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 (hip...
| Otros Autores: | |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Hoboken, NJ :
John Wiley & Sons, Inc
2018.
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| Edición: | 1st ed |
| Colección: | Wiley ebooks.
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| Acceso en línea: | Conectar con la versión electrónica |
| Ver en Universidad de Navarra: | https://innopac.unav.es/record=b40622095*spi |
Tabla de Contenidos:
- 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 Approximations for Understanding Intellectual Disability in Down Syndrome; Future Directions; Concluding Remarks; Acknowledgments; References; Chapter 3: Computational Psychiatry; Introduction; Computational Modeling of Mood Disorders; The Function of Mood and its Relation to Behavior; Bayesian Inference and Hierarchical Models; Schizophrenia, Precision, and Inference; Aberrant Salience and Psychosis; Computational Phenotyping Using Social Games; Summary; References.
- Chapter 4: Computational Models of Post-traumatic Stress Disorder (PTSD)Introduction; Models of Fear Conditioning; Limitations and Future Directions; Models of Changes in Arousal and Reactivity; Limitations and Future Directions; Models of Avoidance; Limitations and Future Directions; Models of Changes in Cognition and Mood; Limitations and Future Directions; Models of Intrusive Recollection; Limitations and Future Directions; Conclusions; References; Chapter 5: Reward Processing in Depression; Introduction; The Computational Approach and its Merits; Depression and Reinforcement Learning.
- Depression and LikingDepression and Wanting; Depression and Model-based RL; Related Findings in Neuroeconomics and Quantum Decision Theory; Implications and Future Directions; References; Chapter 6: Neurocomputational Models of Schizophrenia; Introduction; Models of Cognition in Schizophrenia; Models of Schizophrenia Symptoms; Models of Pharmacological and Nonpharmacological Treatment of Schizophrenia; Conclusions; References; Chapter 7: Oscillatory Dynamics of Brain Microcircuits; Introduction; Oscillatory Brain Microcircuits-Modeling Perspectives.
