Memory capacity of adaptive flow networks

TL;DR

This paper investigates the memory capacity of adaptive biological flow networks, revealing how they store multiple stimuli based on network age and stimulus duration, with implications for understanding biological memory mechanisms.

Contribution

It introduces a numerical model to analyze how adaptive flow networks retain memory of stimuli and identifies factors influencing their memory capacity.

Findings

Networks retain strong memory signals for long-imprinted stimuli.

Capacity to store stimuli depends on stimulus duration and network age.

Networks can store multiple stimuli with balanced imprinting and aging effects.

Abstract

Biological flow networks adapt their network morphology to optimise flow while being exposed to external stimuli from different spatial locations in their environment. These adaptive flow networks retain a memory of the stimulus location in the network morphology. Yet, what limits this memory and how many stimuli can be stored is unknown. Here, we study a numerical model of adaptive flow networks by applying multiple stimuli subsequently. We find strong memory signals for stimuli imprinted for a long time into young networks. Consequently, networks can store many stimuli for intermediate stimulus duration, which balance imprinting and ageing.