---------- Forwarded message ---------- From: Guillaume Desjardins guillaume.desjardins@gmail.com Date: Mon, Jun 20, 2011 at 3:56 PM Subject: Update: CIFAR machine learning seminar Thurs. June 23rd @ 14h30, AA3195 To: lisa_seminaires@iro.umontreal.ca

Aapo Hyvarinen's talk, scheduled for Thurs. June 23rd @ 14h30,  will take place in AA3195 (Pavillon  Andre-Aisenstadt, room 3195, University of Montreal).

On Fri, Jun 17, 2011 at 6:07 PM, Guillaume Desjardins guillaume.desjardins@gmail.com wrote:

I am delighted to announce the following talk by Aapo Hyvarinen, which will take place on Thursday June 23rd at 14h30. The talk will be held at the University of Montreal, with the exact room to be announced at a later date. Hope to see you there !

Title: Unsupervised machine learning for analysis of EEG and MEG at rest Speaker: Aapo Hyvarinen

Abstract: Recently, a lot of brain imaging has concentrated on analyzing brain activity at rest, i.e. when the subject is not doing anything particular and does not receive specific stimulation. When using functional magnetic resonance imaging (fMRI), such analysis is typically done by independent component analysis (ICA). However, there has not been very much work on analysing resting activity measured by EEG or MEG. We have recently developed various methods to analyse EEG/MEG data at rest. First, we have created new variants of ICA to more completely exploit the statistical structure of EEG/MEG data. Second, we have developed tests of the statistical significance of the independent components. Third, we have a framework for analysis of causality (connectivity) which uses the non-Gaussianity of the data and hopefully it can be used to analyse the connectivity of the independent components.