In this course you will be introduced to methods and tools for assessing causal relationships and directed couplings in real-world data such as physiological signals, finance data, etc.
We will introduce statistical and information theoretic measures for assessing functional and effective connectivity. This includes concepts such as correlation, coherence, mutual information, directed information, Granger causality, conditional transfer entropy, and phase synchrony.
You will learn how to estimate connectivity matrices from real-world data using data driven and model based estimation techniques. This includes variants of KSG estimators and learning based methods.
As applications we will use real EEG and fMRI signals, and a brief introduction to these signals will be given.
Organizer: Jan Østergaard
Lecturers: Jan Østergaard, Postdoc Manuel Morante, Postdoc Payam Baboukani
ECTS: 2
Time: 3 - 4 May 2023
Place: Aalborg
Zip code:
City:
Number of seats: 50
Deadline: 12 April
Important information concerning PhD courses:
We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.
- Teacher: Payam Shahsavari Baboukani
- Teacher: Manuel Morante
- Teacher: Jan Østergaard