Recording of the event
?
Fyhn is internationally known for her contribution to the discovery of grid cells and for her influential work on memory. In the seminar, she presented new findings on how neurons behave after learning, using advanced imaging techniques and genetic tools.

During her talk, she highlighted several key insights from her recent research:
- Sleep matters. Consolidation of visual associations relies on intact PV neuron activity after learning.
- Neurons in the medial entorhinal cortex (MEC) respond strongly to reward and saliency in non-spatial contexts.
- In spatial contexts, cue-selectivity becomes stronger as experience induces changes in MEC neurons.
These findings show how essential rest is for the brain, since much of the work involved in shaping memories takes place when neural networks reorganize during quiet periods.
A closer look at the resting brain
Fyhn explained how her group uses gene engineering and large-scale live imaging to observe neuron populations in mice during learning and rest. The results demonstrate that specific neural activity after training is crucial for memory consolidation. This offers a rare and valuable insight into the processes that support learning.

About the speaker
Professor Marianne Fyhn earned her PhD in Neuroscience from NTNU in 2005. She played a central role in the discovery of grid cells, which later contributed to the 2014 Nobel Prize in Physiology or Medicine. After a postdoctoral fellowship at the University of California, San Francisco, where she studied visual cortical plasticity with MP Stryker, she established her research group at the University of Oslo. Her work focuses on the neural mechanisms of memory in rodents, from molecular processes to large-scale neural networks.

About the series
The dScience Lunch Seminar series offers monthly talks at the Science Library where researchers present cutting-edge science over lunch. In addition, dScience serves lunch every Thursday in the lounge at Kristine Bonnevies house. See more upcoming events here.?