A comparison of feature extraction methods for prediction of neuropsychological scores from functional connectivity data of stroke patients

A comparison of feature extraction methods for prediction of neuropsychological scores from functional connectivity data of stroke patients

Abstract Multivariate prediction of human behavior from resting state data is gaining increasing popularity in the neuroimaging community, with far-reaching translational implications in neurology and psychiatry. However, the high dimensionality of neuroimaging data increases the risk of overfitting...

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Bibliographic Details
Main Authors: Federico Calesella, Alberto Testolin, Michele De Filippo De Grazia, Marco Zorzi
Format: Article
Language:English
Published: SpringerOpen 2021-04-01
Series:Brain Informatics
Subjects:
Resting state networks
Functional connectivity
Machine learning
Feature extraction
Dimensionality reduction
Predictive modeling
Online Access:https://doi.org/10.1186/s40708-021-00129-1

Internet

https://doi.org/10.1186/s40708-021-00129-1

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