Book contents
- Frontmatter
- Contents
- List of contributors
- Preface
- Neurons and neural networks: general principles
- Synaptic plasticity, topological and temporal features, and higher cortical processing
- Spin glass models and cellular automata
- Cyclic phenomena and chaos in neural networks
- The cerebellum and the hippocampus
- Olfaction, vision and cognition
- 26 Neural computations and neural systems
- 27 Development of feature-analyzing cells and their columnar organization in a layered self-adaptive network
- 28 Reafferent stimulation: a mechanism for late vision and cognitive processes
- 29 Mathematical model and computer simulation of visual recognition in retina and tectum opticum of amphibians
- 30 Pattern recognition with modifiable neuronal interactions
- 31 Texture description in the time domain
- Applications to experiment, communication and control
- Author index
- Subject index
27 - Development of feature-analyzing cells and their columnar organization in a layered self-adaptive network
from Olfaction, vision and cognition
Published online by Cambridge University Press: 05 February 2012
- Frontmatter
- Contents
- List of contributors
- Preface
- Neurons and neural networks: general principles
- Synaptic plasticity, topological and temporal features, and higher cortical processing
- Spin glass models and cellular automata
- Cyclic phenomena and chaos in neural networks
- The cerebellum and the hippocampus
- Olfaction, vision and cognition
- 26 Neural computations and neural systems
- 27 Development of feature-analyzing cells and their columnar organization in a layered self-adaptive network
- 28 Reafferent stimulation: a mechanism for late vision and cognitive processes
- 29 Mathematical model and computer simulation of visual recognition in retina and tectum opticum of amphibians
- 30 Pattern recognition with modifiable neuronal interactions
- 31 Texture description in the time domain
- Applications to experiment, communication and control
- Author index
- Subject index
Summary
Introduction
Many features of the functional architecture of the mammalian visual system have been experimentally identified during the past 25 years. Among the most striking of these features is the presence of layers of orientation-selective cells – cells whose response to an edge or bar in the appropriate portion of visual field is sensitive to the local orientation of the input. These cells are organized in bands or ‘columns’ of cells of the same or similar orientation preference. The preferred orientation varies roughly monotonically, but with frequent breaks and reversals, as one traverses the cell layer. Orientation-selective cells, organized in this fashion, are found in cat, monkey, and other mammalian systems. In macaque monkey, they are present at birth.
I have found that several salient features of mammalian visual system architecture – including orientation-selective cells and columns – emerge in a multilayered network of cells whose connections develop, one layer at a time, according to a synaptic modification rule of Hebb type. The theoretical base is biologically plausible, none of the assumptions is specific to visual processing, no orientation preferences are specified to the system at any stage, and the features emerge even in the absence of environmental input.
The development of this system is discussed in detail, and references to experimental work are provided, in a series of three papers (Linsker, 1986a,b,c).
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- Computer Simulation in Brain Science , pp. 416 - 431Publisher: Cambridge University PressPrint publication year: 1988
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