Embodiment in distributed information processing: “Solid” plants versus “liquid” ant colonies

Abstract

Information processing is an essential part of biology, enabling coordination of intra-organismal processes such as development, environmental adaptation and inter-organismal communication. Whilst in animals with specialised brain tissue a substantial amount of information processing occurs in a centralised manner, most biological computing is distributed across multiple entities, such as cells in a tissue, roots in a root system or ants in a colony. Physical context, called embodiment, also affects the nature of biological computing. While plants and ant colonies both perform distributed computing, in plants the units occupy fixed positions while individual ants move around. This distinction, solid versus liquid brain computing, shapes the nature of computations. Here we compare information processing in plants and ant colonies, highlighting how similarities and differences originate in, as well as make use of, the differences in embodiment. We end with a discussion on how this embodiment perspective may inform the debate on plant cognition.

Plants sum and subtract stimuli over different timescales

“…Approaching the case of plant gravitropism through the lens of Response Theory, we identify the dependence of gravitropic responses on past stimuli as a form of memory, captured by the memory kernel. Examples of memory formation at the tissue level are widespread ( 18, 21, 22, 35, 36 ), even in non-biological matter ( 37, 38 ). Here we assume that the input signal depends on the relative angle between the organ and the direction of gravity, following the well-known sine law sin ( θ ( s, t ) − θ P ) ( 39, 40 ).…”

“…The last decade has seen an increasing body of evidence that plants quantify and integrate sensory information about their environment at the tissue level (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16), detecting and climbing spatial signal gradients despite environmental and internally-driven noise (17). While it is generally accepted that tropic responses are a product of complex computational processes (1,14,(18)(19)(20)(21)(22), attempts to characterize these processes mathematicallythat is, to obtain an understanding of the rules according to which plants quantify and process the sensory information they acquire over time-are limited. There is a need for comprehensive experimental and mathematical frameworks that can be used, respectively, to derive quantitative observations regarding plants' growth in response to various stimuli, and to decode the underlying principles.…”

Plant science in the age of simulation intelligence

“…Each module functions autonomously, gathering, producing, or distributing resources for the overall plant’s advantage. Remarkably, plants lack a central controlling entity, resembling a decentralized “swarm intelligence” ( Baluška et al., 2010a ; Oborny, 2019 ; van Schijndel et al., 2022 ). For instance, a plant’s root tips exhibit both sensory and command center roles, independently deciding growth directions and even forming symbiotic relationships with mycorrhizal fungi ( Baluška et al., 2010b ).…”

Editorial: Plant sensing and computing - PlantComp 2022

“…The modular build of plants seems to lend itself to some form of swarm intelligence similar to social insects ( Baluška et al., 2010 ). Various conceptual and experimental papers have shown the computational capacities of plants ( Pieters et al., 2022 ; Trewavas, 2014 ; van Schijndel et al., 2022 ). A deeper insight into how plants perform cognition is obviously valuable scientifically, there is also great potential for applied plant scientists.…”