Pattern Analysis of the Human Connectome

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 ca...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Hu, Dewen (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Zeng, Ling-Li (http://id.loc.gov/vocabulary/relators/aut)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Singapore : Springer Singapore : Imprint: Springer, 2019.
Έκδοση:1st ed. 2019.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • Introduction
  • Multivariate pattern analysis of whole-brain functional connectivity in major depression
  • Discriminative analysis of nonlinear functional connectivity in schizophrenia
  • Predicting individual brain maturity using window-based dynamic functional connectivity
  • Locally linear embedding of functional connectivity for classification
  • Locally linear embedding of anatomical connectivity for classification
  • Locality preserving projection of functional connectivity for regression
  • Intrinsic discriminant analysis of functional connectivity for multi-class classification
  • Sparse representation of dynamic functional connectivity in depression
  • Low-rank learning of functional connectivity reveals neural traits of individual differences
  • Multi-task learning of structural MRI for multi-site classification
  • Deep discriminant auto-encoder network for multi-site fMRI classification.