Computer Simulation in Brain Science

There has been an enormous increase in research activity aimed at elucidating the basis for cortical activity in the brain. Among modern techniques used in this area of scientific endeavour, few have proved as popular as computer simulation. Model neural networks are the subject of intense study, and some remarkable properties have already come to light: these networks are able to discriminate, remember and associate. Professor Cotterill has assembled leading experts in this burgeoning field to produce an exciting review of advances. The volume covers the creation of computer models of neural networks, and their use in the study 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.

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.