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Connectomics
Applications to Neuroimaging
Provides insights into connectomics methods and their application to a variety of neuro and clinical applications
Brent C. Munsell (Edited by), Guorong Wu (Edited by), Leonardo Bonilha (Edited by), Paul Laurienti (Edited by)
9780128138380, Elsevier Science
Paperback, published 12 September 2018
233 pages
23.4 x 19 x 1.6 cm, 0.63 kg
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: 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:
1. Autism Spectrum Disorders: Unbiased Functional Connectomics Provide New Insights into a Multifaceted Neurodevelopmental Disorder
2. Insights Into Cognition from Network Science Analyses of Human Brain Functional Connectivity:Working Memory as a Test Case
3. Overlapping and Dynamic Networks of the Emotional Brain
4. The Uniqueness of the Individual Functional Connectome
5. Dysfunctional Brain Network Organization in Neurodevelopmental Disorders
6. Addiction: Informing Drug Abuse Interventions with Brain Networks
7. Connectivity and Dysconnectivity: A Brief History of Functional Connectivity Research in Schizophrenia and Future Directions
8. Genetics of Brain Networks and Connectivity
9. Characterizing Dynamic Functional Connectivity Using Data-Driven Approaches and its Application in the Diagnosis of Alzheimer’s Disease
10. Toward a more Integrative Cognitive Neuroscience of Episodic Memory
Subject Areas: Computer vision [UYQV]