Producción CyT

Machine learning in connectomics: from representation learning to model fitting

Capítulo de Libro

Autoría:

FERRANTE, ENZO

Fecha:

2023

Editorial y Lugar de Edición:

Elsevier

Libro:

Connectome Analysis Characterization, Methods, and Analysis (pp. 267-283)
Elsevier

ISBN:

9780323852807

Resumen *

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. Información suministrada por el agente en SIGEVA

Palabras Clave

graphsmachine learningconnectiomics analysisfunctional mri