Emergence of Simple-Cell Receptive Field Properties by Learning a Sparse Code for Natural Images.¶
Olshausen, B. A., & Field, D. J. (1996). Emergence of Simple-Cell Receptive Field Properties by Learning a Sparse Code for Natural Images. Nature, 381(6583), 607-609.
Cited by¶
1 citation across 1 artifact.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Sparse Coding
- In neuroscience — the canonical case — any single sensory stimulus activates a small fraction of cortical neurons; place cells and grid cells are sparse codes for spatial location, and efficient-coding optimisation on natural images yields sparse V1 receptive fields.
This sourceDerives sparse, localized, oriented, bandpass basis functions matching V1 simple-cell receptive fields by minimizing reconstruction error plus a sparsity penalty over an overcomplete dictionary.
Supported in partVerified against the publisher's abstract
The abstract backs only the V1 clause: sparse coding of natural scenes yields localized, oriented, bandpass receptive fields like simple cells; it says nothing about cortical sparseness or place/grid cells.
“We show that a learning algorithm that attempts to find sparse linear codes for natural scenes will develop a complete family of localized, oriented, bandpass receptive fields, similar to those found in the primary visual cortex.”
- In neuroscience — the canonical case — any single sensory stimulus activates a small fraction of cortical neurons; place cells and grid cells are sparse codes for spatial location, and efficient-coding optimisation on natural images yields sparse V1 receptive fields.
Verification¶
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Registry ID ref:2558c03a9d62 · see in the full table