Current trends and advances in research in neuro-engineering: methods and applications - Artificial intelligence for multi-variate brain signals

ABSTRACT

The course aims at presenting how artificial intelligence approaches – especially deep learning-based ones – can be used for decoding multivariate brain signals (e.g., electroencephalogram). The state-of-the-art solutions for realizing deep neural networks for processing neural time series will be presented, together with the main application scenarios. Emphasis will be given to convolutional neural networks. Lastly, methodologies aimed at explaining neural network decision will be presented during the course, to discover the most relevant neural correlates underlying a specific task (e.g., cognitive or motor task) in a data-driven way. It is strongly suggested to attend the course in person.

SCHEDULE

• 12th June, 9am-12pm
  
• 13th June, 9am-12pm

This course is part of the training provided for IBES PhD Students in the academic year 2023/2024.

Those who succesfully attend and complete the course:

• are eligible for max. 2 credits if they are enrolled in cycle 37;
• gain 6 attendance hours of the IBES training for the Biomedical Engineering (BIO) curriculum if they are enrolled in cycle 38 and 39.

Check the links above for further information about the specific academic requirements for each cyle and how to comply with them.