4.7 Article

Efficient Visual Recalibration from Either Visual or Haptic Feedback: The Importance of Being Wrong

Journal

JOURNAL OF NEUROSCIENCE
Volume 30, Issue 44, Pages 14745-14749

Publisher

SOC NEUROSCIENCE
DOI: 10.1523/JNEUROSCI.2749-10.2010

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Funding

  1. Engineering and Physical Sciences Research Council [EP/D039916/1]
  2. British Academy [SG-49590]
  3. Royal Society
  4. Economic and Social Research Council
  5. EPSRC [EP/D039916/1] Funding Source: UKRI
  6. Engineering and Physical Sciences Research Council [EP/D039916/1] Funding Source: researchfish

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The human visual system adapts to the changing statistics of its environment. For example, the light-from-above prior, an assumption that aids the interpretation of ambiguous shading information, can be modified by haptic (touch) feedback. Here we investigate the mechanisms that drive this adaptive learning. In particular, we ask whether visual information can be as effective as haptics in driving visual recalibration and whether increased information (feedback from multiple modalities) induces faster learning. During several hours' training, feedback encouraged observers to modify their existing light-from-above assumption. Feedback was one of the following: (1) haptic only, (2) haptic and stereoscopic (providing binocular shape information), or (3) stereoscopic only. Haptic-only feedback resulted in substantial learning; the perceived shape of shaded objects was modified in accordance with observers' new light priors. However, the addition of continuous visual feedback (condition 2) substantially reduced learning. When visual-only feedback was provided intermittently (condition 3), mimicking the time course of the haptic feedback of conditions 1 and 2, substantial learning returned. The intermittent nature of conflict information, or feedback, appears critical for learning. It causes an initial, erroneous percept to be corrected. Contrary to previous proposals, we found no particular advantage for cross-modal feedback. Instead, we suggest that an oops factor drives efficient learning; recalibration is prioritized when a mismatch exists between sequential representations of an object property. This oops factor appears important both across and within sensory modalities, suggesting a general principle for perceptual learning and recalibration.

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