- Abstract:
-
How can a system as complex as the human visual system be constructed? How can it be specified genetically, while allowing it to adapt to the environment? How can it perform complicated functions such as recognizing faces and identifying coherent objects immediately and automatically? While these questions have been open for quite some time, and much experimental work remains to be done to answer them conclusively, computational models have recently become powerful enough to suggests specific, computational answers: The cortical structures are constructed through input-driven self-organization, the self-organization is driven both by external visual inputs and by genetically determined internal inputs, and perceptual grouping takes place automatically through synchronization of neuronal activity, mediated by self-organized lateral connections. In this book, we describe a unified computational map model, LISSOM, built on these principles. Simulated experiments with LISSOM demonstrate how a wide variety of phenomena follow from them, including columnar map organization and patchy connectivity, recovery from retinal and cortical injury, psychophysical phenomena such as tilt aftereffects and contour integration, and newborn preference for faces. The model is used to gain a precise computational understanding of existing data, and to make specific predictions for future experimental and theoretical research.
- Links To Paper
- 1st Link
- 2nd Link
- Bibtex format
- @Book{EDI-INF-RR-0329,
- author = {
Risto Miikkulainen
and James Bednar
and Yoonsuck Choe
and Joseph Sirosh
},
- title = {Computational Maps in the Visual Cortex},
- publisher = {Springer},
- year = 2005,
- url = {http://computationalmaps.org},
- }
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