Machine Learning for Neural Engineering
Event details
| Date | 01.02.2016 |
| Hour | 14:00 › 15:00 |
| Speaker | Dr. Moritz Grosse-Wentrup (Max Planck Institute) |
| Location | |
| Category | Conferences - Seminars |
Science traditionally progresses by developing mechanistic models that capture cause-effect relations. In cognitive neuroscience, such models of are not yet available. While this is often seen as a major shortcoming, I will argue that we do not actually need mechanistic models to translate research in cognitive neuroscience into clinical applications. I will present machine learning methods that can infer causal hypotheses directly from empirical data. I will demonstrate the utility of this novel conceptual approach on two applications. First, I will show how it has led to a new class of brain-computer interfaces (BCIs) for communication with patients in late stages of amyotrophic lateral sclerosis (ALS). Second, I will present a novel approach to BCI-based motor rehabilitation that considers the global configuration of brain rhythms and its relation to motor deficits.
A live transmission will be available on the EPFL campus in SV3715
A live transmission will be available on the EPFL campus in SV3715
Practical information
- Informed public
- Free
Organizer
- Center for Neuroprosthetics, Prof Dimitri Van de Ville