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Neuroimage. 2020 May 1;211:116621. doi: 10.1016/j.neuroimage.2020.116621. Epub 2020 Feb 10.

TbCAPs: A toolbox for co-activation pattern analysis.

Author information

1
Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Department of Radiology and Medical Informatics, University of Geneva (UNIGE), Geneva, Switzerland. Electronic address: thomas.bolton@epfl.ch.
2
Centre Hospitalier Universitaire Bicêtre, Service de Neurochirurgie, Paris, France; Sorbonne Université, Faculté de Médecine, Paris, France; Lausanne University (UNIL), Faculty of Biology and Medicine (FBM), Lausanne, Switzerland; Centre Hospitalier Universitaire Vaudois (CHUV), Neurosurgery Service and Gamma Knife Center, Lausanne, Switzerland.
3
Program for Sustainable Development of Mental Health, University of Zurich, Zurich, Switzerland.
4
Department of Neuroscience, University of Geneva (UNIGE), Geneva, Switzerland.
5
Laboratory of Cognitive Neuroscience, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
6
Developmental Imaging and Psychopathology Laboratory, Office Médico-Pédagogique, Department of Psychiatry, University of Geneva (UNIGE), Geneva, Switzerland.
7
Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
8
Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Department of Radiology and Medical Informatics, University of Geneva (UNIGE), Geneva, Switzerland.

Abstract

Functional magnetic resonance imaging provides rich spatio-temporal data of human brain activity during task and rest. Many recent efforts have focussed on characterising dynamics of brain activity. One notable instance is co-activation pattern (CAP) analysis, a frame-wise analytical approach that disentangles the different functional brain networks interacting with a user-defined seed region. While promising applications in various clinical settings have been demonstrated, there is not yet any centralised, publicly accessible resource to facilitate the deployment of the technique. Here, we release a working version of TbCAPs, a new toolbox for CAP analysis, which includes all steps of the analytical pipeline, introduces new methodological developments that build on already existing concepts, and enables a facilitated inspection of CAPs and resulting metrics of brain dynamics. The toolbox is available on a public academic repository at https://c4science.ch/source/CAP_Toolbox.git. In addition, to illustrate the feasibility and usefulness of our pipeline, we describe an application to the study of human cognition. CAPs are constructed from resting-state fMRI using as seed the right dorsolateral prefrontal cortex, and, in a separate sample, we successfully predict a behavioural measure of continuous attentional performance from the metrics of CAP dynamics (R ​= ​0.59).

KEYWORDS:

Attention; Co-activation pattern analysis; Continuous performance; Dynamic functional connectivity; Frame-wise analysis; Open source software; Task-positive network

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