Research Group Leader, Max Planck
Institute for Dynamics and Self-Organization
10:00am EDT | 4.00pm CEST
Presentation: Self-organization and learning in neural systems
Abstract: The advent of novel recording techniques enables unprecedented access to neural activity in vivo. In parallel, the development of novel compute architectures enables us to explore the self-organization and learning in brain-like neural networks. We use neuromorphic chips, to parallelize learning in spiking neural networks, and demonstrate how these networks tune their working point to task requirements. We then show how that working point changes across brain areas in the living brain. Thereby, we demonstrate a versatile tuning mechanism in silico, and show evidence for its role in shaping computation in vivo.
A multiscale approach to brain disorders
Wireless miniature medical robots for neurological applications
Making memories in mice