Invertebrate Learning and Memory: Chapter 7. Computational Analyses of Learning Networks (Handbook of Behavioral Neuroscience) Book PDF, ePub eBook

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Book Descriptions:
Mathematical models and computer simulations play important roles in developing a better understanding of learning and memory mechanisms. Models provide a means for representing, integrating, and manipulating diverse and complex empirical data. This chapter provides an overview of computational studies of learning and memory in invertebrates, including gene regulatory networks, signal transduction cascades, single neurons, and neural networks. These computational studies are helping to link specific component processes (e.g., changes in protein levels and phosphorylation, modulation of membrane conductances, synaptic plasticity, and network architecture) to features of nonassociative and associative learning. Moreover, these computational studies highlight mechanistic features that are common among different animals and common to multiple forms of learning and memory. Thus, computational analyses provide insights into the relationships among simple and complex forms of learning.

Invertebrate Learning and Memory: Chapter 7. Computational Analyses of Learning Networks (Handbook of Behavioral Neuroscience) by Douglas A. Baxter, Enrico Cataldo, John H. Byrne

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