Cracking the Synaptic Memory Code
This project aims to uncover how local protein production at synapses contributes to memory encoding in the brain using advanced imaging and sequencing techniques.
Projectdetails
Introduction
Despite their role in long-term information storage, synapses are highly dynamic and composed of rather short-lived components. In the adult mouse brain, it takes a couple of days for half of the dendritic spines to be replaced. Similarly, at the molecular level, most synaptic proteins have half-lives in the order of a week, meaning they constantly need to be replaced by freshly produced ones. Thus, understanding how long-term memory can arise from unstable elements is one of today’s neuroscience’s greatest challenges.
Discovery of Local Protein Production
Overturning an old dogma, I discovered using in vivo and in vitro approaches that most synapses produce their own proteins locally at both the pre- and postsynaptic sites. Interestingly, classic plasticity paradigms produce unique patterns of rapid pre- and/or postsynaptic translation. This finding is driving a paradigm shift in our understanding of synaptic function. It is now possible to decode pre- and postsynaptic memory traces formed during learning.
Research Methodology
I am now in the unique position to combine omics, cytometry, super-resolution and live-imaging techniques, and behavioral learning tasks to unravel how local production of new proteins contributes to information storage at synapses.
Experimental Goals
- Live-imaging: I want to understand how and when protein synthesis is recruited in excitatory boutons.
- Next generation sequencing and imaging: I will investigate how mRNA finds its way to presynapses.
- Genetically encoded neuronal activation tracker: I will follow the molecular changes and thus uncover the synaptic memory traces in the hippocampus and cortex after learning.
Conclusion
Altogether, these experiments will tackle the unresolved question of memory encoding in the brain, from molecules to neural networks. With an unprecedented resolution, we will gain critical insights into how memories are stored at synapses. Such a fundamental understanding of brain function is needed to provide new avenues against neurodegenerative diseases.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 1.500.000 |
Totale projectbegroting | € 1.500.000 |
Tijdlijn
Startdatum | 1-3-2023 |
Einddatum | 29-2-2028 |
Subsidiejaar | 2023 |
Partners & Locaties
Projectpartners
- STICHTING RADBOUD UNIVERSITEITpenvoerder
Land(en)
Vergelijkbare projecten binnen European Research Council
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Revealing the Landscape of Synaptic Diversity by Cell type- and Synapse-specific Proteomics and TranscriptomicsThis project aims to elucidate the molecular diversity of synapses by analyzing their proteomes and transcriptomes across different brain areas, using advanced sorting and profiling techniques. | ERC Advanced... | € 2.498.575 | 2022 | Details |
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Lysosomal exocytosis of metastable proteins to control synaptic function
The LEXSYN project aims to investigate lysosomal exocytosis in dendrites to understand its role in synaptic plasticity and neurodegeneration, utilizing advanced imaging and new monitoring tools.
Epigenetic and transcriptional basis of memory engram plasticity
This project aims to uncover the epigenetic and transcriptional mechanisms of memory engram cells during consolidation and retrieval using advanced genomics and functional analysis techniques.
Plasticity of neurotransmitter release sites in temporal coding, homeostasis, learning and disease
This project aims to explore the mechanisms of synaptic release site plasticity in Drosophila to understand its role in neural function, behavior, and disease treatment.
Revealing the Landscape of Synaptic Diversity by Cell type- and Synapse-specific Proteomics and Transcriptomics
This project aims to elucidate the molecular diversity of synapses by analyzing their proteomes and transcriptomes across different brain areas, using advanced sorting and profiling techniques.
Creating Knowledge
This project aims to test a new theory on experience-dependent learning by investigating how knowledge networks are built and updated across species using innovative behavioral and neuroimaging techniques.
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Metaplastic Spintronics Synapses
METASPIN aims to develop low-power spintronic artificial synapses with metaplasticity to prevent catastrophic forgetting in AI, integrating this technology into an ANN for multitask learning applications.