title: Co-activation Probability Estimation (CoPE): An approach for modeling functional co-activation architecture based on neuroimaging coordinates.
abstract: Recent progress in functional neuroimaging has prompted studies of brain activation during various cognitive tasks. Coordinate-based meta-analysis has been utilized to discover the brain regions that are consistently activated across experiments. However, within-experiment co-activation relationships, which can reflect the underlying functional relationships between different brain regions, have not been widely studied. In particular, voxel-wise co-activation, which may be able to provide a detailed configuration of the co-activation network, still needs to be modeled. To estimate the voxel-wise co-activation pattern and deduce the co-activation network, a Co-activation Probability Estimation (CoPE) method was proposed to model within-experiment activations for the purpose of defining the co-activations. A permutation test was adopted as a significance test. Moreover, the co-activations were automatically separated into local and long-range ones, based on distance. The two types of co-activations describe distinct features: the first reflects convergent activations; the second represents co-activations between different brain regions. The validation of CoPE was based on five simulation tests and one real dataset derived from studies of working memory. Both the simulated and the real data demonstrated that CoPE was not only able to find local convergence but also significant long-range co-activation. In particular, CoPE was able to identify a 'core' co-activation network in the working memory dataset. As a data-driven method, the CoPE method can be used to mine underlying co-activation relationships across experiments in future studies.
authors.affiliation: Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.
authors.forename: Congying
authors.initials: C
authors.lastname: Chu
authors.affiliation: Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.
authors.forename: Lingzhong
authors.initials: L
authors.lastname: Fan
authors.affiliation: Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, 52425 Juelich, Germany; Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, 52074 Aachen, Germany.
authors.forename: Claudia R
authors.initials: CR
authors.lastname: Eickhoff
authors.affiliation: Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.
authors.forename: Yong
authors.initials: Y
authors.lastname: Liu
authors.affiliation: Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.
authors.forename: Yong
authors.initials: Y
authors.lastname: Yang
authors.affiliation: Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, 52425 Juelich, Germany; Institute for Clinical Neuroscience and Medical Psychology, Heinrich-Heine-University Düsseldorf, 40225 Düsseldorf, Germany. Electronic address: S.Eickhoff@fz-juelich.de.
authors.forename: Simon B
authors.initials: SB
authors.lastname: Eickhoff
authors.affiliation: Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China; Queensland Brain Institute, The University of Queensland, St. Lucia, QLD 4072, Australia; CAS Center for Excellence in Brain Science, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China. Electronic address: jiangtz@nlpr.ia.ac.cn.
authors.forename: Tianzi
authors.initials: T
authors.lastname: Jiang
mesh_terms: D059907:Functional Neuroimaging / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008570:Memory, Short-Term / Q000502:physiology*; D015201:Meta-Analysis as Topic; D015233:Models, Statistical; D009415:Nerve Net / Q000502:physiology*
keywords: CoPE; Coordinate-based meta-analysis; Functional co-activation; Working memory