Journal Article FZJ-2015-04176

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Co-activation Probability Estimation (CoPE): An approach for modeling functional co-activation architecture based on neuroimaging coordinates

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2015
Academic Press Orlando, Fla.

NeuroImage 117, 397 - 407 () [10.1016/j.neuroimage.2015.05.069]

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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.

Classification:

Contributing Institute(s):
  1. Strukturelle und funktionelle Organisation des Gehirns (INM-1)
Research Program(s):
  1. 571 - Connectivity and Activity (POF3-571) (POF3-571)
  2. HBP - The Human Brain Project (604102) (604102)
  3. SMHB - Supercomputing and Modelling for the Human Brain (HGF-SMHB-2013-2017) (HGF-SMHB-2013-2017)

Appears in the scientific report 2015
Database coverage:
Medline ; BIOSIS Previews ; Current Contents - Life Sciences ; IF >= 5 ; JCR ; NCBI Molecular Biology Database ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Thomson Reuters Master Journal List ; Web of Science Core Collection
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 Record created 2015-06-12, last modified 2021-01-29


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