Decoding brain activity using a large-scale probabilistic functional-anatomical atlas of human cognition
Fig 3
Selected topics learned by the GC-LDA model (for full results, see S1 Fig).
(a) Spatial distributions for 90 of the 200 topics. Each color represents a different topic. Top row: hard assignments of activations to topics; each point represents a single activation from a single study in the Neurosynth database (note that each topic is spatially represented by a mixture of only two symmetrically-constrained gaussians; the appearance of multiple regions that share colors is due to the inevitable reuse of perceptually similar colors). Bottom row: estimated multivariate Gaussian mixture distribution of each topic. (b) Top semantic associates (word clouds) and activation distributions (orthogonal brain slices) for selected topics. The size of a term in each word cloud is proportional to the strength of loading on the corresponding topic.