Transfer- and meta-learning in deep networks for human brain-signal analysis (B01)

• Subject Area: Human Cognitive and Systems Neuroscience ; Image and Language Processing, Computer Graphics and Visualisation, Human Computer Interaction, Ubiquitous and Wearable Computing
• Term: since 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 499552394

We will develop techniques for information transfer across small EEG datasets from different setups, subjects, and tasks. Specifically, we will collect publicly available EEG data sets, and train a single large neural network across the whole collection by learning to align different topological layouts, and training a transformer model that can directly process the electrode coordinates. Moreover, we will pre-train neural networks on subsets of homogeneous EEG datasets and study how to exploit pre-trained neural networks to fine-tune for a new task.

• DFG Programme: Collaborative Research Centres
• Subproject of: SFB 1597: Small Data
• Applicant Institution: Albert-Ludwigs-Universität Freiburg
• Project Heads: Professor Dr. Tonio Ball; Professor Frank Hutter, Ph.D.