Introduction to Information Theory in Neuroscience (2025)
The Technical Doctoral School of IT and Design at Aalborg University
Description: In this course, we introduce information theoretic notions that are applicable to several neuroscience systems. Our focus will be on directed information measures, which are useful for establishing statistical relationships between time series data such as EEG. We will also introduce non-directed measures such as phase synchrony.
You will learn about concepts such as mutual information, transfer entropy, redundant and synergistic information, connectivity matrices and coupling strengths between time series. These concepts will be demonstrated on EEG data and you will be able to apply the tools on your own real-world physiological data.
Prerequisites: Basic courses on statistics and probability theory
Learning objectives: You will learn about concepts such as mutual information, transfer entropy, redundant and synergistic information, connectivity matrices and coupling strengths between time series. These concepts will be demonstrated on EEG data and you will be able to apply the tools on your own real-world physiological data.
Organizer: Jan Østergaard
Lecturers: Jan Østergaard
ECTS: 1.0
Time: 7, 8, 9 April 2025
Place: Aalborg University
Zip code: 9220
City: Aalborg
Maximal number of participants: 30
Deadline: 17 March 2025