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Compartmentalized learning with coupled electrochemical adaptation

Aprendizagem compartimentalizada com adaptação electroquímica acoplada

Reference
2023.13758.PEX
Project Start Date
2025-02-20
Project End Date
2026-10-19
Principal Investigator
Scientific Area
Medical and health sciences
Funding Program
Concurso de Projetos Exploratórios em Todos os Domínios Científicos 2023

Abstract

Chemical synapses are the most complex inter-cellular juntion in the mammalian body. Involving over 2000 different proteins, interacting across multiple spatial and temporal domains, activity-dependent alterations in intracellular molecular dynamics underlie the phenomenon of synaptic plasticity which, in turn, provides the physiological, mechanistic basis for information acquisition and long-term storage (learning and memory). While the types and nature of these processes have been systematically unravelled in the past decades, these insights have largely failed to permeate into theoretical modelling and the development of functional learning algorithms. Ascribing a mechanistic role to the many different molecular players and pathways involved and understanding their interplay from a functional standpoint is a necessary step to interpret the vast amounts of empirical data and derive deeper insights into the neurobiological bases of learning and memory. In this exploratory project, we take the first steps towards a fundamental re-conceptualization of how we model learning via synaptic plasticity and how we think about adaptation in cortical circuits. By emphasizing intracellular molecular dynamics, we propose that: plasticity is compartmentalized and heterosynaptic, i.e., the induction of plasticity mechanisms within one synapse is coupled to the expression of synaptic change in neighboring synapses within restricted spatial domains (dendritic branches). intracellular heterosynaptic interactions bridge plasticity in different synapse types, i.e., the induction of plasticity at a Glutamatergic synapse will yield the expression of plasticity at neighboring GABAergic synapses, resulting in a localized, detailed balance between excitation and inhibition. electrochemical compartmentalization yields distinct, but coupled, forms of distributed, competitive plasticity, i.e., the mechanisms of homeostatic synaptic scaling, neuron-wide intrinsic plasticity and structural remodelling, among others, are all coupled and share the same triggers and effectors. Establishing adequate mathematical descriptions of these processes, validating their biophysical compatibility and investigating their functional consequences will yield new theoretical and computational tools to consolidate existing knowledge on the interplay between synaptic, dendritic and neuronal adaptive and homeostatic processes as well as a deeper understanding of the biophysics of learning and memory. The PI, Renato Duarte, has extensive experience in computational neuroscience, with a particular emphasis and interest in modelling synaptic plasticity and functional neural circuits. He aims to establish a Computational Neuroscience group at CNC-UC and he is gathering the necessary support for this endeavour. The team proposed for this project provides a broad range of expertise. From high-performance computing and theoretical modelling to synaptic molecular biology, the core team and consultants will ensure the successful completion of the project. Combining biochemical evidence with biophysical and phenomenological modelling, we will provide a set of empirically validated new models of synaptic plasticity, learning and adaptation as well as a systematic evaluation of their functional outcomes at the circuit/population levels. The CNC-UC will provide a suitable intellectual environment to foster the development of the project and team and the international collaborations involved will benefit the institution and the growth of new hired fellows, who will develop in a nurturing, multidisciplinary research environment and will be exposed to state-of-the-art research approaches and infrastructures in a scientific domain whose expression in the portuguese research infrastructure is lagging. The results from this research will be published in international peer-reviewed journals in Open Access format. This innovative project complies with the 2030 Agenda of the UN, goals 3: Ensure healthy lives and promote well-being; 4: Ensure inclusive and equitable quality education and 9: Foster innovation in the industrial sector.

Institutions

Main Institutions

  • Universidade de Coimbra (UC)

Other Institutions

  • Institute for Advanced Simulation, Forschungszentrum Jülich (IAS-6)
  • Institut Pasteur, Centre National de la Recherche Scientifique, Unité de Recherche Associée, Paris, France (Institut Pasteur)

Funding 49.626,96 €

Fundação para a Ciência e a Tecnologia (FCT) - Portugal

49.626,96 €