Abstract
Human beings have always speculated about the nature of things. These speculations have taken form as models. Though we cannot directly know the brain, models can approximate it. Therefore, neuroscience develops models of the brain. Two general categories of approach to neuroscience model making are covered. One is to start at the foundational units and build up from there (bottom-up) and the other is to begin by formulating a broad, general picture and then analyze down to the individual parts (top-down). Mathematics has been a helpful tool for working with the complex, multi-factored dynamic data the brain presents. Typically, in the Western social sciences, and especially in psychotherapy, verbal models are used to explain human individual, interpersonal, and group behavior. More recently, science has adopted sophisticated ways to model using mathematics as an alternative to verbal concepts. Chapter 6 describes the prominent neuroscience modeling methods in simple, straightforward terms that anyone can understand, including Bayesian inference, Stochastic estimation, optimal control, the Markov chain, and the Bellman equation. Some mathematically based models of the brain are also described such as connectionist models, tensor theories, and dynamical systems approaches. As models, technologies, and statistical methods improve, neuroscience forges ever deeper into the recesses of the brain to uncover its secrets and activate the vast potentials that lie hidden, just waiting to be discovered.
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© 2013 Springer Science+Business Media New York
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Simpkins, C.A., Simpkins, A.M. (2013). Modeling the Brain. In: Neuroscience for Clinicians. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-4842-6_6
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DOI: https://doi.org/10.1007/978-1-4614-4842-6_6
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Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-4841-9
Online ISBN: 978-1-4614-4842-6
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