Biological Cybernetics

, Volume 96, Issue 4, pp 389–404

Bayesian processing of vestibular information

Original Paper

Abstract

Complex self-motion stimulations in the dark can be powerfully disorienting and can create illusory motion percepts. In the absence of visual cues, the brain has to use angular and linear acceleration information provided by the vestibular canals and the otoliths, respectively. However, these sensors are inaccurate and ambiguous. We propose that the brain processes these signals in a statistically optimal fashion, reproducing the rules of Bayesian inference. We also suggest that this processing is related to the statistics of natural head movements. This would create a perceptual bias in favour of low velocity and acceleration. We have constructed a Bayesian model of self-motion perception based on these assumptions. Using this model, we have simulated perceptual responses to centrifugation and off-vertical axis rotation and obtained close agreement with experimental findings. This demonstrates how Bayesian inference allows to make a quantitative link between sensor noise and ambiguities, statistics of head movement, and the perception of self-motion.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Angelaki DE, Shaikh AG, Green AM, Dickman JD (2004) Neurons compute internal models of the physical laws of motion. Nature, 430(6999):560–564PubMedCrossRefGoogle Scholar
  2. Benson AJ, Bodin MA (1966) Interaction of linear and angular accelerations on vestibular receptors in man. Aerosp Med 37(2):144–154PubMedGoogle Scholar
  3. Borah J, Young LR, Curry RE (1988) Optimal estimator model for human spatial orientation. Ann NY Acad Sci 545:51–73PubMedCrossRefGoogle Scholar
  4. Bos JE, Bles W (2002) Theoretical considerations on canal-otolith interaction and an observer model. Biol Cybern 86(3):191–207PubMedCrossRefGoogle Scholar
  5. Bos JE, Bles W, de Graaf B (2002) Eye movements to yaw, pitch, and roll about vertical and horizontal axes: adaptation and motion sickness. Aviat Space Environ Med 73(5):436–444PubMedGoogle Scholar
  6. Correia MJ, Guedry FE (1966) Modification of vestibular responses as a function of rate of rotation about an earth-horizontal axis. Acta Otolaryngol 62(4):297–308PubMedGoogle Scholar
  7. Curthoys IS, Haslwanter T, Black RA, Burgess AM, Halmagyi GM, Topple AN, Todd MJ (1998) Off-center yaw rotation: effect of naso-occipital linear acceleration on the nystagmus response of normal human subjects and patients after unilateral vestibular loss. Exp Brain Res 123(4):425–438PubMedCrossRefGoogle Scholar
  8. Deneve S, Latham PE, Pouget A (2001) Efficient computation and cue integration with noisy population codes. Nat Neurosci 4(8):826–831PubMedCrossRefGoogle Scholar
  9. Denise P, Darlot C, Droulez J, Cohen B, Berthoz A (1988) Motion perceptions induced by off-vertical axis rotation (ovar) at small angles of tilt. Exp Brain Res 73(1):106–114PubMedCrossRefGoogle Scholar
  10. Droulez J, Darlot C (1989) The geometric and dynamic implications of the coherence constraints in three-dimensional sensorimotor interactions. In: Jeannerod M. (ed) Attention and Performance XIII. New York, Erlbaum, pp 495–526Google Scholar
  11. Droulez J, Cornilleau Perez V (1993) Application of the coherence scheme to the multisensory fusion problem. In: Jeannerod M (ed) Multisensory control of movement. Oxford University Press, Oxford, pp 485–501Google Scholar
  12. Ernst MO and Banks MS (2002) Humans integrate visual and haptic information in a statistically optimal fashion. Nature 415(6870):429–433PubMedCrossRefGoogle Scholar
  13. Glasauer S, Merfeld DM (1997) Modeling three dimensional vestibular responses during complex motion stimulations. In: Three-dimensional kinematics of eye, head and limb movements, Harwood Switzerland, pp 387–389Google Scholar
  14. Glasauer S (1992) Human spatial orientation during centrifuge experiments : non-linear interaction of semicircular canals and otoliths. In: Jerabek J Krejcova H (ed) Proceedings of the XVIIth Barany Society Meeting, pp 48–52Google Scholar
  15. Graybiel A and Clark B (1965) Validity of the oculogravic illusion as an indicator of otolith function. Aerospace Med 36: 1173–1181Google Scholar
  16. Guedry FE (1965) Orientation of the rotation-axis relative to gravity: its influence on nystagmus and the sensation of rotation. Acta Otolaryngol 60:30–48PubMedGoogle Scholar
  17. Guedry FE (1974) Psychophysics of vestibular sensation. In: Kornhuber H.H (ed) Handbook of sensory physiology, Chap. 1. Springer, Berlin, pp 3–154Google Scholar
  18. Henn V, Cohen B, Young LR (1980) Visual-vestibular interaction in motion perception and the generation of nystagmus. Neurosci Res Program Bull 18(4):457–651PubMedGoogle Scholar
  19. Hillis JM, Ernst MO, Banks MS, Landy MS (2002) Combining sensory information: Mandatory fusion within, but not between, senses. Science 298:1627–1630PubMedCrossRefGoogle Scholar
