<div dir="ltr"><div class="gmail_extra"><div class="gmail_extra">Dear all,<br></div><div class="gmail_extra"> </div><div class="gmail_extra">We are pleased to announce that our annual SPM course for MEG/EEG will take place this year from Monday May 8 to Wednesday May 10 2017.</div><div class="gmail_extra"> </div><div class="gmail_extra">Hosted by University College London, the course will be held at Queen Square, a very central location in London (UK).</div><div class="gmail_extra"> </div><div class="gmail_extra">The course will present instruction on the analysis of MEG and EEG data. The first two days will combine theoretical presentations with practical demonstrations of the different data analysis methods implemented in SPM. On the last day participants will have the opportunity to work on SPM tutorial data sets under the supervision of the course faculty. We also invite students to bring their own data for analysis.</div><div class="gmail_extra"> </div><div class="gmail_extra">The course is suitable for both beginners and more advanced users. The topics that will be covered range from pre-processing and statistical analysis to source localization and dynamic causal modelling. The program is listed below.</div><div class="gmail_extra"> </div><div class="gmail_extra">Registration is now open. For full details see <a href="http://www.fil.ion.ucl.ac.uk/spm/course/london/">http://www.fil.ion.ucl.ac.uk/spm/course/london/</a> where you can also register.</div><div class="gmail_extra"> </div><div class="gmail_extra">Available places are limited so please register as early as possible if you would like to attend!</div><div class="gmail_extra"> </div><div class="gmail_extra"> ----------------------</div><div class="gmail_extra"> </div><div class="gmail_extra"> </div><div class="gmail_extra">Monday May 8th (33 Queen square, basement)</div><div class="gmail_extra"> </div><div class="gmail_extra">9.00 - 9.30    Registration</div><div class="gmail_extra"> </div><div class="gmail_extra">9.30 - 9.45                SPM introduction and resources                       Guillaume Flandin                                              </div><div class="gmail_extra"> </div><div class="gmail_extra">9.45 - 10.30              What are we measuring with M/EEG?              Saskia Heibling        </div><div class="gmail_extra">                                              </div><div class="gmail_extra">10.30 - 11.15            Data pre-processing                                           Hayriye Cagnan</div><div class="gmail_extra"> </div><div class="gmail_extra">           Coffee</div><div class="gmail_extra"> </div><div class="gmail_extra">11.45 - 12.30            Data pre-processing – demo                              Sofie Meyer, Misun Kim                                  </div><div class="gmail_extra"> </div><div class="gmail_extra">12.30 - 13.15            General linear model and classical inference     Christophe Phillips</div><div class="gmail_extra">                        </div><div class="gmail_extra">           Lunch</div><div class="gmail_extra"> </div><div class="gmail_extra">14.15 - 15.00            Multiple comparisons problem and solutions     Guillaume Flandin</div><div class="gmail_extra">                      </div><div class="gmail_extra">15.00 - 15.45    Bayesian inference                                                    Christophe Mathys    </div><div class="gmail_extra">                      </div><div class="gmail_extra">           Coffee</div><div class="gmail_extra"> </div><div class="gmail_extra">16.15 - 17.45            Group M/EEG dataset analysis - demo            Jason Taylor, Martin Dietz    </div><div class="gmail_extra"> </div><div class="gmail_extra">17.45 - 18.30            Advanced applications of the GLM                   Ashwani Jha,  Bernadette van Wijk</div><div class="gmail_extra"> </div><div class="gmail_extra"> </div><div class="gmail_extra"> </div><div class="gmail_extra"><br></div><div class="gmail_extra"> </div><div class="gmail_extra">Tuesday May 9th (33 Queen square, basement)</div><div class="gmail_extra"> </div><div class="gmail_extra">9.30 - 10.15              M/EEG source analysis                                    Gareth Barnes</div><div class="gmail_extra"><br></div><div class="gmail_extra">10.15 - 11.15            M/EEG source analysis – demo                       Jose Lopez, Leonardo Duque</div><div class="gmail_extra">          </div><div class="gmail_extra">           Coffee</div><div class="gmail_extra"> </div><div class="gmail_extra">11.45 - 12.30            The principles of dynamic causal modelling          Bernadette van Wijk</div><div class="gmail_extra">                                              </div><div class="gmail_extra">12.30 - 13.15            DCM for evoked responses  Ryszard Auksztulewicz                                </div><div class="gmail_extra">           Lunch</div><div class="gmail_extra">  </div><div class="gmail_extra">14.15 - 15.00            DCM for steady state responses      Rosalyn Moran</div><div class="gmail_extra"> </div><div class="gmail_extra">15.00 - 15.45            DCM - demo   Richard Rosch, Tim West</div><div class="gmail_extra">                      </div><div class="gmail_extra">           Coffee</div><div class="gmail_extra"> </div><div class="gmail_extra">16.15 - 17.00            Bayesian model selection and averaging   Peter Zeidman</div><div class="gmail_extra">                      </div><div class="gmail_extra">17.00 - 18.30            Clinic - questions & answers            Karl Friston</div><div class="gmail_extra">                        </div><div class="gmail_extra">19.00 - ...        Social Event</div><div class="gmail_extra"> </div><div class="gmail_extra"> </div><div class="gmail_extra"> </div><div class="gmail_extra"> </div><div class="gmail_extra">Wednesday May 10th</div><div class="gmail_extra"> </div><div class="gmail_extra">9.30 - 17.00</div><div class="gmail_extra"> </div><div class="gmail_extra">Practical hands-on session in UCL computer class rooms. Participants can either work on SPM tutorial datasets or on their own data with the help of the faculty. There will also be an opportunity to ask questions in small tutorial groups for further discussions on the topics of the lectures.</div><div><br></div></div></div>