[pymvpa] 1st phase of Unsupervised and Transfer Learning Challenge is on

[Emanuele Olivetti]

On 01/07/2011 11:21 PM, Yaroslav Halchenko wrote:
> If you are up for a challenge: there you go

And you might be interested in this one too:

Mind reading from MEG - Challenge

     http://www.cis.hut.fi/icann2011/mindreading.php

* Overview

The challenge combines two recent trends in neuroscience: Analysis of naturalistic 
stimulation and mind reading. The task in the challenge is to decode the stimulus identity 
based on magnetoencephalography (MEG) recording done during naturalistic stimulation. In 
more detail, the subject is viewing video stimuli of different kinds (football match, 
feature film, recording of natural scenery etc), and the goal is to classify unlabeled 
test examples into these categories based on the MEG signal alone.

The challenge aims at promoting awareness on feasibility of MEG for mind reading tasks, as 
well as encouraging application of recent advances in machine learning development to this 
difficult but possible modeling task. Demonstration of mind reading from MEG signals 
showcases the amount of information about perceptual processes captured by the imaging 
technology, whereas advanced modeling techniques are needed to reliably extract the 
information.

In this challenge the stimulus identity is inferred from very limited amount of signal 
measured during natural stimulation, lacking the usual characteristics of MEG analysis 
such as controlled experimental condition and averaging over multiple trials. The problem 
can be approached either as a single-trial MEG challenge, or as a generic classification 
task with high-dimensional signal representation and potentially large shift between the 
distributions of the training and test samples that were recorded in different sessions. 
To encourage participants with limited MEG expertise, the data is provided after standard 
preprocessing.

* Organizers

A. Klami1, P. Ramkumar2, S. Virtanen1, L. Parkkonen2, R. Hari2, and S. Kaski1

Aalto University School of Science and Technology
1Department of Information and Computer Science, Helsinki Institute for Information 
Technology HIIT
2Brain Research Unit, Low Temperature Laboratory