Multi-scale brain plasticity - from molecules to behaviour in life-long learning

Brain plasticity is essential for learning, executive functions and our thoughts and memories but how this is regulated is far from understood. Emerging evidence from us and others points to a role for a type of extracellular matrix molecules, perineuronal nets (PNNs) enwrapping some neuron types, to limit and regulate adult brain plasticity. In the BrainMatrix project, we have investigated the role of PNNs for sensory and memory processing as a step to reveal how the PNNs contribute to regulate brain plasticity. The characterization of PNNs across the brain was poorly described when the project started. We therefore started out by showing how the distribution of the PNNs varies between brain areas and we reported how PNNs may act as a brake to adult brain plasticity. We went on to show, for the first time, that the PNNs may work as a physical framework to assist in storage of long-term memories likely by stabilizing the neural network involved in the recall or storage of the memory. Memory processing requires the integration of many sensory modalities involving many brain regions including the memory centers of the entorhinal cortex and the hippocampus. A key element of episodic memories is the link to the location and indeed, many neurons in these areas exhibit location-specific activity. Our mapping study revealed high expression of PNNs in the entorhinal cortex and we therefore set out to investigate the role of PNNs for spatial representations. In our work we could show that PNNs are important for aspects of spatial representations and in particular for establishing new spatial maps. Also, it turns out that without the PNNs, formation of new maps will disturb already known maps. In order to reveal molecular mechanisms of how PNNs are involved in these processes, we have been implementing the gene editing tools of CRISPR/Cas9 in both in vitro and in vivo systems. These interventions will be combined with neural activity measurements. This work is not completed and will pave the road for future work. As part of the work, we have developed new constructs which enable visualization and measuring from more than one thousand neurons at the same time. This allows unique insights into animal cognition, and for us, learning and memory processing. The constructs we have developed is far better than the current state-of-the-art and we have share these constructs with more than 100 research groups world wide. They are also made available at the non-profit AddGene. The brain operates at large temporal and spatial scales from the molecular dynamics of neural signaling, to the cell-to-cell interactions within neural networks. It is impossible to measure from all these scales and in particular at the same time. Therefore, in the BrainMatrix project experimentalists and computational scientists have worked side by side to develop models and run simulations to obtain a deeper understanding of what we measure and what we cannot measure. We have used moelcular dynamics simulations and biochemical models to understand how PNNs are formed and how they operate. We have developed physics based single cell models to understand the role of PNNs for the electrophysiological properties of the neurons and we have developed network models to visualize processes at a larger scale. Most of this theoretical work is in the process of being published. The project has resulted in several high impact papers and many PhD candidates have had their PhD projects directly associated to the BrainMatrix project. The results and thoughts from the project have made the foundation for our future work and research plan including our focus on learning and memory processing but also extending to understanding mechanisms of disease. The genetic tools we have developed have many generic applications which we and others will pursue. A recently established activity in the our research group has been on bio-inspired artificial intelligence system. In this research we take knowledge and the opportunity for targeted experiments on the brain and use this to develop new and more brain-inspired artificial intelligence systems. By studying these processes in parallel, we believe that we will gain deeper insight into processes in the brain as well as develop artificial intelligence systems that may overcome some of the current hurdles in the field.

Prosjektet var en unik mulighet for å kunne samle fremragende forskere fra biologi, fysikk og matematikk for å kunne studere spørsmål som krever stor grad av tverrfaglighet, nemlig å forstå hjerneprosesser på ulike skalaer. De biologiske spørsmålene var bærende, men de kan ikke løses uten tett samarbeid med beregningsorienterte fysikere som kan lage modeller for hva vi prøver å måle i eksperimentene. Selvom gruppen hadde etablert et samarbeid gjennom midler fra Universitetet i Oslo manglet vi ressursene som prosjektet ga. Tre stipendiater har vært lønnet av prosjektet. Alle tre vil disputere i løpet av 2022/23. I tillegg har seks PhD stipendiater hatt doktorgradsprosjektene sine direkte tilknyttet prosjektet. Av disse har tre disputert i løpet av prosjektperioden og de tre siste leverer i løpet av 2023/34. Flere av postdoktorene søker midler til forskningsrådet om ny forskning basert på prosjektresultatene. For prosjektleder, M.Fyhn, har prosjektet vært helt avgjørende for hennes forskningsmuligheter. Gruppen har søkt ulike prosjektmidler basert på prosjektresultatene og har lykkes i noe grad. Gruppen sammen med internasjonale samarbeidspartnere vil fortsette og utvide forskningsretningen slik den startet opp i BrainMatrix. Teamet vil søke innovasjonsmidler for å etablere en mindre virksomhet for de genetiske konstruktene og metodene som er fremkommet i prosjektet. Man søker nå med klinisk grunnforskning for å utrede hvor pernevrale nett spiller en rolle i hjernesykdom. Gruppen har etablert og vil utvide aktiviteten inn mot kunstig intelligensforskning ved å utnytte vårt tette tverrfagelig samarbeid. Prosjektet har kommet med nye vitenskapelige funn som har betydning for vår forståelse av læring og hukommelse og hjerneplastisitet generelt. Resultatene kan potensielt peke på mulige nye virkningsområder for medikamenter, men dette er på et for tidlig stadium til å konkludere. Prosjektet har i stor grad endret kulturen for tverrfaglighet innenfor forskningsmiljøet og for hvordan forskningsgruppen jobber internt, men også mot nasjonale og internasjonale samarbeidspartnere. Den tverrfaglige forskningskulturen er også noe som får ringvirkninger for utdanningen vi gir.

What are the mechanisms underlying the brains immense ability to change, explaining our capacity to learn from our experiences, and at the same time be stable enough to store memories for decades? Brain plasticity is essential for our beings but little is known about contributing factors in the intact brain. Increasing evidence points to a role for a type of extracellular matrix molecules, perineuronal nets (PNNs) enwrapping neuron sub-types to limit and regulate adult plasticity. In BrainMatrix, we will investigate memory processing to understand the role of PNNs and their regulation in brain plasticity. The brain operates at large temporal and spatial scales from the molecular dynamics of neural signaling, to the cell-to-cell interactions within neural networks. This calls for interdisciplinary efforts between experiments and mathematical modeling and simulations. In BrainMatrix we face these challenges and will develop a multi-scale model linking various spatial scales (molecules, single neurons, networks) based on targeted experiments using genetic perturbations in mice as well as high-end electrophysiology and microscopy. Computational models, taking advantage of the simulation platforms being developed e.g. within the EU Human Brain Project, will be developed to give insights to experimental data, make predictions and link the scales. This cutting-edge project, taking advantage of leading expertise in experimental neuroscience, computational physics and computer science will bring novel insights into the principles of brain plasticity. Furthermore, the PIs in BrainMatrix are part of the strategic research initiative, CINPLA (Centre for Integrative Neuroplasticity), supported by the Faculty of Mathematics and Natural Sciences, University of Oslo, and spearheaded by the project leader, Marianne Fyhn. The proposed project will quickly establish CINPLA as an internationally competitive research environment and develop Fyhn as a strong research leader.