The novel methodological tools offer a unique integration of diverse data (MEG, fMRI, convolutional neural networks, and behavior) in a common RSA framework, enabling a holistic description of human brain function. This is fundamentally different than any available tools to date, and will enable novel experimental paradigms to test hypotheses in perception and cognition in the human brain.
To apply these tools, we have focused our efforts in a critical research area: human visual recognition. A multistage distributed network of cortical visual pathways provides the neural basis for object recognition in humans. While the computations and tuning properties of low-level neurons have been investigated in detail, the precise neural computations transforming low-level features to mid- and high-level representations remain terra ingognita. By operationalizing representations as similarities across pairs of stimuli in an RSA framework, we study the hierarchical cascade of the human visual system in a systematic way.