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Exploring Associators in Computational Neuroscience: Plasticity Insights

Learn about structural and functional plasticity mechanisms, Hebbian learning, synaptic plasticity types, and more in computational neuroscience. Discover how synaptic plasticity shapes neural networks with practical examples. 8

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Exploring Associators in Computational Neuroscience: Plasticity Insights

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  1. Chapter 4: Associators and synaptic plasticity Fundamentals of Computational Neuroscience Dec 09

  2. Types of plasticity • Structural plasticity is the mechanism describing the generation of new connections and thereby redefining the topology of the network. • Functional plasticity is the mechanism of changing the strength values of existing connections.

  3. Hebbian plasticity "When an axon of a cell A is near enough to excite cell B or repeatedly or persistently takes part in firing it, some growth or metabolic change takes place in both cells such that A's efficiency, as one of the cells firing B, is increased." Donald O. Hebb, The organization of behavior, 1949 see also Sigmund Freud, Law of association by simultaneity, 1888 Donald Hebb

  4. Association

  5. Learning example

  6. Features of associators and Hebbian learning • Pattern completion and generalization • Prototypes and extraction of central tendencies • Graceful degradation and fault tolerance

  7. Classical LTP/LTD

  8. Synaptic neurotransmitter release probability

  9. A. Spike timing dependent plasticity (STDP)

  10. The calcium hypothesis and modeling chemical pathways

  11. Mathematical formulation of Hebbian plasticity

  12. Hebbian learning in population and rate models Eduardo Caianiello

  13. Synaptic weighting and weight distributions after Song, Miller and Abbott 2000

  14. Hebbian rate rule on random patterns

  15. Synaptic scaling and PCA

  16. Further readings

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