{"product_id":"computational-models-of-brain-and-behavior-isbn-9781119159063","title":"Computational Models of Brain and Behavior","description":"\u003cp\u003e\u003cb\u003eA comprehensive\u003c\/b\u003e\u003cb\u003e Introduction to the world of brain and behavior computational models\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThis 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).\u003c\/p\u003e \u003cp\u003e\u003ci\u003eComputational Models of Brain and Behavior\u003c\/i\u003e 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.\u003c\/p\u003e \u003cul\u003e \u003cli\u003eCovers computational approximations to intellectual disability in down syndrome\u003c\/li\u003e \u003cli\u003eDiscusses computational models of pharmacological and immunological treatment in Alzheimer's disease\u003c\/li\u003e \u003cli\u003eExamines neural circuit models of serotonergic system (from microcircuits to cognition)\u003c\/li\u003e \u003cli\u003eEducates on information theory, memory, prediction, and timing in associative learning \u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003ci\u003eComputational Models of Brain and Behavior\u003c\/i\u003e is written for advanced undergraduate, Master's and PhD-level students—as well as researchers involved in computational neuroscience modeling research.\u003c\/p\u003e \u003cp\u003eNotes on Contributors ix\u003c\/p\u003e \u003cp\u003eIntroduction xxi\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart I Models of Brain Disorders 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1 A Computational Model of Dyslexics’ Perceptual Difficulties as Impaired Inference of Sound Statistics 3\u003cbr\u003e\u003ci\u003eSagi Jaffe-Dax, Ofri Raviv, Yonatan Loewenstein, and Merav Ahissar\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2 Computational Approximations to Intellectual Disability in Down Syndrome 15\u003cbr\u003e\u003ci\u003eÁngel E. Tovar, Ahmed A. Moustafa, and Natalia Arias-Trejo\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3 Computational Psychiatry 29\u003cbr\u003e\u003ci\u003eRobb B. Rutledge and Rick A. Adams\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4 Computational Models of Post-traumatic Stress Disorder (PTSD) 43\u003cbr\u003e\u003ci\u003eMilen L. Radell, Catherine E. Myers, Jony Sheynin, and Ahmed A. Moustafa\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5 Reward Processing in Depression 57\u003c\/p\u003e \u003cp\u003eThe Computational Approach\u003cbr\u003e\u003ci\u003eChong Chen and Taiki Takahashi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6 Neurocomputational Models of Schizophrenia 73\u003cbr\u003e\u003ci\u003eAhmed A. Moustafa, B³a¿ej Misiak, and Dorota Frydecka\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7 Oscillatory Dynamics of Brain Microcircuits 85\u003c\/p\u003e \u003cp\u003eModeling Perspectives and Neurological Disease Considerations\u003cbr\u003e\u003ci\u003eFrances K. Skinner and Alexandra Pierri Chatzikalymniou\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8 Computational Models of Pharmacological and Immunological Treatment in Alzheimer’s Disease 99\u003cbr\u003e\u003ci\u003eVassilis Cutsuridis and Ahmed A. Moustafa\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9 Modeling Deep Brain Stimulation for Parkinson’s Disease 109\u003c\/p\u003e \u003cp\u003eVolume Conductor, Network, and Mean-Field Models\u003cbr\u003e\u003ci\u003eMadeleine M. Lowery\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10 The Development of Medications for Parkinson’s Disease Using Computational Modeling 125\u003cbr\u003e\u003ci\u003eMubashir Hassan and Ahmed A. Moustafa\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11 Multiscale Computer Modeling of Epilepsy 139\u003cbr\u003e\u003ci\u003eM. Sanjay, Samuel A. Neymotin, Srinivasa B. Krothapalli, and William W. Lytton\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart II Neural Models of Behavioral Processes 151\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12 Simple Models of Sensory Information Processing 153\u003cbr\u003e\u003ci\u003eDanke