Details

Computational Models of Brain and Behavior


Computational Models of Brain and Behavior


1. Aufl.

von: Ahmed A. Moustafa

142,99 €

Verlag: Wiley-Blackwell
Format: EPUB
Veröffentl.: 18.09.2017
ISBN/EAN: 9781119159186
Sprache: englisch
Anzahl Seiten: 584

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Beschreibungen

<p><b>A comprehensive</b><b> Introduction to the world of brain and behavior computational models</b></p> <p>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).</p> <p><i>Computational Models of Brain and Behavior</i> 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.</p> <ul> <li>Covers computational approximations to intellectual disability in down syndrome</li> <li>Discusses computational models of pharmacological and immunological treatment in Alzheimer's disease</li> <li>Examines neural circuit models of serotonergic system (from microcircuits to cognition)</li> <li>Educates on information theory, memory, prediction, and timing in associative learning </li> </ul> <p><i>Computational Models of Brain and Behavior</i> is written for advanced undergraduate, Master's and PhD-level students—as well as researchers involved in computational neuroscience modeling research.</p>
<p>Notes on Contributors ix</p> <p>Introduction xxi</p> <p><b>Part I Models of Brain Disorders 1</b></p> <p>1 A Computational Model of Dyslexics’ Perceptual Difficulties as Impaired Inference of Sound Statistics 3<br /><i>Sagi Jaffe-Dax, Ofri Raviv, Yonatan Loewenstein, and Merav Ahissar</i></p> <p>2 Computational Approximations to Intellectual Disability in Down Syndrome 15<br /><i>Ángel E. Tovar, Ahmed A. Moustafa, and Natalia Arias-Trejo</i></p> <p>3 Computational Psychiatry 29<br /><i>Robb B. Rutledge and Rick A. Adams</i></p> <p>4 Computational Models of Post-traumatic Stress Disorder (PTSD) 43<br /><i>Milen L. Radell, Catherine E. Myers, Jony Sheynin, and Ahmed A. Moustafa</i></p> <p>5 Reward Processing in Depression 57</p> <p>The Computational Approach<br /><i>Chong Chen and Taiki Takahashi</i></p> <p>6 Neurocomputational Models of Schizophrenia 73<br /><i>Ahmed A. Moustafa, B³a¿ej Misiak, and Dorota Frydecka</i></p> <p>7 Oscillatory Dynamics of Brain Microcircuits 85</p> <p>Modeling Perspectives and Neurological Disease Considerations<br /><i>Frances K. Skinner and Alexandra Pierri Chatzikalymniou</i></p> <p>8 Computational Models of Pharmacological and Immunological Treatment in Alzheimer’s Disease 99<br /><i>Vassilis Cutsuridis and Ahmed A. Moustafa</i></p> <p>9 Modeling Deep Brain Stimulation for Parkinson’s Disease 109</p> <p>Volume Conductor, Network, and Mean-Field Models<br /><i>Madeleine M. Lowery</i></p> <p>10 The Development of Medications for Parkinson’s Disease Using Computational Modeling 125<br /><i>Mubashir Hassan and Ahmed A. Moustafa</i></p> <p>11 Multiscale Computer Modeling of Epilepsy 139<br /><i>M. Sanjay, Samuel A. Neymotin, Srinivasa B. Krothapalli, and William W. Lytton</i></p> <p><b>Part II Neural Models of Behavioral Processes 151</b></p> <p>12 Simple Models of Sensory Information Processing 153<br /><i>Danke Zhang, Malte J. Rasch, and Si Wu</i></p> <p>13 Motion Detection 171<br />An Artificial Recurrent Neural Network Approach<br /><i>Jeroen Joukes and Bart Krekelberg</i></p> <p>14 Computation in the Olfactory System 185<br /><i>Christiane Linster</i></p> <p>15 Computational Models of Olfaction in Fruit Flies 199<br /><i>Ankur Gupta, Faramarz Faghihi, and Ahmed A. Moustafa</i></p> <p>16 Multisensory Integration 215</p> <p>How the Brain Combines Information Across the Senses<br /><i>Ryan L. Miller and Benjamin A. Rowland</i></p> <p>17 Computational Models in Social Neuroscience 229<br /><i>Jin Hyun Cheong, Eshin Jolly, Sunhae Sul, and Luke J. Chang</i></p> <p>18 Sleep is For the Brain 245</p> <p>Contemporary Computational Approaches in the Study of Sleep and Memory and a Novel “Temporal Scaffolding” Hypothesis<br /><i>Itamar Lerner</i></p> <p>19 Models of Neural Homeostasis 257<br /><i>Hazem Toutounji</i></p> <p><b>Part III Models of Brain Regions and Neurotransmitters 271</b></p> <p>20 Striatum 