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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Global Signal Regression Strengthens Association between Resting-State Functional Connectivity and Behavior
Jingwei Li, Ru Kong, Raphaël Liégeois, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2019)
Open Access | Times Cited: 14

Showing 14 citing articles:

Resting brain dynamics at different timescales capture distinct aspects of human behavior
Raphaël Liégeois, Jingwei Li, Ru Kong, et al.
Nature Communications (2019) Vol. 10, Iss. 1
Open Access | Times Cited: 291
Individual-Specific Areal-Level Parcellations Improve Functional Connectivity Prediction of Behavior
Ru Kong, Qing Yang, Evan M. Gordon, et al.
Cerebral Cortex (2021) Vol. 31, Iss. 10, pp. 4477-4500
Open Access | Times Cited: 181
Predicting Alzheimer's disease progression using deep recurrent neural networks
Minh Nguyen, Tong He, Lijun An, et al.
NeuroImage (2020) Vol. 222, pp. 117203-117203
Open Access | Times Cited: 146
Determining the Hierarchical Architecture of the Human Brain Using Subject-Level Clustering of Functional Networks
Teddy J. Akiki, Chadi G. Abdallah
Scientific Reports (2019) Vol. 9, Iss. 1
Open Access | Times Cited: 88
On the intersection between data quality and dynamical modelling of large-scale fMRI signals
Kevin Aquino, Ben Fulcher, Stuart Oldham, et al.
NeuroImage (2022) Vol. 256, pp. 119051-119051
Open Access | Times Cited: 16
Determining the Hierarchical Architecture of the Human Brain Using Subject-Level Clustering of Functional Networks
Teddy J. Akiki, Chadi G. Abdallah
bioRxiv (Cold Spring Harbor Laboratory) (2018)
Open Access | Times Cited: 9
Provisioning a risk predictor model for Alzheimers disease using an improved deep network model
V. Murugesh, P. Janarthanan, A. Kavitha, et al.
Multimedia Tools and Applications (2023) Vol. 83, Iss. 11, pp. 33465-33488
Closed Access | Times Cited: 2
Predicting Alzheimer’s disease progression using deep recurrent neural networks
Minh Nguyen, Tong He, Lijun An, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2019)
Open Access | Times Cited: 5
Identifying and removing widespread signal deflections from fMRI data: Rethinking the global signal regression problem
Kevin Aquino, Ben Fulcher, Linden Parkes, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2019)
Open Access | Times Cited: 4
On the intersection between data quality and dynamical modelling of large-scale fMRI signals
Kevin Aquino, Ben Fulcher, Stuart Oldham, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2021)
Open Access | Times Cited: 3
Spontaneous brain activity, graph metrics, and head motion related to prospective post-traumatic stress disorder trauma-focused therapy response
Remko van Lutterveld, Tim Varkevisser, Karlijn Kouwer, et al.
Frontiers in Human Neuroscience (2022) Vol. 16
Open Access | Times Cited: 2
Individual-Specific fMRI-Subspaces Improve Functional Connectivity Prediction of Behavior
Rajan Kashyap, Ru Kong, Sagarika Bhattacharjee, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2019)
Open Access | Times Cited: 1
Faculty Opinions recommendation of Resting brain dynamics at different timescales capture distinct aspects of human behavior.
Lutz Jäncke
Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature (2019)
Open Access
A generic decision-making ability predicts psychopathology in adolescents and young adults and is reflected in distinct brain connectivity patterns
Michael Moutoussis, Benjamín Garzón, Sharon Neufeld, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2020)
Open Access
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