Computer Simulation in Brain Scienceby Rodney M. J. Cotterill
Forty-three of the leading experts in this burgeoning field have assembled to produce an exciting review of the many advances to date. The volume reviews the creation of computer models of neural function, of cognition, memory, and vision. The results and future directions explored here will have an important bearing on research into brain function, physiology,… See more details below
Forty-three of the leading experts in this burgeoning field have assembled to produce an exciting review of the many advances to date. The volume reviews the creation of computer models of neural function, of cognition, memory, and vision. The results and future directions explored here will have an important bearing on research into brain function, physiology, psychology, biophysics, and artificial intelligence.
- Cambridge University Press
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- 5.98(w) x 8.98(h) x 1.30(d)
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Table of Contents
Preface; Part I. Neurons and Neural Networks: General Principles: 1. Some recent developments in the theory of neural networks; 2. Representation of sensory information in self-organizating feature maps, and the relation of these maps to distributed memory networks; 3. Excitable dendritic spine clusters: nonlinear synaptic processing; 4. Vistas from tensor network theory: a horizon from reductionalistic neurophilosophy to the geometry of multi-unit recordings; Part II. 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 metwork model of sensory cortex; 9. Computer simulation of networks of electronic 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; Part III. Spin Glass Models and Cellular Automata: 13. Neural networks: learning and forgetting; 14. Learning by error corrections in spin glass models of neural networks; 15. Random complex automata: analogy with spin glasses; 16. The evolution of data processing abilities in competing automata; 17. The inverse problem for neural nets and cellular automata; Part IV. Cyclic Phenomena and Chaos in Neural Networks: 18. A new synaptic modification algorithm and rhythmic oscillation; 19. 'Normal' and 'abnormal' dynamic behaviour during synaptic transmission; 20. Computer simulation studies to deduce the structure and function of the human brain; 21. Access stability of cyclic modes in quasirandom networks of threshold neurons obeying a deterministic synchronous dynamics; 22. Transition to cycling in neural networks; 23. Exemplification of chaotic activity in non-linear neural networks obeying a deterministic dynamics in continuous time; Part V. The Cerebellum and the Hippocampus: 24. Computer simulation of the cerebellar cortex compartment with a special reference to the Purkinje cell dendrite structure; 25. Modeling the electrical behaviour of cortical neurons - simulation of hippocampal pyramidal cells; Part VI. Olfaction, Vision and Cognition: 26. Neural computations and neural systems; 27. development of feature-analyzing cells and their columnar organisation 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; Part VII. Applications to Experiment, Communication and Control: 32. Computer-aid design of neurobiological experiments; 33. Simulation of the prolactin level fluctuations during pseudopregnancy in rats; 34. Applications of biological intelligence to command, control and communications; 35. Josin's computational system for use as a research tool; Author index; Subject index.
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