Team SODA, involving one lecturer and three postgraduate students from the School of Mathematical Sciences, are the highly commended runner-up in this year's RSS (Royal Statistical Society) Statistical Analytics Challenge.
Unveiled in April, 18 teams were involved in the six week Challenge which set out an open-ended research question related to a large complex data set.
Chris Brignell, Phillip Paine, Wilhelm Braun and Heather Pettitt worked on the analysis of resting state functional MRI (rfMRI) neuroimaging data, submitting a report with the title:
"Effect of smoothing halfwidth on estimated network structure in single-subject fMRI data".
The approach was to consider whether changing the preprocessing protocol required for the analysis of these high dimensional datasets would have an effect on the estimated network structure in the resting brain of one individual. R-fMRI data sets are known to be very large and complex, meaning that their analysis is challenging insofar as there exists no obviously right or wrong answer when it comes to detecting connectivity and network structure. Also, findings can change when different statistical measures are used.
The team have been invited to present their findings at the RSS 2014 conference in Sheffield on Wednesday 3 September 2014. They might also be considered for publication in the Journal of the Royal Statistical Society, Series C.
For further information please visit the RSS Challenge homepage.
Well done Team SODA!
Posted on Tuesday 12th August 2014