Extracting representations of cognition across neuroimaging studies improves brain decoding
Fig 4
Visualization of some of task-optimized networks.
Our approach learns networks that are important for decoding across studies. These networks are individually focal and collectively well spread across the cortex. They are readily associated with the cognitive tasks that they contribute to predict. We display a selection of these networks on the cortical surface (A) and in 2D transparency (B), named with the salient anatomical brain region they recruit, along with a word-cloud (C) representation of the stimuli whose likelihood increases with the network activation. The words in this word cloud are the terms used in the contrast names by the investigators; they are best interpreted in the context of the corresponding studies.