Connectomics, Wu, Guorong

Connectomics: Methods, Mathematical Models and Applications is unique in combining a broad introduction to methods in connectomics with neuro- applications. In Part 1 the book explains the importance of connectomics using brain connectivity maps and then outlines the historical advancements in connectivity analysis, showing how these are related to imaging modalities such as diffusion and functional MRI. It then summarizes connectivity analysis approaches that apply different mathematical modeling techniques, such as linear models with regularization, deep-learning models, and graph models.

In part 2 the book describes state-of-the-art research that applies brain connectivity analysis techniques to a broad range of neurological and psychiatric disorders (Alzheimers, epilepsy, stroke, autism, Parkinsons, traumatic brain injury, drug or alcohol addiction, depression, bipolar, and schizophrenia), brain finger-print applications, speech-language assessments, cognitive assessment, as well as how the connectome can be used to predict demographic information (such as age, gender, or race).

With this book the reader will learn:

• The historical development of connectomics together with state-of-the-art methods
• Basic mathematical principles underlying connectomics.
• How connectomics is applied to a wide range of neuro-applications.

This book is an ideal reference for researchers and graduate students in computer science, data science, computational neuroscience, computational physics or mathematics who need to understand how computational models derived from brain connectivity data are being used in clinical applications, as well as neuroscientists and medical researchers wanting an overview of the technical methods.

• Combines connectomics methods with relevant and interesting neuro-applications
• Appeals to researchers in a wide range of disciplines: computer science, engineering, data science, mathematics, computational physics, computational neuroscience, as well as neuroscience and medical researchers interested in the technical methods of connectomics
• Includes a mathematics primer that formulates connectomics from an applied point-of-view, avoiding a difficult to understand theoretical perspective
• An introduction to popular machine learning techniques that enable diagnostic values to connectomics Information on publically available software tools that are used to construct, analyze, and visualize connectome data
• Lists of publically available neuro-imaging datasets that can be used to construct structural and functional connectomes