AI for Aging societies: From Basic Concepts to Practical Tools for AI-Facilitated Cognitive Training
The aim of AI-Cog is to leverage the potential of artificial intelligence (AI) approaches to foster healthy aging. To this aim we will study objective machine-learning-driven biomarkers to evaluate cognitive interventions as well as support personalized therapies. We will develop novel, dedicated machine learning (ML) methods and adapt them to the special signal types that can be recorded from the human brain. We will make our methods publicly available in an open-source reference software package, focussing on unsupervised learning, data augmentation, domain adaptation, and interpretable machine learning models. Our main scientific aims is to optimize the decodable information about the current functional state of the brain, to identify biomarkers of the risk for cognitive impairments and different forms of dementia, and use these improved methods to guide AI-facilitated cognitive training.
Alexandre Gramfort; INRIA Saclay Ile-de-France -
Tonio Ball; University of Freiburg, Medical Center, Department of Neurosurgery, Neuromedical AI Lab -
Tomasz Rutkowski; RIKEN, Center for Advanced Intelligence Project