Pattern Analysis of the Human Connectome

Ling-Li Zeng, Dewen Hu

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Springer Singapore img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Nichtklinische Fächer

Beschreibung

This book presents recent advances in pattern analysis of the human connectome. The human connectome, measured by magnetic resonance imaging at the macroscale, provides a comprehensive description of how brain regions are connected. Based on machine learning methods, multiviarate pattern analysis can directly decode psychological or cognitive states from brain connectivity patterns. Although there are a number of works with chapters on conventional human connectome encoding (brain-mapping), there are few resources on human connectome decoding (brain-reading). Focusing mainly on advances made over the past decade in the field of manifold learning, sparse coding, multi-task learning, and deep learning of the human connectome and applications, this book helps students and researchers gain an overall picture of pattern analysis of the human connectome. It also offers valuable insights for clinicians involved in the clinical diagnosis and treatment evaluation of neuropsychiatric disorders.

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Schlagwörter

Sparse coding, Human connectome, Deep learning, Manifold learning, Magnetic resonance imaging