Generative Embedding for Model-Based Classification of fMRI Data
Figure 8
Given the low dimensionality of the model-induced feature space, subjects can be visualized in terms of ‘connectional fingerprints’ [98] that are based on a simple radial coordinate system in which each axis corresponds to the maximum a posteriori (MAP) estimate of a particular model parameter. The plot shows that the difference between aphasic patients (red) and healthy controls (grey) is not immediately obvious, suggesting that it might be subtle and potentially of a distributed nature.