  20. Hosman RJ, van der Vaart JC (1978) Vestibular models and thresehomds of motion perception. results of tests in a flight simulator. ReportGoogle Scholar
  21. Klam F, Graf W (2003) Vestibular response kinematics in posterior parietal cortex neurons of macaque monkeys. Eur J Neurosci 18(4):995–1010PubMedCrossRefGoogle Scholar
  22. Kording KP, Wolpert DM (2004) Bayesian integration in sensorimotor learning. Nature 427(6971):244–247PubMedCrossRefGoogle Scholar
  23. Lackner JR, Graybiel A (1978) Postural illusions experienced during z-axis recumbent rotation and their dependence upon somatosensory stimulation of the body surface. Aviat Space Environ Med 49(3):484–488PubMedGoogle Scholar
  24. Lee TS and Mumford D (2003) Hierarchical bayesian inference in the visual cortex. J Opt Soc Am A Opt Image Sci Vis 20(7):1434–1448PubMedGoogle Scholar
  25. Maskell S, Gordon N (2002) A tutorial on particle filters for on-line nonlinear/non-gaussian bayesian tracking. IEEE Trans Signal Process 50(2):174–188CrossRefGoogle Scholar
  26. Mayne R (1974) A system concept of the vestibular organs. In: Kornhuber H.H (ed) Handbook of Sensory Physiology, vol VI. Vestibular system Part 2: psychophysics, applied aspects and general interpretations. Springer, Berlin Heidelberg New York, pp 493–580Google Scholar
  27. Merfeld DM, Zupan LH, Gifford CA (2001) Neural processing of gravito-inertial cues in humans. ii. influence of the semicircular canals during eccentric rotation. J Neurophysiol 85(4):1648–1660PubMedGoogle Scholar
  28. Merfeld DM, Park S, Gianna C-Poulin, Black FO, Wood S (2005) Vestibular perception and action employ qualitatively different mechanisms. I. frequency response of vor and perceptual responses during translation and tilt. J Neurophysiol 94(1):186–198PubMedCrossRefGoogle Scholar
  29. Merfeld DM, Park S, Gianna Poulin C, Black FO, Wood S (2005) Vestibular perception and action employ qualitatively different mechanisms. ii. vor and perceptual responses during combined tilt and translation. J Neurophysiol 94(1):199–205PubMedCrossRefGoogle Scholar
  30. Merfeld DM (1995) Modeling the vestibulo-ocular reflex of the squirrel monkey during eccentric rotation and roll tilt. Exp Brain Res 106(1):123–134PubMedGoogle Scholar
  31. Mittelstaedt H, Glasauer S, Gralla G, Mittelstaedt ML (1989) How to explain a constant subjective vertical at constant high speed rotation about an earth-horizontal axis. Acta Otolaryngol Suppl 468:295–299PubMedGoogle Scholar
  32. Oman CM (1982) A heuristic mathematical model for the dynamics of sensory conflict and motion sickness. Acta Otolaryngol Suppl 392:1–44PubMedGoogle Scholar
  33. Rao RP (2004) Bayesian computation in recurrent neural circuits. Neural Comput 16(1):1–38PubMedCrossRefGoogle Scholar
  34. Raphan T, Cohen B (2002) The vestibulo-ocular reflex in three dimensions. Exp Brain Res 145(1):1–27PubMedCrossRefGoogle Scholar
  35. Raphan T, Cohen B, Matsuo V (1977) A velocity-storage mechanism responsible for optokinetic nystagmus (okn), optokinetic after-nystagmus (okan) and vestibular nystagmus. In: Control of gaze by brainsteam neurons, Elsevier, Amsterdam pp 37–47Google Scholar
  36. Reymond G, Droulez J, Kemeny A (2002) Visuovestibular perception of self-motion modeled as a dynamic optimization process. Biol Cybern 87(4):301–314PubMedCrossRefGoogle Scholar
  37. Robinson DA (1977) Vestibular and optokinetic symbiosis: an example of explaining by modelling. In: Control of gaze by brainsteam neurons, Elsevier, Amsterdam pp 49–58Google Scholar
  38. van der Kooij H, Jacobs R, Koopman B, Grootenboer H (1999) A multisensory integration model of human stance control. Biol Cybern 80(5):299–308PubMedCrossRefGoogle Scholar
  39. van der Kooij H, Jacobs R, Koopman B, van der Helm F (2001) An adaptive model of sensory integration in a dynamic environment applied to human stance control. Biol Cybern 84(2): 103–115PubMedCrossRefGoogle Scholar
  40. Weiss Y, Simoncelli EP, Adelson EH (2002) Motion illusions as optimal percepts. Nat Neurosci 5(6):598–604PubMedCrossRefGoogle Scholar
  41. Yakushin SB, Raphan T, Suzuki J, Arai Y, Cohen B (1998) Dynamics and kinematics of the angular vestibulo-ocular reflex in monkey: effects of canal plugging. J Neurophysiol 80(6): 3077–3099PubMedGoogle Scholar
  42. Zemel RS, Dayan P, Pouget A (1998) Probabilistic interpretation of population codes. Neural Comput 10(2):403–430PubMedCrossRefGoogle Scholar
  43. Zupan LH, Merfeld DM, Darlot C (2002) Using sensory weighting to model the influence of canal, otolith and visual cues on spatial orientation and eye movements. Biological Cybernetics 86(3):209–230PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  1. 1.Laboratoire de Physiologie de la Perception et de l’ActionCNRS UMR 7152ParisFrance

Personalised recommendations