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Flow network morphology as memory map: Principles of fluid flow driven dynamic memory in living tubular networks

Project description

Exploring memory in fluid networks of living organisms

Living systems transport vital cargo including signalling molecules, oxygen, nutrients and waste over long and short distances with the help of fluids coursing through vast tubular networks. Many of these tubes respond dynamically to changes in flow characteristics, for example increasing diameter in response to increasing flow velocity. These adaptations can be long-term, essentially reflecting a type of memory storage for the preceding events and conditions. The EU-funded FlowMem project is investigating how local transient stimuli can induce long-term changes; the goal is to use this knowledge to modulate tubular networks and apply it in fields ranging from biomedicine and microfluidics to soft robotics.

Objective

Fluid flows through tubular networks are crucial for life as they are the dominant means of substance and signal transport. In living networks across organisms as disparate as animals and fungi, alterations of flows drive dynamic adaptation of tube diameters which in turn alters transport performance. In effect, local transient stimuli that affect flows are memorized as long-lived alterations to tube diameters across the network. I aim to identify the physical principles behind fluid flows driving dynamic memory storage in network morphology. I will thereby uncover how to control network morphology and performance by applied flow-altering stimuli, which promises significant advances in important challenges of the future: treatment of vascular diseases and tumour development, encoding complex behaviour in soft robotics and self-optimizing porous media.
The dynamic nature of flows and networks complex morphologies requires a combined experimental and theoretical approach to address: What are the physical mechanisms of how flows in living tubular networks can encode and store information about stimuli? How do memories impact network performance? As experimental model system I choose the slime mould Physarum polycephalum. It is ideally suited as a starting point, as it reduces the problem in its complexity to just a tubular network. This model allows me to follow with unprecedented level of detail how stimuli transiently perturb network-wide flows flows that subsequently drive long-term changes in network morphology. Theoretical models will verify mechanisms and allow investigation of impact on network function. Identified principles of dynamic memory formation will be applied to study consequences of mini-stroke stimuli and possible treatment in brain microvasculature and to design self-optimizing porous media. I will develop general principles advancing physics and biology with far-reaching implications in medicine and engineering.

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ERC-STG - Starting Grant

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Call for proposal

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(opens in new window) ERC-2020-STG

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Host institution

TECHNISCHE UNIVERSITAET MUENCHEN
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.

€ 1 499 905,00
Address
Arcisstrasse 21
80333 Muenchen
Germany

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Region
Bayern Oberbayern München, Kreisfreie Stadt
Activity type
Higher or Secondary Education Establishments
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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.

€ 1 499 905,00

Beneficiaries (1)

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