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Learning in single cells through dynamical internal representations

Project description

Understanding single-cell learning in variable environments

Cells sense and interpret signals from their environments to generate context-dependent responses, a capability found across all life forms. Understanding this process is crucial in biology. The ERC-funded CeLEARN project will establish a new conceptual framework in which cells create internal representations of their external environment to infer information about the environment that guides their responses. This framework integrates information theory to quantify predictive information from these representations with dynamical systems theory to explain their realisation. The project will investigate various biological systems to identify shared molecular mechanisms of learning in single bacteria and eukaryotic cells and further explore how neurons in Drosophila melanogaster form stabilise or eliminate axonal branches, creating consistent synaptic patterns under variable conditions during development.

Objective

Cells continuously sense and interpret the external signals coming from their time-varying environments to generate context-dependent responses. This is true for the entire tree of life, ranging from bacteria and unicellular eukaryotes to neurons forming networks in the developing brain. Identifying the fundamental principles and underlying mechanisms that enable cells to interpret their complex natural surroundings and adequately respond remains one of the fundamental questions in biology. Conceptual views so far have been mainly guided by molecular biology descriptions, suggesting that cells are controlled by a genomic program executing a pre-scripted plan. Our goal is to develop an alternative conceptual framework: cells generate internal representations of their external ‘world’, which they utilise to actively infer information about it and predict changes, in order to determine their response. We will formalise this concept in a theory of single-cell learning, by combining information theory concepts to quantify the predictive information from the internal cell representations, with dynamical systems theory to explain how these encodings are realised. We will interrogate experimentally systems across all scales of biological organization: bacteria (B. subtilis), single-cell organisms (Paramecium, Tetrahymena) and neuronal cell culture models. By studying them in a comparative manner, we aim at identifying generic molecular mechanisms through which single-cell learning is realised. The acquired understanding will enable us to address in vivo how single neurons during D. melanogaster development learn to form, stabilize or eliminate axonal branches, to generate stereotyped synaptic patterning under highly-variable conditions. We argue that providing a broader and generic definition of learning will serve as a unifying framework, linking disparate areas and scales of biology, and offering a basis for addressing fundamental biological questions.

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-ERC-SYG - HORIZON ERC Synergy Grants

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Call for proposal

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(opens in new window) ERC-2024-SyG

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Host institution

MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 3 499 776,00
Address
HOFGARTENSTRASSE 8
80539 Munchen
Germany

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Region
Bayern Oberbayern München, Kreisfreie Stadt
Activity type
Research Organisations
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 3 499 776,00

Beneficiaries (5)

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