Imbalance of functional connectivity and temporal entropy in resting-state networks in Autism Spectrum Disorder: A machine learning approach

Authors

Robert X. Smith, Washington University School of Medicine in St. Louis
Kay Jann, University of Southern California
Mirella Dapretto, University of California, Los Angeles
Danny J.J. Wang, University of Southern California

Journal

Frontiers in Neuroscience

Publication Date

2018

Volume

12

Inclusive Pages

869

Document Type

Open Access Publication

DOI

10.3389/fnins.2018.00869

Rights and Permissions

Smith RX, Jann K, Dapretto M and Wang DJJ (2018) Imbalance of Functional Connectivity and Temporal Entropy in Resting-State Networks in Autism Spectrum Disorder: A Machine Learning Approach. Front. Neurosci. 12:869. doi: 10.3389/fnins.2018.00869 © 2018 Smith, Jann, Dapretto and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

Recommended Citation

Smith, Robert X.; Jann, Kay; Dapretto, Mirella; and Wang, Danny J.J., "Imbalance of functional connectivity and temporal entropy in resting-state networks in Autism Spectrum Disorder: A machine learning approach." Frontiers in Neuroscience. 12, 869. (2018).
https://digitalcommons.wustl.edu/open_access_pubs/7363