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Activity in perceptual classification networks as a basis for human subjective time perception
Warrick Roseboom1,2, Zafeirios Fountas3, Kyriacos Nikiforou3
1Department of Informatics, University of Sussex, Falmer, Brighton, BN1 9QJ, UK. wjroseboom@gmail.com.
Nature Communications
|January 19, 2019
Summary
Human brain
Area of Science:
- Neuroscience
- Cognitive Science
- Artificial Intelligence
Background:
- The mechanisms underlying human time perception remain largely unknown.
- Understanding temporal perception is crucial for comprehending consciousness and experience.
Purpose of the Study:
- To propose and validate a novel computational model for human time perception.
- To investigate the role of non-temporal perceptual classification in estimating duration.
Main Methods:
- Developed an artificial neural system based on a feed-forward image classification network.
- Simulated human visual processing using natural scene videos as input.
- Measured duration estimates based on the accumulation of salient changes in network activation.
Main Results:
- The artificial system's duration estimates closely matched human reports for the same videos.
- The model successfully replicated key qualitative biases in human time perception.
- Differentiated between dynamic (e.g., city walking) and static (e.g., cafe) scenes.
Conclusions:
- Non-temporal perceptual classification processes offer a viable explanation for human time perception.
- The developed model provides a functional link from visual stimulus to duration estimation.
- This work opens new avenues for researching the neural basis of temporal experience.
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