Ricardo Vigário: Steps towards understanding the brain using independent component analysis

Aalto University recognizes the excellence of an individual by promotion to a distinguished professor category known as Aalto Professor. Professor Erkki Oja is the third Aalto Distinguished Professor in the history of the university.

A symposium in honour of Aalto Distinguished Professor Erkki Oja was organized on 3rd December 2013 in Dipoli Conference Center, Espoo. Dipoli, known for its special architecture, is often used for local and international events such as ICANN 2011 conference. The symposium was opened by the President of Aalto University Tuula Teeri and followed by Professor Oja’s lecture "40 years of machine learning and pattern recognition". In addition, four scientific presentations were given by colleagues and his former doctoral students, Professors Samuel Kaski and Jouko Lampinen, Docent Ricardo Vigário, and Doctor Matti Aksela.

In his talk "Component analysis - a machine learning and neuroinformatics view", Ricardo Vigário described Erkki Oja's influential works in developing machine learning and pattern recognition methods. Oja's early works include important contributions related to artificial neural networks with publications like "Simplified neuron model as a principal component analyzer" (Oja 1982) and "Principal components, minor components, and linear neural networks" (Oja 1992). Vigário told his own story as a young research who was considering opportunities all around the world. He had a plan to first move to Finland to take the first steps here and then move to the United States to continue for the PhD studies. After some time in Finland, he realized that there is no need to go elsewhere to learn from the best experts - who happen to be in Finland. An interesting coincidence was that the artificial and biological neural network researchers were in the 1990s in the very same building in the Otaniemi campus. This lead to collaboration in which analysis of brain research results was conducted by neurally inspired computational methods. A good example of the successful results was the paper "Independent Component Approach to the Analysis of EEG and MEG Recordings" (Vigário et al. 2000). As latest developments, Vigário discussed research on phase synchrony, e.g., "A comparison of algorithms for separation of synchronous subspaces" (Almeida et al. 2012).