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Academic Press Connectome Analysis: Characterization, Methods, and Analysis

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Description

Connectome Analysis: Characterization, Methods, and Analysis is a comprehensive companion for the analysis of brain networks, or connectomes. The book provides sources of constituent structural and functional MRI signals, network construction and practices for analysis, cutting-edge methods that address the latest challenges in neuroscience, and the fundamentals of network theory in the context of giving practical methods for building connectomes for analysis. Emphasis is placed on quality control of the individual analysis steps. Subsequent chapters discuss networks in neuroscience in clinical and general populations, including how findings are related to underlying neurophysiology and neuropsychology. This book is aimed at students and early-career researchers in brain connectomics and neuroimaging who have a background in computer science, mathematics and physics, as well as more broadly to neuroscientists and psychologists who want to start incorporating connectomics into their research. Review Helps readers understand how to construct, assess and analyze brain networks (connectomes) About the Author Markus is a Marie-Curie Fellow PhD at the German Centre for Neurodegenerative Disease Bonn, Germany, Harvard Medical School, and Massachusetts General Hospital. He received his M.Sc. in Theoretical Physics from Aachen University in Germany and his Ph.D. in Brain Connectivity from King’s College in London. In the Rost Research Lab, Markus applies his theoretical background combined with his interest in neuroimage analysis across the life-span to further research to improve our understanding of stroke and the associated outcome for patients. In his current work, Markus promotes the use of clinical magnetic resonance images in large scale analyses. He is investigating different outcomes in stroke patients, aiming to understand and utilize the concept that some brains are seemingly more resilient to insults. In the future, his goal is the facilitation of translational research to the point where theoretical neuroimage analysis can be used to understand individual differences in patients. This will help support medical decision making and personalize treatment options for patients in order to improve their long-term outcome. Dr Tomoki Arichi MBChB FRCPCH PhDMBChB FRCPCH PhD is a MRC Clinician Scientist and Clinical Senior Lecturer in the Centre for the Developing Brain, King's College London. He received his PhD from Imperial College London in 2012, following the award of a Chain-Florey Fellowship from the MRC Clinical Sciences Centre. The work of his thesis focused on the optimisation of functional MRI techniques for studying activity in the newborn brain. He was appointed as an MRC Clinician Scientist in March 2017. Dr Arichi also holds an honorary position as a Consultant in Paediatric Neurodisability in the Evelina London Children's Hospital. His clinical work is focused on the early identification and resulting management of the disabilities associated with perinatal brain injury. His current work aims to apply non-invasive imaging techniques (EEG, functional MRI and simultaneous EEG-fMRI, motion-tracking methods) to characterise the development of functional activity in the human brain, during fetal and preterm life and following brain injury. This is particularly focused on understanding how early somatosensory and motor processing relates to brain development and behaviour. He is also aiming to gain a deeper understanding of the underlying biophysics of the fMRI signal in the newborn brain. He also holds a visiting position in the Human Robotics group at Imperial College London, where they are developing novel tools for use in the MRI scanner and automated rehabilitative strategies for young infants who have suffered brain injury. Ai Wern Chung PhD is a Research Fellow in the Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, USA.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
16 June 2023
Listed Since
25 January 2022

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