Independent component filters of natural images compared with simple cells in primary visual cortex
Open accessAbstract
Properties of the receptive fields of simple cells in macaque cortex were compared with properties of independent component filters generated by independent component analysis (ICA) on a large set of natural images. Histograms of spatial frequency bandwidth, orientation tuning bandwidth, aspect ratio and length of the receptive fields match well. This indicates that simple cells are well tuned to the expected statistics of natural stimuli. There is no match, however, in calculated and measured distributions for the peak of the spatial frequency response: the filters produced by ICA do not vary their spatial scale as much as simple cells do, but are fixed to scales close to the finest ones allowed by the sampling lattice. Possible ways to resolve this discrepancy are discussed.
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A collection of 4,167 digital photographs of random outdoor scenes was assembled in the late 1990s by van Hateren and van der Schaaf.
“A collection of 4,167 digital photographs of random outdoor scenes was assembled in the late 1990s by van Hateren and van der Schaaf [20].”
From Barcodes: the persistent topology of data (2007) · cites this paper as [20]
The Images section describes a collection photographed with a digital camera, but gives its size as 4,212 images, not 4,167. It says the images came from woods, open landscapes and urban areas, often in consecutive series, rather than describing them as random outdoor scenes. The paper was published in 1998, but the passage does not specify when the photographs were taken. (LLM, conf=0.90)
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- Authors
- van Hateren, J. H., & van der Schaaf, A.
- Affiliations
- Department of Biophysics, University of Groningen, Nijenborgh 4, NL–9747 AG Groningen, The Netherlands
- Venue
- Proceedings of the Royal Society of London. Series B: Biological Sciences
- Publisher
- The Royal Society
- Published
- 1998-03-07
- Volume
- 265
- Issue
- 1394
- Pages
- 359-366
- ISSN
- 0080-4649 (ISSN-L)
- 0962-8452
- 1471-2954
- PMC
- PMC1688904
- OpenAlex
- W2101933716
- Cited by
- 1,106
- References
- 42
- Citations by year
- 2026: 10 · 2025: 8 · 2024: 16 · 2023: 18 · 2022: 28 · 2021: 30 · 2020: 32 · 2019: 54 · 2018: 33 · 2017: 30 · 2016: 43 · 2015: 45 · 2014: 58 · 2013: 42 · 2012: 46
- FWCI
- 19.11
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the Royal Society B Biological Sciences (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, other-oa)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion)
- Funders
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Physical Sciences › Computer Science › Signal Processing › Blind Source Separation Techniques
- Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
- Keywords
- independent component analysis, natural images, simple cells, primary visual cortex, receptive fields, spatial frequency tuning, orientation tuning, macaque cortex, sampling lattices
- MeSH terms
- Animals, Eidetic Imagery, Information Theory, Macaca, Neurons, Visual Cortex, Visual Perception
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