This one-day meeting provides an opportunity to learn about multivariate analyses of fMRI data from both internationally reknowned experts and local researchers. Multivariate pattern analysis (MVPA) is a sensitive and powerful tool that harnesses the information provided by changing patterns of activity within a neural population.
The MVPA meeting will be accompanied by a two-day workshop on the use of 'nilearn' software for multivariate analysis, comprising theoretical background and practical hands-on experience.
The one-day MVPA meeting is open to all. The 2-day nilearn workshop is open to experienced fMRI users.
Overview
20th November - nilearn workshop Part 1 (theoretical background & practice)
21st November - MVPA meeting with 8 speakers
22nd November - nilearn workshop Part 2 (practical experience)
Inscription
Registration is free but mandatory.
Please register for the one-day MVPA meeting by Monday 4th November 2019.
Please register for the 2-day nilearn workshop by Monday 14th October 2019 : registrations now closed !
During registration, you will be asked whether you also wish to attend the 2-day nilearn workshop. Workshop participants should have prior experience with analysing fMRI data and programming in Python. As the workshop is limited to 30 participants, please don't sign up for the workshop unless you are certain you will be able to attend both days.
If you only want to attend the one-day MVPA workshop, please select No in the drop-down menu.
If you wish to attend both the MVPA meeting and the nilearn workshop, please select Yes in the drop-down menu.
Please note that signing up for the nilearn workshop does not guarantee your participation, since space is limited. Successful candidates for the nilearn workshop will be notified separately by e-mail.
To register, please choose "Registration" from the menu on the left.
If you already have a 'scienceconf' account, simply fill in your details and press Save.
If you don't have a 'scienceconf' account, please first create an account by clicking on the downward arrow next to Login (above right), fill in your details, then press Save.
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