Date: Saturday, May 12th, 2018, 8:00AM to 5:00PM
Location: Center for Brain Health – University of British Columbia
Majid Mohajerani University of Lethbridge, Artur Luczak University of Lethbridge and Timothy Murphy University of British Columbia.
Supported in part by the UBC Dynamic Brain Circuits in Health and Disease Cluster and the Canadian Neurophotonics platform.
Description:Given the exponentially growing size and complexity of experimental data, advanced data analyses methods are proving to be indispensable for neuroscience research. In this workshop we will provide an overview of different analysis methods used in variety of neuroscience fields to help to understand complex brain signals.
The target audience of the workshop will be graduate students, postdoctoral researchers and principal investigators in neuroscience and psychology with interest in data analysis. The course will combine lectures and hands-on tutorials using MATLAB. Participants will perform the computer exercises using data sets and analysis software on their own laptop computers.
Scope: This one-day course will provide a survey of diverse topics, including methods for analyzing single and multiple spike trains, local field potential, EEG/MEG recordings, and fMRI data.
The maximum number of registrants has been reached and registration is now closed.
Ticket price: 50 CAD
Saturday May 12, 2018 UBC CBH
8:00 Opening remarks
8:05 Analyses of neuronal population data (Artur Luczak, University of Lethbridge)
9:00 Place fields and head direction cells analyses (Adrien Peyrache, McGill University)
10:00 Analyses of EEG signals (Kyle E. Mathewson, University of Alberta)
11:00 Graph theory and measures of brain connectivity (Bratislav Misic, McGill University)
12:00 Lunch break
1:00 Multivariate analyses (Mark Reimers, Michigan State University)
2:00 Deep Learning for neuronal and behavioral data analyses (Artur Luczak, University of Lethbridge)
3:00 Analysis of fMRI data: principles and techniques (Todd S. Woodward, UBC)
4:00 Open discussion about data analysis methods (all instructors and students)