Computational models of brain and behavior

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 syndrome -Discusses computational models of pharmacological and immunological treatment in Alzheimer's disease -Examines 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.

Cover; Title Page; Copyright; Contents; Notes on Contributors; Acknowledgment; Introduction; Computational Models of Brain and Behavior; Part 1 Models of Brain Disorders; Models of psychiatric disorders; Models of neurological disorders; Part 2 Neural Models of Behavioral Processes; Part 3 Models of Brain Regions and Neurotransmitters; Models of brain areas; Models of neurotransmitters; Part 4 Neural Modeling Approaches; Higher-level models; Lower-level models; Part I: Models of Brain Disorders.

Chapter 1: A Computational Model of Dyslexics' Perceptual Difficulties as Impaired Inference of Sound StatisticsIntroduction-Contraction Bias in Simple Discrimination Tasks; Contraction Bias-a Simple Experimental Measure of Context Effects; Dyslexia; The Magnitude of Contraction Bias is Smaller in Dyslexics than in Controls; The Implicit Memory Model (IMM) Account for the Contraction Bias; Dyslexics Underweight Previous Trials Given Their Internal Noise Level; General Discussion; References; Chapter 2: Computational Approximations to Intellectual Disability in Down Syndrome; Introduction.

Theories of Intellectual Disability and Atypical DevelopmentDown Syndrome; Computational Approximati…