273</p> <p>Structure, Dynamics, and Function<br /><i>Jyotika Bahuguna and Arvind Kumar</i></p> <p>21 Amygdala Models 285<br /><i>Vinay Guntu, Feng Feng, Adel Alturki, Ajay Nair, Pranit Samarth, and Satish S. Nair</i></p> <p>22 Cerebellum and its Disorders 303</p> <p>A Review of Perspectives from Computational Neuroscience<br /><i>Shyam Diwakar and Ahmed A. Moustafa</i></p> <p>23 Models of Dynamical Synapses and Cortical Development 321<br /><i>Radwa Khalil, Marie Z. Moftah, Marc Landry, and Ahmed A. Moustafa</i></p> <p>24 Computational Models of Memory Formation in</p> <p>Healthy and Diseased Microcircuits of the Hippocampus 333<br /><i>Vassilis Cutsuridis</i></p> <p>25 Episodic Memory and the Hippocampus 345<br /><i>Naoyuki Sato</i></p> <p>26 How Do We Navigate Our Way to Places? 357</p> <p>Developing a New Model to Study Place Field Formation in Hippocampus Including the Role of Astrocytes<br /><i>Fariba Bahrami and Shiva Farashahi</i></p> <p>27 Models of Neuromodulation 373<br /><i>Michael C. Avery and Jeffrey L. Krichmar</i></p> <p>28 Neural Circuit Models of the Serotonergic System 389</p> <p>From Microcircuits to Cognition<br /><i>Pragathi Priyadharsini Balasubramani, V. Srinivasa Chakravarthy, KongFatt Wong-Lin, Da-Hui Wang, Jeremiah Y. Cohen, Kae Nakamura, and Ahmed A. Moustafa</i></p> <p><b>Part IV Neural Modeling Approaches 401</b></p> <p>29 A Behavioral Framework for Information Representation in the Brain 403<br /><i>Frédéric Alexandre</i></p> <p>30 Probing Human Brain Function with Artificial Neural Networks 413<br /><i>Umut Güçlü and Marcel van Gerven</i></p> <p>31 Large-scale Computational Models of Ongoing Brain Activity 425<br /><i>Tristan T. Nakagawa, Mohit H. Adhikari, and Gustavo Deco</i></p> <p>32 Optimizing Electrical Stimulation for Closed-loop Control of Neural Ensembles 439</p> <p>A Review of Algorithms and Applications<br /><i>Seif Eldawlatly</i></p> <p>33 Complex Probabilistic Inference 453</p> <p>From Cognition to Neural Computation<br /><i>Samuel J. Gershman and Jeffrey M. Beck</i></p> <p>34 A Flexible and Efficient Hierarchical Bayesian Approach to the Exploration of Individual Differences in Cognitive-model-based Neuroscience 467<br /><i>Alexander Ly, Udo Boehm, Andrew Heathcote, Brandon M. Turner, Birte Forstmann, Maarten Marsman, and Dora Matzke</i></p> <p>35 Information Theory, Memory, Prediction, and Timing in Associative Learning 481<br /><i>Jason T. Wilkes and C. R. Gallistel</i></p> <p>36 The Utility of Phase Models in Studying Neural Synchronization 493<br /><i>Youngmin Park, Stewart A. Heitmann, and G. Bard Ermentrout</i></p> <p>37 Phase Oscillator Network Models of Brain Dynamics 505<br /><i>Carlo R. Laing</i></p> <p>38 The Neuronal Signal and Its Models 519<br /><i>Igor Palmieri, Luiz H. A. Monteiro, and Maria D. Miranda</i></p> <p>39 History Dependent Neuronal Activity Modeled with Fractional Order Dynamics 531<br /><i>Seth H. Weinberg and Fidel Santamaria</i></p> <p>Index 549</p>
<p><b> DR. AHMED A. MOUSTAFA, PhD</b> 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 <i>Science, Proceedings of the National Academy of Science, Journal of Neuroscience,</i> and <i>Brain, Neuroscience and Biobehavioral Reviews. </i>
<p><b> A comprehensive introduction to the world of brain and behavior computational models </b> <p> 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). <p><i> Computational Models of Brain and Behavior</i> 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. <ul> <li>Covers computational approximations to intellectual disability in down syndrome</li> <li>Discusses computational models of pharmacological and immunological treatment in Alzheimer's disease</li> <li>Examines neural circuit models of serotonergic system (from microcircuits to cognition)</li> <li>Educates on information theory, memory, prediction, and timing in associative learning</li> </ul> <br> <p><i> Computational Models of Brain and Behavior</i> is written for advanced undergraduate and graduate students, and researchers involved in computational neuroscience modeling research.

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