeGoogle Scholar
  14. Butler JS, Smith ST, Campos JL, Bülthoff HH (2010) Bayesian integration of visual and vestibular signals for heading. J Vis 10(11): Article 23. doi: 10.1167/10.11.23
  15. Campos JL, Bülthoff HH (in press) Multisensory integration during self-motion in virtual reality. In: Wallace M, Murray M (eds) Frontiers in the neural bases of multisensory processes, Taylor and FrancisGoogle Scholar
  16. Campos JL, Siegle JH, Mohler BJ, Bülthoff HH, Loomis JM (2009) Imagined self-motion differs from perceived self-motion: evidence from a novel continuous pointing method. PLoS ONE 4:e7793. doi: 10.1371/journal.pone.0007793 PubMedCrossRefGoogle Scholar
  17. Campos JL, Byrne P, Sun H-J (2010) Body-based cues trump vision when estimating walked distance. Eur J Neurosci 31:1889–1898PubMedCrossRefGoogle Scholar
  18. Cheng K, Shettleworth SJ, Huttenlocher J, Rieser JJ (2007) Bayesian integration of spatial information. Psychol Bull 133:625–637PubMedCrossRefGoogle Scholar
  19. Durgin FH, Mikio A, Gallistel CR, Haiken W (2009) The precision of locomotor odometry in humans. Exp Brain Res 193:429–436PubMedCrossRefGoogle Scholar
  20. Ellard CG, Shaughnessy SC (2003) A comparison of visual and non-visual sensory inputs to walked distance in a blind-walking task. Perception 32:567–578PubMedCrossRefGoogle Scholar
  21. Elliott D (1986) Continuous visual information may be important after all: a failure to replicate Thomson. J Exp Psychol Hum Percept Perform 12:388–391PubMedCrossRefGoogle Scholar
  22. Ernst MO, Banks MS (2002) Humans integrate visual and haptic information in a statistically optimal fashion. Nature 415:429–433PubMedCrossRefGoogle Scholar
  23. Ernst MO, Bülthoff HH (2004) Merging the senses into a robust percept. Trends Cogn Sci 8:162–169PubMedCrossRefGoogle Scholar
  24. Faisal AA, Wolpert DM (2009) Near optimal combination of sensory and motor uncertainty in time during a naturalistic perception-action task. J Neurophysiol 101:1901–1912PubMedCrossRefGoogle Scholar
  25. Fetsch CR, Turner AH, DeAngelis GC, Angelaki DE (2009) Dynamic reweighting of visual and vestibular cues during self-motion perception. J Neurosci 29:15601–15612PubMedCrossRefGoogle Scholar
  26. Fukusima SS, Loomis JM, Da Silva JA (1997) Visual perception of egocentric distance as assessed by triangulation. J Exp Psychol Hum Percept Perform 23:86–100PubMedCrossRefGoogle Scholar
  27. Gepshtein S, Burge J, Ernst MO, Banks MS (2005) The combination of vision and touch depends on spatial proximity. J Vis 5(11): Article 7. doi: 10.1167/5.11.7
  28. Glasauer S, Amorim MA, Vitte E, Berthoz A (1994) Goal-directed linear locomotion in normal and labyrinthine-defective subjects. Exp Brain Res 98:323–335PubMedCrossRefGoogle Scholar
  29. Glasauer S, Amorim MA, Viaud-Delmon I, Berthoz A (2002) Differential effects of labyrinthine dysfunction on distance and direction during blindfolded walking of a triangular path. Exp Brain Res 145:489–497PubMedCrossRefGoogle Scholar
  30. Harris LR, Jenkin M, Zikovitz DC (2000) Visual and non-visual cues in the perception of linear self-motion. Exp Brain Res 135:12–21PubMedCrossRefGoogle Scholar
  31. Israël I, Berthoz A (1989) Contribution of the otoliths to the calculation of linear displacement. J Neurophysiol 62:247–263PubMedGoogle Scholar
  32. Israël I, Grasso R, Georges-Francois P, Tsuzuku T, Berthoz A (1997) Spatial memory and path integration studied by self-driven passive linear displacement. I. Basic properties. J Neurophysiol 77:3180–3192PubMedGoogle Scholar
  33. Jacobs RA (1999) Optimal integration of texture and motion cues to depth. Vis Res 39:3621–3629PubMedCrossRefGoogle Scholar
  34. Jürgens R, Becker W (2006) Perception of angular displacement without landmarks: evidence for Bayesian fusion of vestibular, optokinetic, podokinesthetic and cognitive information. Exp Brain Res 174:528–543PubMedCrossRefGoogle Scholar
  35. Knill DC, Saunders JA (2003) Do humans optimally integrate stereo and texture information for judgments of surface slant? Vis Res 43:2539–2558PubMedCrossRefGoogle Scholar
  36. Körding KP, Wolpert DM (2004) Bayesian integration in sensorimotor learning. Nature 427:244–247PubMedCrossRefGoogle Scholar
  37. Kunz BR, Creem-Regehr SH, Thompson WB (2009) Evidence for motor simulation in imagined locomotion. J Exp Psychol Hum Percept Perform 35:1458–1471PubMedCrossRefGoogle Scholar
