Statistical dependencies in analysis of naturalistic brain stimulation

Lecturer : 
Arto Klami
Event type: 
HIIT seminar
Event time: 
2010-11-19 10:15 to 11:00
Exactum C222

Talk announcement:
HIIT Seminar Kumpula, Friday Nov 19, 10:15 a.m., Exactum C222

On Nov 19 HIIT Seminar Kumpula features a talk by Arto Klami from the HIIT Statistical Machine Learning and Bioinformatics group. The presentation will include a short and accessible overview of the group.

--Matti Järvisalo


Arto Klami
Helsinki Institute for Information Technology HIIT / Aalto University

Statistical dependencies in analysis of naturalistic brain stimulation

Use of more naturalistic experimental conditions is currently one of the major trends in neuroscience. Instead of controlled experiments the brains are being scanned for example when the subject is watching a movie. Naturalistic stimulation opens up new possibilities for understanding the brain, but the classical analysis tools are not sufficient for these new setups. I will introduce a new approach based on extracting statistical dependencies between brain activity and rich feature representations of the stimulus and discuss the necessary modeling tools.

Arto Klami is a postdoc researcher at the Department of Information and Computer Science at Aalto University. He received his PhD in computer science at Helsinki University of Technology in 2008, and is currently working on an Academy of Finland postdoctoral researcher's project. His research interests include Bayesian modeling, proactive interfaces, and analysis of neuroimaging data.

Last updated on 16 Nov 2010 by WWW administrator - Page created on 12 Nov 2010 by Thomas Vikberg