Professor Marianne Fyhn
Affiliation: Department of Biosciences, University of Oslo
A grand challenge in brain research is to understand how our brain balances the need for plasticity to encode new memories with network stability for long-term storage. We aim to reveal mechanisms of learning and memory at multiple scales from synaptic modifications to neural network processing. To achieve this, we combine advanced experimental and computational approaches including large-scale in vivo recording of neural activity, genetic perturbations and network simulations.
We have recently established an activity merging neuroscience with artificial intelligence research to develop and explore bio-inspired artificial neural networks to improve AI systems and bring deep insight into brain function.
Professor Marianne Fyhn completed her PhD in Neuroscience (2005) at NTNU, Norway, where she was seminal to the discovery of grid cells. Her work contributed to the Nobel Prize in Physiology or Medicine in 2014 awarded to M-B and E Moser.
After a post doctoral period at University of California San Francisco, studying visual cortical plasticity with MP Stryker, she established her research group at UiO. Here, she focuses on understanding neural mechanisms of memory processing in rodents from the molecular to neural network level.
In one line of research, they recently discovered how extracellular matrix molecules outside neurons restrict adult brain plasticity, stabilizes the neural network for navigation and contribute to long-term memory storage. In close collaboration with computational physicists, they recently established an activity to use knowledge from the brain to inspire and explore learning in artificial neural networks.
Fyhn has mentored more than 20 master and PhD students to completion. She a dedicated teacher of physiology and neurobiology and is engaged in the national neuroscience research education.
Supervisor for the following CompSci projects
- Large-scale recordings of neurons to reveal mechanisms of learning and memory (available in call 1)
- Large-scale network simulations of mouse visual cortex (available in call 1)
- Neuron population dynamics and the role of neuromodulators for learning in biological and artificial neural networks (available in call 2)
- Neural basis of complex memory processing - common challenges in brain and AI (available in call 2)