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Efficient data compression in perception and perceptual memory
Christopher J Bates1, Robert A Jacobs1
1Department of Brain and Cognitive Sciences.
Psychological Review
|April 24, 2020
Summary
Biological systems, like engineered ones, use efficient data compression. Rate-distortion theory (RDT) principles explain human perception and memory, with new deep learning models approximating RDT in complex scenarios.
Area of Science:
- Cognitive Science
- Computational Neuroscience
- Information Theory
Background:
- Efficient data compression is crucial for biological and engineered systems with limited capacity.
- Rate-distortion theory (RDT) offers a framework for analyzing engineered compression systems.
- Understanding human perception and memory may benefit from applying RDT principles.
Purpose of the Study:
- To explore how principles of efficient data compression explain behavioral phenomena in human perception and memory.
- To investigate the application of rate-distortion theory (RDT) to biological systems.
- To introduce a novel deep neural network architecture for approximating RDT in high-dimensional perceptual spaces.
Main Methods:
- Discussed three general principles of efficient data compression and their relation to RDT.
- Reviewed existing deep neural network approaches for approximating RDT in high-dimensional spaces.
- Introduced a new end-to-end trained deep neural network architecture operating on raw perceptual input.
Main Results:
- Three data compression principles account for numerous behavioral phenomena and experimental findings.
- The new deep neural network architecture approximates RDT in high-dimensional spaces.
- The architecture is trained end-to-end on raw perceptual data, bypassing intermediate abstractions.
Conclusions:
- The need for efficient compression likely shapes biological systems similarly to engineered ones.
- RDT provides a valuable theoretical lens for understanding human perception and memory.
- Future research can explore compression in memory over time and its relation to attention and visual search.
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