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Computational Models of Brain and Behavior
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Computational Models of Brain and Behavior

Book Details

Format Hardback or Cased Book
ISBN-10 1119159067
ISBN-13 9781119159063
Publisher John Wiley and Sons Ltd
Imprint Wiley-Blackwell
Country of Manufacture SG
Country of Publication GB
Publication Date Nov 3rd, 2017
Print length 584 Pages
Weight 1,293 grams
Dimensions 25.70 x 18.50 x 2.80 cms
Ksh 23,550.00
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A comprehensive Introduction to the world of brain and behavior computational models This book provides a broad collection of articles covering different aspects of computational modeling efforts in psychology and neuroscience. Specifically, it discusses models that span different brain regions (hippocampus, amygdala, basal ganglia, visual cortex), different species (humans, rats, fruit flies), and different modeling methods (neural network, Bayesian, reinforcement learning, data fitting, and Hodgkin-Huxley models, among others). Computational Models of Brain and Behavior is divided into four sections: (a) Models of brain disorders; (b) Neural models of behavioral processes; (c) Models of neural processes, brain regions and neurotransmitters, and (d) Neural modeling approaches. It provides in-depth coverage of models of psychiatric disorders, including depression, posttraumatic stress disorder (PTSD), schizophrenia, and dyslexia; models of neurological disorders, including Alzheimer’s disease, Parkinson’s disease, and epilepsy; early sensory and perceptual processes; models of olfaction; higher/systems level models and low-level models; Pavlovian and instrumental conditioning; linking information theory to neurobiology; and more. Covers computational approximations to intellectual disability in down syndromeDiscusses computational models of pharmacological and immunological treatment in Alzheimer's diseaseExamines neural circuit models of serotonergic system (from microcircuits to cognition)Educates on information theory, memory, prediction, and timing in associative learning  Computational Models of Brain and Behavior is written for advanced undergraduate, Master's and PhD-level students—as well as researchers involved in computational neuroscience modeling research.

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