Computational Models of Brain and Behavior

  • ID: 4330155
  • Book
  • 584 Pages
  • John Wiley and Sons Ltd
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A comprehensive introduction to the world of brain and behavior computational models

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).

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 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 and graduate students, and researchers involved in computational neuroscience modeling research.

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Notes on Contributors ix

Introduction xxi

Part I Models of Brain Disorders 1

1 A Computational Model of Dyslexics’ Perceptual Difficulties as Impaired Inference of Sound Statistics 3Sagi Jaffe–Dax, Ofri Raviv, Yonatan Loewenstein, and Merav Ahissar

2 Computational Approximations to Intellectual Disability in Down Syndrome 15Ángel E. Tovar, Ahmed A. Moustafa, and Natalia Arias–Trejo

3 Computational Psychiatry 29Robb B. Rutledge and Rick A. Adams

4 Computational Models of Post–traumatic Stress Disorder (PTSD) 43Milen L. Radell, Catherine E. Myers, Jony Sheynin, and Ahmed A. Moustafa

5 Reward Processing in Depression 57

The Computational ApproachChong Chen and Taiki Takahashi

6 Neurocomputational Models of Schizophrenia 73Ahmed A. Moustafa, B³a¿ej Misiak, and Dorota Frydecka

7 Oscillatory Dynamics of Brain Microcircuits 85

Modeling Perspectives and Neurological Disease ConsiderationsFrances K. Skinner and Alexandra Pierri Chatzikalymniou

8 Computational Models of Pharmacological and Immunological Treatment in Alzheimer’s Disease 99Vassilis Cutsuridis and Ahmed A. Moustafa

9 Modeling Deep Brain Stimulation for Parkinson’s Disease 109

Volume Conductor, Network, and Mean–Field ModelsMadeleine M. Lowery

10 The Development of Medications for Parkinson’s Disease Using Computational Modeling 125Mubashir Hassan and Ahmed A. Moustafa

11 Multiscale Computer Modeling of Epilepsy 139M. Sanjay, Samuel A. Neymotin, Srinivasa B. Krothapalli, and William W. Lytton

Part II Neural Models of Behavioral Processes 151

12 Simple Models of Sensory Information Processing 153Danke Zhang, Malte J. Rasch, and Si Wu

13 Motion Detection 171
An Artificial Recurrent Neural Network ApproachJeroen Joukes and Bart Krekelberg

14 Computation in the Olfactory System 185Christiane Linster

15 Computational Models of Olfaction in Fruit Flies 199Ankur Gupta, Faramarz Faghihi, and Ahmed A. Moustafa

16 Multisensory Integration 215

How the Brain Combines Information Across the SensesRyan L. Miller and Benjamin A. Rowland

17 Computational Models in Social Neuroscience 229Jin Hyun Cheong, Eshin Jolly, Sunhae Sul, and Luke J. Chang

18 Sleep is For the Brain 245

Contemporary Computational Approaches in the Study of Sleep and Memory and a Novel “Temporal Scaffolding” HypothesisItamar Lerner

19 Models of Neural Homeostasis 257Hazem Toutounji

Part III Models of Brain Regions and Neurotransmitters 271

20 Striatum 273

Structure, Dynamics, and FunctionJyotika Bahuguna and Arvind Kumar

21 Amygdala Models 285Vinay Guntu, Feng Feng, Adel Alturki, Ajay Nair, Pranit Samarth, and Satish S. Nair

22 Cerebellum and its Disorders 303

A Review of Perspectives from Computational NeuroscienceShyam Diwakar and Ahmed A. Moustafa

23 Models of Dynamical Synapses and Cortical Development 321Radwa Khalil, Marie Z. Moftah, Marc Landry, and Ahmed A. Moustafa

24 Computational Models of Memory Formation in

Healthy and Diseased Microcircuits of the Hippocampus 333Vassilis Cutsuridis

25 Episodic Memory and the Hippocampus 345Naoyuki Sato

26 How Do We Navigate Our Way to Places? 357

Developing a New Model to Study Place Field Formation in Hippocampus Including the Role of AstrocytesFariba Bahrami and Shiva Farashahi

27 Models of Neuromodulation 373Michael C. Avery and Jeffrey L. Krichmar

28 Neural Circuit Models of the Serotonergic System 389

From Microcircuits to CognitionPragathi Priyadharsini Balasubramani, V. Srinivasa Chakravarthy, KongFatt Wong–Lin, Da–Hui Wang, Jeremiah Y. Cohen, Kae Nakamura, and Ahmed A. Moustafa

Part IV Neural Modeling Approaches 401

29 A Behavioral Framework for Information Representation in the Brain 403Frédéric Alexandre

30 Probing Human Brain Function with Artificial Neural Networks 413Umut Güçlü and Marcel van Gerven

31 Large–scale Computational Models of Ongoing Brain Activity 425Tristan T. Nakagawa, Mohit H. Adhikari, and Gustavo Deco

32 Optimizing Electrical Stimulation for Closed–loop Control of Neural Ensembles 439

A Review of Algorithms and ApplicationsSeif Eldawlatly

33 Complex Probabilistic Inference 453

From Cognition to Neural ComputationSamuel J. Gershman and Jeffrey M. Beck

34 A Flexible and Efficient Hierarchical Bayesian Approach to the Exploration of Individual Differences in Cognitive–model–based Neuroscience 467Alexander Ly, Udo Boehm, Andrew Heathcote, Brandon M. Turner, Birte Forstmann, Maarten Marsman, and Dora Matzke

35 Information Theory, Memory, Prediction, and Timing in Associative Learning 481Jason T. Wilkes and C. R. Gallistel

36 The Utility of Phase Models in Studying Neural Synchronization 493Youngmin Park, Stewart A. Heitmann, and G. Bard Ermentrout

37 Phase Oscillator Network Models of Brain Dynamics 505Carlo R. Laing

38 The Neuronal Signal and Its Models 519Igor Palmieri, Luiz H. A. Monteiro, and Maria D. Miranda

39 History Dependent Neuronal Activity Modeled with Fractional Order Dynamics 531Seth H. Weinberg and Fidel Santamaria

Index 549

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DR. AHMED A. MOUSTAFA, PhD 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 Science, Proceedings of the National Academy of Science, Journal of Neuroscience, and Brain, Neuroscience and Biobehavioral Reviews.

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