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Open AccessJournal ArticleDOI

Visual and haptic integration in the estimation of softness of deformable objects

Cristiano Cellini, +2 more
- 01 Dec 2013 - 
- Vol. 4, Iss: 8, pp 516-531
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TLDR
The visuo-haptic integration of softness information is biased toward vision, rather than being optimal, and might even be guided by a fixed weighting scheme.
Abstract
Softness perception intrinsically relies on haptic information. However, through everyday experiences we learn correspondences between felt softness and the visual effects of exploratory movements that are executed to feel softness. Here, we studied how visual and haptic information is integrated to assess the softness of deformable objects. Participants discriminated between the softness of two softer or two harder objects using only-visual, only-haptic or both visual and haptic information. We assessed the reliabilities of the softness judgments using the method of constant stimuli. In visuo-haptic trials, discrepancies between the two senses' information allowed us to measure the contribution of the individual senses to the judgments. Visual information (finger movement and object deformation) was simulated using computer graphics; input in visual trials was taken from previous visuo-haptic trials. Participants were able to infer softness from vision alone, and vision considerably contributed to bisensory judgments (∼35%). The visual contribution was higher than predicted from models of optimal integration (senses are weighted according to their reliabilities). Bisensory judgments were less reliable than predicted from optimal integration. We conclude that the visuo-haptic integration of softness information is biased toward vision, rather than being optimal, and might even be guided by a fixed weighting scheme.

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References
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Journal ArticleDOI

Humans integrate visual and haptic information in a statistically optimal fashion.

TL;DR: The nervous system seems to combine visual and haptic information in a fashion that is similar to a maximum-likelihood integrator, and this model behaved very similarly to humans in a visual–haptic task.
Journal ArticleDOI

The psychometric function: I. Fitting, sampling, and goodness of fit

TL;DR: An integrated approach to fitting psychometric functions, assessing the goodness of fit, and providing confidence intervals for the function’s parameters and other estimates derived from them, for the purposes of hypothesis testing is described.
Book

The Merging of the Senses

TL;DR: The authors draw on their own experiments to illustrate how sensory inputs converge on individual neurons in different areas of the brain, how these neurons integrate their inputs, the principles by which this integration occurs, and what this may mean for perception and behavior.
Journal ArticleDOI

The Ventriloquist Effect Results from Near-Optimal Bimodal Integration

TL;DR: This study investigates spatial localization of audio-visual stimuli and finds that for severely blurred visual stimuli, the reverse holds: sound captures vision while for less blurred stimuli, neither sense dominates and perception follows the mean position.
Journal ArticleDOI

Merging the senses into a robust percept

TL;DR: It is shown that, depending on the type of information, different combination and integration strategies are used and that prior knowledge is often required for interpreting the sensory signals.
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