Linear path integration deficits in patients with abnormal vestibular afference

Joeanna C. Arthur, Kathleen B. Kortte, Mark Shelhamer, Michael C. Schubert

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


Effective navigation requires the ability to keep track of one's location and maintain orientation during linear and angular displacements. Path integration is the process of updating the representation of body position by integrating internally-generated self-motion signals over time (e.g., walking in the dark). One major source of input to path integration is vestibular afference. We tested patients with reduced vestibular function (unilateral vestibular hypofunction, UVH), patients with aberrant vestibular function (benign paroxysmal positional vertigo, BPPV), and healthy participants (controls) on two linear path integration tasks: experimenter-guided walking and target-directed walking. The experimenter-guided walking task revealed a systematic underestimation of self-motion signals in UVH patients compared to the other groups. However, we did not find any difference in the distance walked between the UVH group and the control group for the target-directed walking task. Results from neuropsychological testing and clinical balance measures suggest that the errors in experimenter-guided walking were not attributable to cognitive and/or balance impairments. We conclude that impairment in linear path integration in UVH patients stem from deficits in self-motion perception. Importantly, our results also suggest that patients with a UVH deficit do not lose their ability to walk accurately without vision to a memorized target location.

Original languageEnglish (US)
Pages (from-to)155-178
Number of pages24
JournalSeeing and Perceiving
Issue number2
StatePublished - 2012


  • Vestibular navigation
  • path integration
  • spatial orientation
  • vestibular hypofunction

ASJC Scopus subject areas

  • Experimental and Cognitive Psychology
  • Ophthalmology
  • Sensory Systems
  • Computer Vision and Pattern Recognition
  • Cognitive Neuroscience


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