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Computational elements of natural vision
Constantin A Rothkopf1,2,3, Mary M Hayhoe4,5,6
1Centre for Cognitive Science & Institute of Psychology, Technical University of Darmstadt, Darmstadt, Germany.
Journal of Vision
|October 3, 2025
Summary
Understanding human behavior requires studying natural tasks. Recent models, like partially observable Markov decision processes, formalize visually guided actions, revealing regularities in sensorimotor decisions for better perception and cognition research.
Area of Science:
- Cognitive Science
- Neuroscience
- Computer Science
Background:
- Human behavior is best understood within natural, everyday tasks.
- Observations of natural visually guided behavior define functional demands on the visual system.
- Progress is hindered by behavioral diversity and lack of unified theoretical frameworks.
Purpose of the Study:
- To propose a formal approach for understanding natural human behavior.
- To identify regularities in natural behavior reflecting sensorimotor decisions.
- To outline how laboratory experiments can model natural behavior.
Main Methods:
- Summarizing regularities observed in natural behavior.
- Describing visually guided behaviors using partially observable Markov decision processes (POMDPs).
- Designing laboratory experiments to elicit common elements of natural behavior and control task statistics.
Main Results:
- Natural behavior exhibits regularities linked to sensorimotor decisions.
- Partially observable Markov decision processes effectively describe simple visually guided behaviors.
- Laboratory experiments can be structured for formal modeling of natural behavior.
Conclusions:
- A formal approach using POMDPs can advance the understanding of natural human behavior.
- Inverse models offer a promising future direction for recovering intrinsic properties of perception, cognition, and action.
- Intertwined perception, cognition, and action in natural behavior can be formally modeled.
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