Jordi Piñero, Ricard Solé; Statistical physics of liquid brains.

Liquid neural networks (or ‘liquid brains’) are a widespread class of cognitive living networks characterized by a common feature: the agents (ants or immune cells, for example) move in space. Thus, no fixed, long-term agent-agent connections are maintained, in contrast with standard neural systems.

Ant colonies also involve collectives of interacting individuals that can be modeled as on/off activity - e.g. engaged in a task or not. However, the physical location of such mobile agents change over time: the colony is ‘liquid’. Thus, interactions are now extended to a spatiotemporal embedding, with agents interacting at a certain location in one instant and then moving on to other locations to continue interacting with each other. This particularity will constrain the system's adaptive properties in a non-trivial manner. Within the liquid realm, we can still characterize two paradigms: given their relative mobility and signal transmissivity (see below) insect colonies are strongly affected by the locality of their interactions, whereas ISs are highly mobile, such that a well-mixed approach might accurately represent their overall dynamics.

Other types of organisms, such as the slime mould Physarum, solve some classes of optimization problems by using a different form of fluid organization [13], although in this case there is no neural substrate. Systems of this kind are able to solve minimization problems on a network [14].

Jordi Piñero, Ricard Solé; Statistical physics of liquid brains. Phil. Trans. R. Soc. B 10 June 2019; 374 (1774): 20180376. https://doi.org/10.1098/rstb.2018.0376