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Processing of probabilistic information in weight perception and motor prediction

Overview of attention for article published in Attention, Perception, & Psychophysics, December 2016
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Title
Processing of probabilistic information in weight perception and motor prediction
Published in
Attention, Perception, & Psychophysics, December 2016
DOI 10.3758/s13414-016-1266-5
Pubmed ID
Authors

Leif Trampenau, Thilo van Eimeren, Johann Kuhtz-Buschbeck

Abstract

We studied the effects of probabilistic cues, i.e., of information of limited certainty, in the context of an action task (GL: grip-lift) and of a perceptual task (WP: weight perception). Normal subjects (n = 22) saw four different probabilistic visual cues, each of which announced the likely weight of an object. In the GL task, the object was grasped and lifted with a pinch grip, and the peak force rates indicated that the grip and load forces were scaled predictively according to the probabilistic information. The WP task provided the expected heaviness related to each probabilistic cue; the participants gradually adjusted the object's weight until its heaviness matched the expected weight for a given cue. Subjects were randomly assigned to two groups: one started with the GL task and the other one with the WP task. The four different probabilistic cues influenced weight adjustments in the WP task and peak force rates in the GL task in a similar manner. The interpretation and utilization of the probabilistic information was critically influenced by the initial task. Participants who started with the WP task classified the four probabilistic cues into four distinct categories and applied these categories to the subsequent GL task. On the other side, participants who started with the GL task applied three distinct categories to the four cues and retained this classification in the following WP task. The initial strategy, once established, determined the way how the probabilistic information was interpreted and implemented.

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The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 33%
Student > Ph. D. Student 3 33%
Professor 1 11%
Unknown 2 22%
Readers by discipline Count As %
Computer Science 1 11%
Economics, Econometrics and Finance 1 11%
Psychology 1 11%
Neuroscience 1 11%
Engineering 1 11%
Other 0 0%
Unknown 4 44%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 January 2017.
All research outputs
#21,500,614
of 24,003,070 outputs
Outputs from Attention, Perception, & Psychophysics
#1,661
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Outputs of similar age
#363,254
of 427,832 outputs
Outputs of similar age from Attention, Perception, & Psychophysics
#27
of 46 outputs
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