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In this paper I review the submission to the Explaining the Human VisualBrain Challenge 2019 in both the fMRI and MEG tracks. The goal was to constructneural network features which generate the so-called representationaldissimilarity matrix (RDM) which is most similar to the one extracted from fMRIand MEG data upon viewing a set of images. I review exploring the optimalgranularity of the receptive field, a construction of intermediate surrogatefeatures using Multidimensional Scaling and modelling them using neural networkfeatures. I also point out some peculiarities of the RDM construction whichhave to be taken into account.

Explaining the Human Visual Brain Challenge 2019 -- receptive fields and surrogate features