A mass-density model can account for the size-weight illusion. Research data of three experiments.

Cognitive Psychology

Authors(s) / Creator(s)



Abstract

When judging the heaviness of two objects with equal mass, people perceive the smaller and denser of the two as being heavier. Despite the high number of theories, covering bottom-up and top-down approaches, none of them can fully account for all aspects of this size-weight illusion and thus for human heaviness perception. Here we propose a new Bayesian-type model which describes the illusion as the weighted average of two heaviness estimates: One estimate derived from the object’s mass, and the other from the object’s density, with the weights based on the estimates’ relative reliabilities. In two magnitude estimation experiments, we tested model predictions for the visual and the haptic size-weight illusion. Participants lifted objects which varied in mass and density. We additionally varied the reliability of the density estimate by varying the quality of either visual (Experiment 1) or haptic (Experiment 2) volume information. Like predicted, with increasing quality of volume information, heaviness judgments were increasingly biased towards the object’s density: Objects of the same density were perceived as more similar and big objects were perceived as increasingly lighter than small (denser) objects of the same mass. This perceived difference increased with an increasing difference in density. In a further two-alternative forced choice heaviness experiments, we replicated that the illusion strength increases with the quality of volume information (Experiment 3). Overall, the results highly corroborate our model, which seems promising as unifying framework for the size-weight illusion and human heaviness perception.

Persistent Identifier

https://doi.org/10.5160/psychdata.wfcn13ma18

Year of Publication

Funding

German Research Foundation (SFB/TRR 135)

Citation

Wolf, C., Bergmann Tiest, W. M. & Drewing, K. (2018). A mass-density model can account for the size-weight illusion. Research data of three experiments. (Version 1.0.0) [Data and Documentation]. Trier: Research Data Center at ZPID. https://doi.org/10.5160/psychdata.wfcn13ma18

Study Description

Research Questions/Hypotheses:

Heaviness perception can be described as a weighted average of a heaviness estimate derived from mass and a heaviness estimate derived from density. The contribution of each estimate depends on its relative reliability.

Research Design:

Experimentelles Design, Laborexperiment; mehrmalige Erhebung

Measurement Instruments/Apparatus:

Participants lifted objects with different mass, size and density. Heaviness was either judged in a free magnitude estimation task (Experiment 1 and 2) or using a two-alternative forced choice (2AFC) task (Experiment 3). More detailed information can be found in Wolf et al. (2018).

Data Collection Method:

Data collection in the presence of an experimenter

Population:

Healthy adults

Survey Time Period:

Due to the length of Experiment 2 and 3, they have been split up into several recording sessions.

Sample:

Convenience sample

Gender Distribution:

Experiment 1:
20% female subjects (n=3)
80% male subjects (n=12)

Experiment 2:
50% female subjects (n=10)
50% male subjects (n=10)

Experiment 3:
50% female subjects (n=5)
50% male subjects (n=5)


Age Distribution: 19-44 years

Spatial Coverage (Country/Region/City): Germany/-/Gießen

Subject Recruitment:

Participants were psychology students from Giessen University and received course credit in return.

Sample Size:

Experiment 1: 15 individuals; Experiment 2: 20 individuals; Experiment 3: 10 individuals

Return/Drop Out:

wfcn13ma18_readme.txt
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wfcn13ma18_fd1.txt
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Description: Research data file from experiment 1

wfcn13ma18_fd2_1.txt
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Description: Research data file from experiment 2 (1)

wfcn13ma18_fd2_2.txt
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Description: Research data file from experiment 2 (2)

wfcn13ma18_fd3.txt
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Description: Research data file from experiment 3

wfcn13ma18_kb1.txt
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wfcn13ma18_kb2_1.txt
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wfcn13ma18_kb2_2.txt
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wfcn13ma18_kb3.txt
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