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Internal references in cross-modal judgments: A global psychophysical perspective
1Department of Psychology, University of Tübingen.
Psychological Review
|May 3, 2021
Summary
This study introduces a generalized theory of cross-dimensional magnitude production, incorporating role-dependent internal references. This new model explains the regression effect in cross-dimensional matching tasks, improving psychophysical predictions.
Area of Science:
- Psychophysics
- Cognitive Science
- Sensory Perception
Background:
- Cross-dimensional matching allows comparing intensities of different sensory stimuli (e.g., visual brightness to auditory loudness).
- The regression effect, where adjusted stimuli tend toward a mean, suggests internal references are used.
- Existing psychophysical theories, like Stevens', do not explicitly incorporate internal references.
Purpose of the Study:
- To generalize R. Duncan Luce's theory of global psychophysics to include role-dependent internal references.
- To empirically test the role of internal references in cross-dimensional magnitude production and matching.
- To provide a unified theoretical framework for understanding the regression effect.
Main Methods:
- Theoretical generalization of Luce's global psychophysics model.
- Reanalysis of existing empirical data from magnitude production and matching experiments.
- Comparison of predictions from the generalized theory with classical psychophysical data.
Main Results:
- Internal references were found to be role-dependent in cross-dimensional tasks (intra- and cross-modal).
- Internal references were found to be role-independent in intra-dimensional tasks.
- The generalized theory's predictions closely matched classical matching data.
Conclusions:
- The generalized theory offers a coherent explanation for the regression effect in cross-dimensional matching.
- Internal references play a crucial, role-dependent role in cross-modal and intra-modal sensory perception.
- The study advances global psychophysics by integrating internal references and making them empirically testable.
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