Zhang, Malte J. Rasch, and Si Wu\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13 Motion Detection 171\u003cbr\u003eAn Artificial Recurrent Neural Network Approach\u003cbr\u003e\u003ci\u003eJeroen Joukes and Bart Krekelberg\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14 Computation in the Olfactory System 185\u003cbr\u003e\u003ci\u003eChristiane Linster\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e15 Computational Models of Olfaction in Fruit Flies 199\u003cbr\u003e\u003ci\u003eAnkur Gupta, Faramarz Faghihi, and Ahmed A. Moustafa\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e16 Multisensory Integration 215\u003c\/p\u003e \u003cp\u003eHow the Brain Combines Information Across the Senses\u003cbr\u003e\u003ci\u003eRyan L. Miller and Benjamin A. Rowland\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e17 Computational Models in Social Neuroscience 229\u003cbr\u003e\u003ci\u003eJin Hyun Cheong, Eshin Jolly, Sunhae Sul, and Luke J. Chang\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e18 Sleep is For the Brain 245\u003c\/p\u003e \u003cp\u003eContemporary Computational Approaches in the Study of Sleep and Memory and a Novel “Temporal Scaffolding” Hypothesis\u003cbr\u003e\u003ci\u003eItamar Lerner\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e19 Models of Neural Homeostasis 257\u003cbr\u003e\u003ci\u003eHazem Toutounji\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart III Models of Brain Regions and Neurotransmitters 271\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e20 Striatum 273\u003c\/p\u003e \u003cp\u003eStructure, Dynamics, and Function\u003cbr\u003e\u003ci\u003eJyotika Bahuguna and Arvind Kumar\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e21 Amygdala Models 285\u003cbr\u003e\u003ci\u003eVinay Guntu, Feng Feng, Adel Alturki, Ajay Nair, Pranit Samarth, and Satish S. Nair\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e22 Cerebellum and its Disorders 303\u003c\/p\u003e \u003cp\u003eA Review of Perspectives from Computational Neuroscience\u003cbr\u003e\u003ci\u003eShyam Diwakar and Ahmed A. Moustafa\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e23 Models of Dynamical Synapses and Cortical Development 321\u003cbr\u003e\u003ci\u003eRadwa Khalil, Marie Z. Moftah, Marc Landry, and Ahmed A. Moustafa\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e24 Computational Models of Memory Formation in\u003c\/p\u003e \u003cp\u003eHealthy and Diseased Microcircuits of the Hippocampus 333\u003cbr\u003e\u003ci\u003eVassilis Cutsuridis\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e25 Episodic Memory and the Hippocampus 345\u003cbr\u003e\u003ci\u003eNaoyuki Sato\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e26 How Do We Navigate Our Way to Places? 357\u003c\/p\u003e \u003cp\u003eDeveloping a New Model to Study Place Field Formation in Hippocampus Including the Role of Astrocytes\u003cbr\u003e\u003ci\u003eFariba Bahrami and Shiva Farashahi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e27 Models of Neuromodulation 373\u003cbr\u003e\u003ci\u003eMichael C. Avery and Jeffrey L. Krichmar\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e28 Neural Circuit Models of the Serotonergic System 389\u003c\/p\u003e \u003cp\u003eFrom Microcircuits to Cognition\u003cbr\u003e\u003ci\u003ePragathi Priyadharsini Balasubramani, V. Srinivasa Chakravarthy, KongFatt Wong-Lin, Da-Hui Wang, Jeremiah Y. Cohen, Kae Nakamura, and Ahmed A. Moustafa\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart IV Neural Modeling Approaches 401\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e29 A Behavioral Framework for Information Representation in the Brain 403\u003cbr\u003e\u003ci\u003eFrédéric Alexandre\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e30 Probing Human Brain Function with Artificial Neural Networks 413\u003cbr\u003e\u003ci\u003eUmut Güçlü and Marcel van Gerven\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e31 Large-scale Computational Models of Ongoing Brain Activity 425\u003cbr\u003e\u003ci\u003eTristan