Book contents
- Frontmatter
- Contents
- List of contributors
- Preface
- Neurons and neural networks: general principles
- Synaptic plasticity, topological and temporal features, and higher cortical processing
- 5 Neurons with hysteresis?
- 6 On models of short- and long-term memories
- 7 Topology, structure, and distance in quasirandom neural networks
- 8 A layered network model of sensory cortex
- 9 Computer simulation of networks of electrotonic neurons
- 10 A possible role for coherence in neural networks
- 11 Simulations of the trion model and the search for the code of higher cortical processing
- 12 AND–OR logic analogue of neuron networks
- Spin glass models and cellular automata
- Cyclic phenomena and chaos in neural networks
- The cerebellum and the hippocampus
- Olfaction, vision and cognition
- Applications to experiment, communication and control
- Author index
- Subject index
11 - Simulations of the trion model and the search for the code of higher cortical processing
from Synaptic plasticity, topological and temporal features, and higher cortical processing
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
- 5 Neurons with hysteresis?
- 6 On models of short- and long-term memories
- 7 Topology, structure, and distance in quasirandom neural networks
- 8 A layered network model of sensory cortex
- 9 Computer simulation of networks of electrotonic neurons
- 10 A possible role for coherence in neural networks
- 11 Simulations of the trion model and the search for the code of higher cortical processing
- 12 AND–OR logic analogue of neuron networks
- Spin glass models and cellular automata
- Cyclic phenomena and chaos in neural networks
- The cerebellum and the hippocampus
- Olfaction, vision and cognition
- Applications to experiment, communication and control
- Author index
- Subject index
Summary
Introduction
The quest or search for the ‘code’ or ‘codes’ involved in short-term memory and information processing in higher mammalian cortex is one of the most exciting and challenging problems in all of science. The recent experimental progress and results from recording in cortex using large arrays of microelectrodes (Krüger & Bach, 1981; Bach & Krüger, 1986) and using optical dye techniques (Blasdel & Salama, 1986; Grinvald et al., 1981) offer great opportunities in the search for the code. The crosscorrelation analyses of these type of data are enormously difficult (Gerstein, Perkel & Dayhoff, 1985; Aertsen, Gerstein & Johannesma, 1986). Thus the close interplay of new theoretical models and experiment will be crucial.
The basis for the tremendous magnitudes of the processing capabilities and the memory storage capacities remain mysteries despite the substantial efforts and results in modeling neural networks; see, e.g., references in Amari & Arbib (1982), Ballard (1986) and Pisco (1984). We believe the Mountcastle (1978) columnar organizing principle for the functioning of neocortex will help provide a basis for these phenomena and we constructed the trion model (Shaw, Silverman & Pearson, 1985; Shaw, Silverman & Pearson, 1986; Silverman, Shaw & Pearson, 1986). Mountcastle proposed that the well-established cortical column (Goldmann–Rakic, 1984), roughly 500 μm in diameter, is the basic network in the cortex and is comprised of small irreducible processing sub-units. The sub-units are connected into the columns or networks having the capability of complex spatial–temporal firing patterns.
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- Computer Simulation in Brain Science , pp. 189 - 209Publisher: Cambridge University PressPrint publication year: 1988
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