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Deep neural networks and kernel regression achieve comparable accuracies for functional connectivity prediction of behavior and demographics

  • Published:2020-02 Issue: Volume:206 Page:116276
  • ISSN:1053-8119
  • Container-title:NeuroImage
  • language:en
  • Short-container-title:NeuroImage

Author:

He Tong,Kong Ru,Holmes Avram J.,Nguyen Minh,Sabuncu Mert R.,Eickhoff Simon B.,Bzdok Danilo,Feng Jiashi,Yeo B.T. Thomas

Funder

Ministry of Education

National University of Singapore

NUS

SOM

NMRC

Singapore National Research Foundation

NRF

Center for Functional Neuroimaging Technologies

Athinoula A. Martinos Center for Biomedical Imaging

UK

NIH

McDonnell Center for Systems Neuroscience

Publisher

Elsevier BV

Subject

Cognitive Neuroscience,Neurology

Reference117 articles.

1. Image processing and Quality Control for the first 10,000 brain imaging datasets from UK Biobank;Alfaro-Almagro;Neuroimage,2018

2. The quest for identifiability in human functional connectomes;Amico;Sci. Rep.,2018

3. Single subject prediction of brain disorders in neuroimaging: promises and pitfalls;Arbabshirani;Neuroimage,2017

4. Abnormal functional connectivity of default mode sub-networks in autism spectrum disorder patients;Assaf;Neuroimage,2010

5. Convolutional neural network for reconstruction of 7T-like images from 3T MRI using appearance and anatomical features;Bahrami,2016
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