Novel Applications Of Bayesian And Other Models In Translational Neuroscience
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Novel Applications of Bayesian and Other Models in Translational Neuroscience
Author: Reza Rastmanesh
language: en
Publisher: Frontiers Media SA
Release Date: 2024-05-06
It has been proposed that the brain works in a Bayesian manner, and based on the free-energy principle, the brain's main function is to reduce environmental uncertainty; this is a proposed model as a universal principle governing adaptive brain function and structure. There are many pathophysiological, and clinical observations that can be easily explained by predictive Bayesian brain models. However, the novel applications of Bayesian models in translational neuroscience has been understudied and underreported. For example, variational Bayesian mixed-effects inference has been successfully tested for classification studies. A multi-task Bayesian compressive sensing approach to simultaneously estimate the full posterior of the CSA-ODF and diffusion-weighted volumes from multi-shell HARDI acquisitions has been recently publishe
Translational Neuroscience
Author: James Elmer Barrett
language: en
Publisher: Cambridge University Press
Release Date: 2012-06-28
Translational neuroscience is at the heart of clinical advancement in the fields of psychiatry, neurology and neurodevelopmental disorders. Written and edited by leading scientists and clinicians, this is a comprehensive and authoritative analysis of this emerging strategy for developing more effective treatments for brain disorders. Introductory chapters bring together perspectives from both academia and industry, while subsequent sections focus on disease groups, including bipolar disorder and depression, attention deficit hyperactivity disorder, substance abuse, autism, Alzheimer's disease, pain, epilepsy, Parkinson's disease and multiple sclerosis. Each section includes topical introductory and summary chapters, providing an overview and synthesis of the field. Translational Neuroscience: Applications in Psychiatry, Neurology, and Neurodevelopmental Disorders is an important text for clinicians, scientists and students in academic settings, government agencies and industry, as well as those working in the fields of public health and the behavioural sciences.
Computational and Network Modeling of Neuroimaging Data
Neuroimaging is witnessing a massive increase in the quality and quantity of data being acquired. It is widely recognized that effective interpretation and extraction of information from such data requires quantitative modeling. However, modeling comes in many diverse forms, with different research communities tackling different brain systems, different spatial and temporal scales, and different aspects of brain structure and function. Computational and Network Modeling of Neuroimaging Data provides an authoritative and comprehensive overview of the many diverse modeling approaches that have been fruitfully applied to neuroimaging data. This book gives an accessible foundation to the field of computational and network modeling of neuroimaging data and is suitable for graduate students, academic researchers, and industry practitioners who are interested in adopting or applying model-based approaches in neuroimaging. - Provides an authoritative and comprehensive overview of major modeling approaches to neuroimaging data - Written by experts, the book's chapters use a common structure to introduce, motivate, and describe a specific modeling approach used in neuroimaging - Gives insights into the similarities and differences across different modeling approaches - Analyses details of outstanding research challenges in the field