Brainless but Multi-Headed: Decision Making by the Acellular Slime Mould Physarum polycephalum

Beekman, Madeleine; Latty, Tanya

doi:10.1016/j.jmb.2015.07.007

Cited by 77 publications

(53 citation statements)

References 65 publications

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“…Increasing the correlation length of such control could have driven the development of targeted, long cellular structures (axons): to move the whole animal, not just individual cells, the electrical information needs to be scaled considerably, and nervous systems are an ideal extension of ancient, pre-neural bioelectric signaling paths to enable further scaling of the cognitive boundary of cells into organs, organisms, swarms, and societies. A prediction of this proposed scaling is that swarm organisms should fall prey to the same kinds of cognitive illusions and specific failures of rationality as do vertebrate brains, which has indeed been observed in ants and slime molds Gunji, 2013, 2016;Tani et al, 2014;Beekman and Latty, 2015). Another consequence is that the cybernetics of associative learning in networks is agnostic as to the spatio-temporal scale and physical implementation, being widespread from molecular networks and inorganic physics to whole evolving populations (Cragg and Temperley, 1955;Mcgregor et al, 2012;Power et al, 2015;Watson and Szathmary, 2016;Kouvaris et al, 2017;Lopez Garcia De Lomana et al, 2017).…”

Section: A B Cmentioning

confidence: 82%

The Computational Boundary of a “Self”: Developmental Bioelectricity Drives Multicellularity and Scale-Free Cognition

2019

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All epistemic agents physically consist of parts that must somehow comprise an integrated cognitive self. Biological individuals consist of subunits (organs, cells, and molecular networks) that are themselves complex and competent in their own native contexts. How do coherent biological Individuals result from the activity of smaller sub-agents? To understand the evolution and function of metazoan creatures' bodies and minds, it is essential to conceptually explore the origin of multicellularity and the scaling of the basal cognition of individual cells into a coherent larger organism. In this article, I synthesize ideas in cognitive science, evolutionary biology, and developmental physiology toward a hypothesis about the origin of Individuality: "Scale-Free Cognition." I propose a fundamental definition of an Individual based on the ability to pursue goals at an appropriate level of scale and organization and suggest a formalism for defining and comparing the cognitive capacities of highly diverse types of agents. Any Self is demarcated by a computational surface -the spatio-temporal boundary of events that it can measure, model, and try to affect. This surface sets a functional boundarya cognitive "light cone" which defines the scale and limits of its cognition. I hypothesize that higher level goal-directed activity and agency, resulting in larger cognitive boundaries, evolve from the primal homeostatic drive of living things to reduce stress -the difference between current conditions and life-optimal conditions. The mechanisms of developmental bioelectricity -the ability of all cells to form electrical networks that process informationsuggest a plausible set of gradual evolutionary steps that naturally lead from physiological homeostasis in single cells to memory, prediction, and ultimately complex cognitive agents, via scale-up of the basic drive of infotaxis. Recent data on the molecular mechanisms of pre-neural bioelectricity suggest a model of how increasingly sophisticated cognitive functions emerge smoothly from cell-cell communication used to guide embryogenesis and regeneration. This set of hypotheses provides a novel perspective on numerous phenomena, such as cancer, and makes several unique, testable predictions for interdisciplinary research that have implications not only for evolutionary developmental biology but also for biomedicine and perhaps artificial intelligence and exobiology.

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Section: A B Cmentioning

confidence: 82%

The Computational Boundary of a “Self”: Developmental Bioelectricity Drives Multicellularity and Scale-Free Cognition

2019

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“…The notion of 'proto-brains' formed by individual bacterial or amoeboid cells is something that was unthinkable until very recently. Slime moulds are currently studied in terms of their 'proto-cognitive' abilities [94][95][96].…”

Section: Sociomicrobiologymentioning

confidence: 99%

The brain: a concept in flux

Pagán

2019

Phil. Trans. R. Soc. B

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One of the most important aspects of the scientific endeavour is the definition of specific concepts as precisely as possible. However, it is also important not to lose sight of two facts: (i) we divide the study of nature into manageable parts in order to better understand it owing to our limited cognitive capacities and (ii) definitions are inherently arbitrary and heavily influenced by cultural norms, language, the current political climate, and even personal preferences, among many other factors. As a consequence of these facts, clear-cut definitions, despite their evident importance, are oftentimes quite difficult to formulate. One of the most illustrative examples about the difficulty of articulating precise scientific definitions is trying to define the concept of a brain. Even though the current thinking about the brain is beginning to take into account a variety of organisms, a vertebrocentric bias still tends to dominate the scientific discourse about this concept. Here I will briefly explore the evolution of our ‘thoughts about the brain’, highlighting the difficulty of constructing a universally (or even a generally) accepted formal definition of it and using planarians as one of the earliest examples of organisms proposed to possess a ‘traditional’, vertebrate-style brain. I also suggest that the time is right to attempt to expand our view of what a brain is, going beyond exclusively structural and taxa-specific criteria. Thus, I propose a classification that could represent a starting point in an effort to expand our current definitions of the brain, hopefully to help initiate conversations leading to changes of perspective on how we think about this concept. This article is part of the theme issue ‘Liquid brains, solid brains: How distributed cognitive architectures process information’.

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“…Physarum was also presented with tasks that required easy or difficult discrimination between separate food sources. When conditions of stress were imposed, individuals tended to make inaccurate or costly decisions [33]. This is an indication of a primary path of information flow which can be interfered with through cross reaction with others.…”

Section: Intelligent Behaviour In the Single Cell Physarum Polycephalummentioning

confidence: 99%

The foundations of plant intelligence

Trewavas

2017

Interface Focus.

104

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Intelligence is defined for wild plants and its role in fitness identified. Intelligent behaviour exhibited by single cells and systems similarity between the interactome and connectome indicates neural systems are not necessary for intelligent capabilities. Plants sense and respond to many environmental signals that are assessed to competitively optimize acquisition of patchily distributed resources. Situations of choice engender motivational states in goal-directed plant behaviour; consequent intelligent decisions enable efficient gain of energy over expenditure. Comparison of swarm intelligence and plant behaviour indicates the origins of plant intelligence lie in complex communication and is exemplified by cambial control of branch function. Error correction in behaviours indicates both awareness and intention as does the ability to count to five. Volatile organic compounds are used as signals in numerous plant interactions. Being complex in composition and often species and individual specific, they may represent the plant language and account for self and alien recognition between individual plants. Game theory has been used to understand competitive and cooperative interactions between plants and microbes. Some unexpected cooperative behaviour between individuals and potential aliens has emerged. Behaviour profiting from experience, another simple definition of intelligence, requires both learning and memory and is indicated in the priming of herbivory, disease and abiotic stresses.

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Brainless but Multi-Headed: Decision Making by the Acellular Slime Mould Physarum polycephalum

Cited by 77 publications

References 65 publications

The Computational Boundary of a “Self”: Developmental Bioelectricity Drives Multicellularity and Scale-Free Cognition

The Computational Boundary of a “Self”: Developmental Bioelectricity Drives Multicellularity and Scale-Free Cognition

The brain: a concept in flux

The foundations of plant intelligence

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