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A novel meta-analytic approach: Mining frequent co-activation patterns in neuroimaging databases
2014
NeuroImage
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In recent years, coordinate-based meta-analyses have become a powerful and widely used tool to study coactivity across neuroimaging experiments, a development that was supported by the emergence of large-scale neuroimaging databases like BrainMap. However, the evaluation of coactivation patterns is constrained by the fact that previous coordinate-based meta-analysis techniques like Activation Likelihood Estimation (ALE) and Multilevel Kernel Density Analysis (MKDA) reveal all brain regions that
doi:10.1016/j.neuroimage.2013.12.024
pmid:24365675
pmcid:PMC4981640
fatcat:4ilkwknjbzd37iu4wxnos2ue5i