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...
| Main Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
Singapore
Springer Nature Singapore
2019, 2019
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| Edition: | 1st ed. 2019 |
| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- 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