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Computational Maps in the Visual Cortex

✍ Scribed by Risto Miikkulainen, James A. Bednar, Yoonsuck Choe, Joseph Sirosh (auth.)


Publisher
Springer-Verlag New York
Year
2005
Tongue
English
Leaves
546
Edition
1
Category
Library

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✦ Synopsis


Biological structures can be seen as collections of special devices coordinated by a matrix of organization. Devices are dif?cult to evolve and are meticulously conserved through the eons. Organization is a ?uid medium capable of rapid adaptation. The brain carries organizational ?uidity to the extreme. In its context, typical devices are ion channels, transmitters and receptors, signaling pathways, whole individual neurons or speci?c circuit patterns. The border line between what is to be called device and what a feat of organization is ?owing, given that in time organized s- systems solidify into devices. In spite of the neurosciences’ traditional concentration on devices, their aiming point on the horizon must be to understand the principles by which the nervous system ties vast arrays of internal and external variables into one coherent purposeful functional whole β€” to understand the brain’s mechanism of organization. For that purpose a crucial methodology is in silico experimentation. Computer simulation is a convenient tool for testing functional ideas, a sharp weapon for d- tinguishing those that work from those that don’t. To be sure, many alternatives can only be decided by direct experiment on the substrate, not by modeling. However, if a functional idea can be debunked as ?awed once tried in silico it would be a waste to make it the subject of a decade of experimentation or discussion. The venture of understanding the function and organization of the visual system illustrates this danger.

✦ Table of Contents


Introduction....Pages 3-13
Biological Background....Pages 15-37
Computational Foundations....Pages 39-64
LISSOM: A Computational Map Model of V1....Pages 67-83
Development of Maps and Connections....Pages 85-132
Understanding Plasticity....Pages 133-153
Understanding Visual Performance: The Tilt Aftereffect....Pages 155-172
HLISSOM: A Hierarchical Model....Pages 175-187
Understanding Low-Level Development: Orientation Maps....Pages 189-202
Understanding High-Level Development: Face Detection....Pages 203-238
PGLISSOM: A Perceptual Grouping Model....Pages 241-255
Temporal Coding....Pages 257-271
Understanding Perceptual Grouping: Contour Integration....Pages 273-304
Computations in Visual Maps....Pages 307-324
Scaling LISSOM simulations....Pages 325-343
Discussion: Biological Assumptions and Predictions....Pages 345-373
Future Work: Computational Directions....Pages 375-408
Conclusion....Pages 409-412

✦ Subjects


Neurobiology; Neurosciences; Ophthalmology; Computer Appl. in Life Sciences


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