MEG@McGill Training Programs

MEG@McGill Comprehensive Training

Brainstorm Software Training Workshop


MEG@McGill Comprehensive Training

Where:

MEG Unit, McConnell Brain Imaging Centre
Montreal Neurological Institute, McGill University
3801 University St, Montreal (Canada)

When:

April 24-28, 2017
Registration

Target audience:

Students, researchers and staff with little to no prior experience with MEG

5-day course - April 24-28, 2017

A week of hands-on training experience with MEG imaging:
From paradigm design to advanced data analysis

Maximum 12 participants (4 groups of 3 people each)
McGillians: $1,000 - Externals: $1,200

1-day course - April 24, 2017

This is the first day of the 5-day comprehensive training course.
This 1-day training is designed to give the attendees an introduction to MEG through lectures and a "MEG by Example" poster session.

Maximum 70 participants
McGillians: $50 - Externals: $100

 


 

April 2017 - PDF icon Final Program

Day 1: Full-day MEG/EEG imaging crash course

 

Keynote : Multivariate pattern classification of MEG signals reveals the spatiotemporal and representational dynamics of the ventral visual pathway: Dimitrios Pantazis, Research Scientist, Director of MEG Lab, McGovern Institute for Brain Research at MIT

 

Foundations and Applications of MEG:

Wine and Cheese: MEG by Example poster session

Next 4 days are hands-on, in small groups (3 per group, 4 groups max)
Day 2: Hands-on practical paradigm design: design your pilot study in small groups
Day 3: Hands-on data collection: collect your own data
Day 4: Hands-on analysis of collected data using Brainstorm (including software training)
Day 5: Advanced data analysis continues and group presentations: what have we learned?


November 2016 Program - PDF icon Full Program

Day 1: Full-day MEG/EEG imaging crash course

PDF icon The physiological origins of scalp signals: Sylvain Baillet, PhD,
Professor, Director of MEG Research, McConnell
Brain Imaging Centre

Basic signal extraction: ERP/ERFs, Jeremy Moreau, PhD Student,
neuroSPEED Lab

PDF icon Spectral analysis, Peter Donhauser, PhD Student, neuroSPEED Lab

Source imaging 101: Christophe Grova, PhD, Assistant Professor,
Physics Dpt, and PERFORM centre, Concordia University

PDF icon Keynote : Multivariate statistical analyses for MEG data
Bratislav Misic, PhD, Assistant Professor, McConnell Brain
Imaging Centre

PDF icon Resting state analysis and the Open MEG Archive (OMEGA), technical and ethical aspects:

Julia Guiomar Niso-Galán, PhD, neuroSPEED lab

MEG and MSI in epilepsy: contributions and limitations illustrated in
real patients: Eliane Kobayashi, MD, PhD, Neurology and
Neurosurgery, McGill University and Jeremy Moreau, PhD Student,
neuroSPEED Lab

Next 4 days are hands-on, in small groups (3 per group, 4 groups max)

Day 2: Hands-on practical paradigm design: design your pilot study in small groups

Day 3: Hands-on data collection: collect your own data

Day 4: Hands-on analysis of collected data using Brainstorm (including software training)

Day 5: Advanced data analysis continues and group presentations: what have we learned?

 


 

 

 

                           

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