TY - JOUR
T1 - A mathematical perspective on edge-centric brain functional connectivity
AU - Novelli, Leonardo
AU - Razi, Adeel
N1 - Funding Information:
Data used in the preparation of this work were obtained from the MGH-USC Human Connectome Project (HCP) database ( https://ida.loni.usc.edu/login.jsp ). The HCP project is supported by the National Institute of Dental and Craniofacial Research (NIDCR), the National Institute of Mental Health (NIMH) and the National Institute of Neurological Disorders and Stroke (NINDS). L.N. is funded by the Australian Research Council (Ref: DP200100757). A.R. is funded by the Australian Research Council (Refs: DE170100128 and DP200100757) and Australian National Health and Medical Research Council Investigator Grant (Ref: 1194910). A.R. is affiliated with The Wellcome Centre for Human Neuroimaging supported by core funding from Wellcome [203147/Z/16/Z]. A.R. is a CIFAR Azrieli Global Scholar in the Brain, Mind & Consciousness Programme. We thank Joseph Lizier, Ben Fulcher, James Mac Shine and Andrew Zalesky for their feedback on an earlier draft of this manuscript.
Funding Information:
Data used in the preparation of this work were obtained from the MGH-USC Human Connectome Project (HCP) database (https://ida.loni.usc.edu/login.jsp). The HCP project is supported by the National Institute of Dental and Craniofacial Research (NIDCR), the National Institute of Mental Health (NIMH) and the National Institute of Neurological Disorders and Stroke (NINDS). L.N. is funded by the Australian Research Council (Ref: DP200100757). A.R. is funded by the Australian Research Council (Refs: DE170100128 and DP200100757) and Australian National Health and Medical Research Council Investigator Grant (Ref: 1194910). A.R. is affiliated with The Wellcome Centre for Human Neuroimaging supported by core funding from Wellcome [203147/Z/16/Z]. A.R. is a CIFAR Azrieli Global Scholar in the Brain, Mind & Consciousness Programme. We thank Joseph Lizier, Ben Fulcher, James Mac Shine and Andrew Zalesky for their feedback on an earlier draft of this manuscript.
Publisher Copyright:
© 2022, The Author(s).
PY - 2022/5/16
Y1 - 2022/5/16
N2 - Edge time series are increasingly used in brain imaging to study the node functional connectivity (nFC) dynamics at the finest temporal resolution while avoiding sliding windows. Here, we lay the mathematical foundations for the edge-centric analysis of neuroimaging time series, explaining why a few high-amplitude cofluctuations drive the nFC across datasets. Our exposition also constitutes a critique of the existing edge-centric studies, showing that their main findings can be derived from the nFC under a static null hypothesis that disregards temporal correlations. Testing the analytic predictions on functional MRI data from the Human Connectome Project confirms that the nFC can explain most variation in the edge FC matrix, the edge communities, the large cofluctuations, and the corresponding spatial patterns. We encourage the use of dynamic measures in future research, which exploit the temporal structure of the edge time series and cannot be replicated by static null models.
AB - Edge time series are increasingly used in brain imaging to study the node functional connectivity (nFC) dynamics at the finest temporal resolution while avoiding sliding windows. Here, we lay the mathematical foundations for the edge-centric analysis of neuroimaging time series, explaining why a few high-amplitude cofluctuations drive the nFC across datasets. Our exposition also constitutes a critique of the existing edge-centric studies, showing that their main findings can be derived from the nFC under a static null hypothesis that disregards temporal correlations. Testing the analytic predictions on functional MRI data from the Human Connectome Project confirms that the nFC can explain most variation in the edge FC matrix, the edge communities, the large cofluctuations, and the corresponding spatial patterns. We encourage the use of dynamic measures in future research, which exploit the temporal structure of the edge time series and cannot be replicated by static null models.
UR - https://www.scopus.com/pages/publications/85130062371
U2 - 10.1038/s41467-022-29775-7
DO - 10.1038/s41467-022-29775-7
M3 - Article
C2 - 35577769
AN - SCOPUS:85130062371
SN - 2041-1723
VL - 13
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 2693
ER -