An information network flow approach for measuring functional connectivity and predicting behavior-Reference-Cited by-同舟云学术

An information network flow approach for measuring functional connectivity and predicting behavior

Published:2019-07-09 Issue:8 Volume:9 Page:
ISSN:2162-3279
Container-title:Brain and Behavior
language:en
Short-container-title:Brain Behav

Author:

Kumar Sreejan¹^ORCID,Yoo Kwangsun¹,Rosenberg Monica D.¹²,Scheinost Dustin³^ORCID,Constable R. Todd³⁴⁵,Zhang Sheng⁶,Li Chiang‐Shan R.⁴⁶⁷,Chun Marvin M.¹⁴⁷

Affiliation:

1. Department of Psychology Yale University New Haven Connecticut

2. Department of Psychology University of Chicago Chicago Illinois

3. Department of Radiology and Biomedical Imaging Yale School of Medicine New Haven Connecticut

4. Interdepartmental Neuroscience Program Yale University New Haven Connecticut

5. Department of Neurosurgery Yale School of Medicine New Haven Connecticut

6. Department of Psychiatry Yale School of Medicine New Haven Connecticut

7. Department of Neuroscience Yale School of Medicine New Haven Connecticut

Funder

National Science Foundation

National Institutes of Health

Publisher

Wiley

Subject

Behavioral Neuroscience

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/brb3.1346

Reference39 articles.

1. Small-World Brain Networks

2. Deligianni F. Robinson E. Beckmann C. F. Sharp D. Edwards A. D. &Rueckert D.(2011).Inference of functional connectivity from direct and indirect structural brain connections. In 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro (pp.849–852). IEEE.

3. Information theory in neuroscience

4. In the Zone or Zoning Out? Tracking Behavioral and Neural Fluctuations During Sustained Attention

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