Alzheimer S Disease Biology Biophysics And Computational Models

Alzheimer's disease (AD) is the leading cause of dementia and, unfortunately, remains incurable. The social, emotional and financial implications of AD are immeasurable, and about 47 million people worldwide are affected by AD or other forms of dementia. As lifespans are improved by healthcare systems worldwide, age-associated neurodegenerative diseases are imposing an increasing challenge to science. It is becoming imperative for us to understand the causes of these diseases, AD in particular, at molecular and cellular levels. Starting with the broader picture from a biological perspective, this book takes the reader through fascinating dynamics within and outside of neurons in the brain.Alzheimer's Disease: Biology, Biophysics and Computational Models helps the reader to understand AD from mechanistic and biochemical perspectives at intra- and inter-cellular levels. It focuses on biochemical pathways and modeling associated with AD. Some of the recent research on biophysics and computational models related to AD are explained using context-driven computational and mathematical modeling and essential biology is discussed to understand the modeling research.

This book demonstrates the power of mathematical thinking in understanding the biological complexity that exists within the brain. It looks at the latest research on modelling of biochemical pathways within synapses, and provides a clear background for the study of mathematical models related to systems biology. Discussion then focusses on developments in computational models based on networks linked to synaptic plasticity. The models are used to understand memory formation and impairment and they provide a mathematical basis for memory research. Computational Systems Biology of Synaptic Plasticity is a valuable source of knowledge to postgraduate students and researchers in computational systems biology, and as a reference book for various techniques that are needed in modelling biological processes.

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.

This is a student text, introducing the scope and problems of a new scientific discipline - Computational Neurogenetic Modeling (CNGM). CNGM is concerned with the study and development of dynamic neuronal models for modeling brain functions with respect to genes and dynamic interactions between genes. These include neural network models and their integration with gene network models. This new area brings together knowledge from various scientific disciplines.

This is a student text, introducing the scope and problems of a new scientific discipline - Computational Neurogenetic Modeling (CNGM). CNGM is concerned with the study and development of dynamic neuronal models for modeling brain functions with respect to genes and dynamic interactions between genes. These include neural network models and their integration with gene network models. This new area brings together knowledge from various scientific disciplines.

Provides a definitive overview of the complex ecosystem facilitating Alzheimer's Disease drug research and development. Demonstrates a drug's journey from in the lab, clinical trial testing, regulatory review, and marketing by pharmaceutical companies. Details the use of artificial intelligence, clinical trial management, and financing models.