Article «Representational dissimilarity component analysis (ReDisCA)» accepted for publication in the journal NeuroImage!

The paper presents a new method for analyzing EEG and MEG data — ReDisCA. This method allows to estimate the spatio-temporal components in EEG or MEG responses that correspond to a given representation difference matrix (RDM).

ReDisCA provides informative spatial filters and corresponding topographies that help determine the location of "representatively relevant" sources in the brain. It is important to note that the method does not require reverse modeling, but its results are consistent with the EEG and MEG observation equations and can be used as input data for precise source localization procedures.

The effectiveness of ReDisCA is demonstrated through simulations and comparison with traditional methods, and higher accuracy of source localization is shown. Applying the method to real EEG data allowed us to identify physiologically plausible representative structures without using reverse modeling.

We look forward to sharing the full version of the work after publication!