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Affect and non-uniform characteristics of predictive processing in musical behaviour
Rebecca S Schaefer1, Katie Overy, Peter Nelson
1Institute for Music in Human and Social Development (IMHSD), Reid School of Music, University of Edinburgh, Edinburgh EH8 9DF, United Kingdom. r.schaefer@ed.ac.uk
The Behavioral and Brain Sciences
|May 14, 2013
Summary
Prior experience and prediction are key to musical intelligence, aligning with predictive processing theories. However, the role of affect in prediction error is crucial for a complete understanding of musical cognition.
Area of Science:
- Cognitive Science
- Neuroscience
- Music Psychology
Background:
- Prior experience and prediction are fundamental in music research.
- These concepts align with hierarchical, bidirectional predictive processing models.
- Andy Clark's theory posits unified perception, cognition, and action.
Purpose of the Study:
- To integrate the role of affect into predictive processing models of musical intelligence.
- To expand upon Clark's framework by incorporating emotional influences on prediction error.
Main Methods:
- Theoretical analysis of existing music cognition research.
- Conceptual integration of affect theory with predictive processing frameworks.
Main Results:
- Predictive processing offers a robust framework for understanding musical intelligence.
- Affect significantly modulates prediction error processing in music.
- Clark's model requires augmentation to fully capture musical cognition.
Conclusions:
- A comprehensive model of musical intelligence must account for the interplay between prediction, prior experience, and affect.
- Future research should explore the neurobiological and psychological mechanisms linking affect and predictive coding in music.
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