  38. Lackner JR, DiZio P (2005) Vestibular, proprioceptive, and haptic contributions to spatial orientation. Annu Rev Psychol 56:115–147PubMedCrossRefGoogle Scholar
  39. Loomis JM, Philbeck JW (2008) Measuring perception with spatial updating and action. In: Klatzky RL, Behrmann M, MacWhinney B (eds) Embodiment, egospace and action. Erlbaum, Mahwah, NJGoogle Scholar
  40. Loomis JM, DaSilva JA, Fujita N, Fukusima SS (1992) Visual space-perception and visually-directed action. J Exp Psychol Hum Percept Perform 18:906–921PubMedCrossRefGoogle Scholar
  41. MacNeilage PR, Banks MS, Berger DR, Bülthoff HH (2007) A Bayesian model of the disambiguation of gravitoinertial force by visual cues. Exp Brain Res 179:263–290PubMedCrossRefGoogle Scholar
  42. Marlinsky VV (1999) Vestibular and vestibule-proprioceptive perception of motion in the horizontal plane in blindfolded man: I. Estimations of linear displacement. Neuroscience 90:389–394PubMedCrossRefGoogle Scholar
  43. Mittelstaedt ML, Mittelstaedt H (2001) Idiothetic navigation in humans: estimation of path length. Exp Brain Res 139:318–332PubMedCrossRefGoogle Scholar
  44. Nardini M, Jones P, Bedford R, Braddick O (2008) Development of cue integration in human navigation. Curr Biol 18:689–693PubMedCrossRefGoogle Scholar
  45. Rieser JJ, Ashmead DH, Talor CR, Youngquist GA (1990) Visual perception and the guidance of locomotion without vision to previously seen targets. Perception 19:675–689PubMedCrossRefGoogle Scholar
  46. Rieser JJ, Pick HL Jr, Ashmead DH, Garing AE (1995) Calibration of human locomotion and models of perceptual-motor organization. J Exp Psychol Hum Percept Perform 21:480–497PubMedCrossRefGoogle Scholar
  47. Riley PO, Paolini G, Della Croce U, Paylo KW, Kerrigan DC (2007) A kinematic and kinetic comparison of overground and treadmill walking in healthy subjects. Gait Posture 26:17–24PubMedCrossRefGoogle Scholar
  48. Siegle JH, Campos JL, Mohler BJ, Loomis JM, Bülthoff HH (2009) Measurement of instantaneous perceived self-motion using continuous pointing. Exp Brain Res 195:429–444PubMedCrossRefGoogle Scholar
  49. Souman JL, Frissen I, Sreenivasa MN, Ernst MO (2009) Walking straight into circles. Curr Biol 19:1538–1542PubMedCrossRefGoogle Scholar
  50. Sperry RW (1950) Neural basis of the spontaneous optokinetic response produced by visual inversion. J Comp Physiol Psychol 43:482–489PubMedCrossRefGoogle Scholar
  51. Steenhuis RE, Goodale MA (1988) The effects of time and distance on accuracy of target-directed locomotion: does an accurate short-term memory for spatial location exist? J Mot Behav 20:399–415PubMedGoogle Scholar
  52. Sun H-J, Lee AJ, Campos JL, Chan GSW, Zhang DH (2003) Multisensory integration in speed estimation during self-motion. Cyberpsychol Behav 6:509–518PubMedCrossRefGoogle Scholar
  53. Sun H-J, Campos JL, Chan GSW (2004a) Multisensory integration in the estimation of relative path length. Exp Brain Res 154:246–254PubMedCrossRefGoogle Scholar
  54. Sun H-J, Campos JL, Chan GSW, Young M, Ellard C (2004b) The contributions of static visual cues, nonvisual cues, and optic flow in distance estimation. Perception 33:49–65PubMedCrossRefGoogle Scholar
  55. Thomson JA (1983) Is continuous visual monitoring necessary in visually guided locomotion? J Exp Psychol Hum Percept Perform 9:427–443PubMedCrossRefGoogle Scholar
  56. Von Holst E, Mittelstaedt H (1950) Das Reafferenzprinzip (Wechselwirkungen zwischen Zentralnervensystem und Peripherie). Naturwissenschaften 37:464–476CrossRefGoogle Scholar
  57. Werner S, Noppeney U (2010) Superadditive responses in superior temporal sulcus predict audiovisual benefits in object categorization. Cereb Cortex 20:1829–1842PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  1. 1.Institut de Recherche en Communication et Cybernétique de Nantes (IRCCyN), UMR CNRS 6597Nantes Cedex 03France
  2. 2.Max Planck Institute for Biological Cybernetics, Multisensory Perception and Action GroupTübingenGermany
  3. 3.Max Planck Institute for Biological Cybernetics, Human Perception, Cognition, and Action GroupTübingenGermany
  4. 4.Department of PsychologyUniversity of TorontoTorontoCanada
  5. 5.Toronto Rehabilitation InstituteTorontoCanada
  6. 6.Department of Cognitive NeuroscienceUniversity of BielefeldBielefeldGermany

Personalised recommendations