Figure 2: Comparison of MEG, fMRI and DNN representations by representational similarity.

From: Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence

Figure 2

In each signal space (fMRI, MEG, DNN) we summarized representational structure by calculating the dissimilarity between activation patterns of different pairs of conditions (here exemplified for two objects: bus and orange). This yielded representational dissimilarity matrices (RDMs) indexed in rows and columns by the compared conditions. We calculated millisecond resolved MEG RDMs from −100 ms to +1,000 ms with respect to image onset, layer-specific DNN RDMs (layers 1 through 8) and voxel-specific fMRI RDMs in a spatially unbiased cortical surface-based searchlight procedure. RDMs were directly comparable (Spearman’s R), facilitating integration across signal spaces. Comparison of DNN with MEG RDMs yielded time courses of similarity between emerging visual representations in the brain and DNN. Comparison of the DNN with fMRI RDMs yielded spatial maps of visual representations common to the human brain and the DNN. Object images shown as exemplars are not examples of the original stimulus set due to copyright; the complete stimulus set is visualized at http://brainmodels.csail.mit.edu/images/stimulus_set.png.