Integration of Serial Sensory Information in Haptic Perception of Softness

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Abstract

Redundant estimates of an environmental property derived simultaneously from different senses or cues are typically integrated according to the maximum likelihood estimation model (MLE): Sensory estimates are weighted according to their reliabilities, maximizing the percept’s reliability. Mechanisms underlying the integration of sequentially derived estimates from one sense are less clear. Here we investigate the integration of serially sampled redundant information in softness perception. We developed a method to manipulate haptically perceived softness of silicone rubber stimuli during bare-finger exploration. We then manipulated softness estimates derived from single movement segments (indentations) in a multisegmented exploration to assess their contributions to the overall percept. Participants explored two stimuli in sequence, using 2–5 indentations, and reported which stimulus felt softer. Estimates of the first stimulus’s softness contributed to the judgments similarly, whereas for the second stimulus estimates from later compared to earlier indentations contributed less. In line with unequal weighting, the percept’s reliability increased with increasing exploration length less than was predicted by the MLE model. This pattern of results is well explained by assuming that the representation of the first stimulus fades when the second stimulus is explored, which fits with a neurophysiological model of perceptual decisions (Deco, Rolls, & Romo, 2010).

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