[FieldTrip] Sending message to Fieldtrip mailing list subscribers
Schoffelen, J.M. (Jan Mathijs)
jan.schoffelen at donders.ru.nl
Mon Jun 26 16:31:17 CEST 2017
Dear Diane,
Well, that makes two of us :). That is: I can tell you what is depicted in these, what you call, 'brain heat maps’, but I don’t understand the purpose. It’s a masked topographical display, where the color values reflect the (spatially interpolated) sensor-specific weights that the classifier ‘learnt’ to be able to do an optimal classification. Typically this is not the most useful depiction, but the people who designed this particular tutorial probably have different ideas about this.
Stefan Haufe has written a nice paper about the interpretation of the outcome of multivariate classification algorithms (http://www.sciencedirect.com/science/article/pii/S1053811913010914) and makes a case for looking at the encoding or forward model, rather than at the decoding/inverse model parameters, as depicted in the tutorial. Some of the implemented methods in the ‘dmlt’ toolbox (which is the lower-level code that FieldTrip uses for the classification) generate output, typically called ‘weights’, that in a current version of FieldTrip is converted into a ‘weightsinv’ field, which reflect the ‘encoding parameters’ mentioned above.
Best wishes,
Jan-Mathijs
On 26 Jun 2017, at 15:56, D.Abdallah <da401 at kent.ac.uk<mailto:da401 at kent.ac.uk>> wrote:
Dear All,
My name is Diane Abdallah. I am a PhD student at the University of Kent. My focus is analyzing EEG data collected on Perceptual Illusions and analyzing that data using MVPA. And this is my first time using the FieldTrip discussion list.
I have completed the MEG MVPA (Multivariate Pattern Analysis) tutorial on the FieldTrip website:http://www.fieldtriptoolbox.org/tutorial/multivariateanalysis
However, I am unable to understand the Brain Heat Map that at the end. Where is the x-axis? Where is the y-axis? What is the legend of the map? What does it represent?
Thank you so much for your help! It is very much appreciated :)
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