Connectomics

Connectomics: Applications to Neuroimaging is unique in presenting the frontier of neuro-applications using brain connectomics techniques. The book describes state-of-the-art research that applies brain connectivity analysis techniques to a broad range of neurological and psychiatric disorders (Alzheimer's, epilepsy, stroke, autism, Parkinson's, drug or alcohol addiction, depression, bipolar, and schizophrenia), brain fingerprint applications, speech-language assessments, and cognitive assessment.
With this book the reader will learn:

- Basic mathematical principles underlying connectomics
- How connectomics is applied to a wide range of neuro-applications
- What is the future direction of connectomics techniques. 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.
Features:

- Combines connectomics methods with relevant and interesting neuro-applications
- Covers most of the hot topics in neuroscience and clinical areas
- 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
- Combines connectomics methods with relevant and interesting neuro-applications
- Presents information that will appeal to researchers in a wide range of disciplines, including computer science, engineering, data science, mathematics, computational physics, computational neuroscience, and more
- Includes a mathematics primer that formulates connectomics from an applied point-of-view, thus avoiding difficult to understand theoretical perspective
- Lists publicly available neuro-imaging datasets that can be used to construct structural and functional connectomes