Course information

Course title
Analyzing Neural Time Series Data
University / Organization
Radboud University
City
Nijmegen
Country
Netherlands
Academic level
Both Msc and PhD
Language
English
School
Address
Course director
Course lecturer(s)
Michael Cohen Assistant professor Donders Center for Neuroscience Radboud UMC
Course aim
After this course you are able to: Understand the mechanics of the Fourier transform and how to implement it in Matlab, Use complex wavelet convolution to extract time-frequency information from time series data, Simulate data to test the accuracy of data analysis methods and effects of parameters, Implement non-parametric statistics to evaluate statistical significance while correcting for multiple comparisons.
Course contents / programme
The purpose of this course is to provide a firm grounding for understanding advanced neural time series (LFP/EEG/MEG) analyses, with a streng focus on time-frequency and synchronization analyses. The course is mathematically rigorous but is approachable to researchers with no format mathematics background. lf you want to analyze your neuroscience data completely on your own, this course will certainly help get you started. lt will also provide a firm basis for using analysis toolboxes such as eeglab or fieldtrip, although the course does not provide instructions for how to use these toolboxes.
Required Knowledge and preparation
Teaching methods
Assessment
Course type
Summer School
Consecutive days
Yes
Online course
No
Duration (net days)
5
Credits
2 ECTS
Course fee
€550, 10-25% early bird + partner discount if you apply before March 1, 2019
Direct e-mail to register
Paper submission required?
Motivation letter CV
Logo of institution
front approval