T. Nakagawa, Mohit H. Adhikari, and Gustavo Deco\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e32 Optimizing Electrical Stimulation for Closed-loop Control of Neural Ensembles 439\u003c\/p\u003e \u003cp\u003eA Review of Algorithms and Applications\u003cbr\u003e\u003ci\u003eSeif Eldawlatly\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e33 Complex Probabilistic Inference 453\u003c\/p\u003e \u003cp\u003eFrom Cognition to Neural Computation\u003cbr\u003e\u003ci\u003eSamuel J. Gershman and Jeffrey M. Beck\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e34 A Flexible and Efficient Hierarchical Bayesian Approach to the Exploration of Individual Differences in Cognitive-model-based Neuroscience 467\u003cbr\u003e\u003ci\u003eAlexander Ly, Udo Boehm, Andrew Heathcote, Brandon M. Turner, Birte Forstmann, Maarten Marsman, and Dora Matzke\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e35 Information Theory, Memory, Prediction, and Timing in Associative Learning 481\u003cbr\u003e\u003ci\u003eJason T. Wilkes and C. R. Gallistel\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e36 The Utility of Phase Models in Studying Neural Synchronization 493\u003cbr\u003e\u003ci\u003eYoungmin Park, Stewart A. Heitmann, and G. Bard Ermentrout\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e37 Phase Oscillator Network Models of Brain Dynamics 505\u003cbr\u003e\u003ci\u003eCarlo R. Laing\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e38 The Neuronal Signal and Its Models 519\u003cbr\u003e\u003ci\u003eIgor Palmieri, Luiz H. A. Monteiro, and Maria D. Miranda\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e39 History Dependent Neuronal Activity Modeled with Fractional Order Dynamics 531\u003cbr\u003e\u003ci\u003eSeth H. Weinberg and Fidel Santamaria\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eIndex 549\u003c\/p\u003e   \u003cp\u003e\u003cb\u003e DR. AHMED A. MOUSTAFA, PhD\u003c\/b\u003e is a Senior Lecturer in Cognitive and Behavioral Neuroscience at the MARCS Institute for Brain, Behavior, and Development, School of Social Sciences and Psychology, Western Sydney University. He has published more than 100 papers in high-ranking journals including \u003ci\u003eScience, Proceedings of the National Academy of Science, Journal of Neuroscience,\u003c\/i\u003e and \u003ci\u003eBrain, Neuroscience and Biobehavioral Reviews. \u003c\/i\u003e     \u003c\/p\u003e\u003cp\u003e\u003cb\u003e A comprehensive introduction to the world of brain and behavior computational models \u003c\/b\u003e  \u003c\/p\u003e\u003cp\u003e This unique resource 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).   \u003c\/p\u003e\u003cp\u003e\u003ci\u003e Computational Models of Brain and Behavior\u003c\/i\u003e is divided into four sections: (a) models of brain disorders; (b) neural models of behavioral processes; (c) models of 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.   \u003c\/p\u003e\u003cul\u003e \u003cli\u003eCovers computational approximations to intellectual disability in down syndrome\u003c\/li\u003e \u003cli\u003eDiscusses computational models of pharmacological and immunological treatment in Alzheimer's disease\u003c\/li\u003e \u003cli\u003eExamines neural circuit models of serotonergic system (from microcircuits to cognition)\u003c\/li\u003e \u003cli\u003eEducates on information theory, memory, prediction, and timing in associative learning\u003c\/li\u003e \u003c\/ul\u003e \u003cbr\u003e  \u003cp\u003e\u003ci\u003e Computational Models of Brain and Behavior\u003c\/i\u003e is written for advanced undergraduate and graduate students, and researchers involved in computational neuroscience modeling research.\u003c\/p\u003e","brand":"Wiley-Blackwell","offers":[{"title":"Default Title","offer_id":47988967014629,"sku":"NP9781119159063","price":170.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781119159063.jpg?v=1761782243","url":"https:\/\/k12savings.com\/es\/products\/computational-models-of-brain-and-behavior-isbn-9781119159063","provider":"K12savings","version":"1.0","type":"link"}