Spatial memory enhances an organism’s navigational ability. Memory typically resides within the brain, but what if an organism has no brain? We show that the brainless slime mold Physarum polycephalum constructs a form of spatial memory by avoiding areas it has previously explored. This mechanism allows the slime mold to solve the U-shaped trap problem—a classic test of autonomous navigational ability commonly used in robotics—requiring the slime mold to reach a chemoattractive goal behind a U-shaped barrier. Drawn into the trap, the organism must rely on other methods than gradient-following to escape and reach the goal. Our data show that spatial memory enhances the organism’s ability to navigate in complex environments. We provide a unique demonstration of a spatial memory system in a nonneuronal organism, supporting the theory that an externalized spatial memory may be the functional precursor to the internal memory of higher organisms.

https://www.pnas.org/content/pnas/109/43/17490.full.pdf

Slime mold uses an externalized spatial “memory” to navigate in complex environments

A Super-Assembly of Whi3 Encodes Memory of Deceptive Encounters by Single Cells during Yeast Courtship

Although human decision making seems complex, there is evidence that many decisions are grounded in simple heuristics. Such heuristic models of decision making are widespread in nature. To understa...

Who needs a brain? Slime moulds, behavioural ecology and minimal cognition:

This thesis is entitled “The Anatomy of a Minimal Mind”. By a “minimal mind” I mean the simplest kind of mind that could exist. As there is widespread philosophical disagreement about what a mind is, or what mental states are, I refrain from assuming at the outset that a minimal mind has to be phenomenally conscious, or subjectively aware of events in its surroundings. My objective is to identify the requirements that an organism would have to satisfy, before it could be credited with possessing a mind of any sort, however rudimentary. I then attempt to develop a detailed model of this minimal mind, using a conservative methodological approach: we should not interpret an organism's behaviour as a manifestation of underlying mental states unless doing so enables us to make better scientific predictions about its behaviour and/or explain its behaviour more fully. In section A, chapter one, I discuss the philosophical background to the contemporary discussion of minds and mental states. I defend the controversial claim that only living things can be said to have minds or mental states, and I argue that there are no convincing grounds for rejecting the common view that mental states are real phenomena. This in no way implies the more controversial view that all mental phenomena share some distinguishing feature that characterises them as mental. If, however, there is some distinguishing property which is common to all mental states, and only those states, then the two most promising philosophical candidates for this property would surely be consciousness and intentionality. I argue that the different varieties of consciousness distinguished by philosophers fail to “carve nature at the joints”. I then analyse the strengths and weaknesses of three common definitions of intentionality. Lastly, I examine Dennett’s intentional stance and argue that the two ways in which it can be formulated are in fact quite distinct. I propose that one of these formulations, which I refer to as the agent-centred intentional stance, can be used to help us identify creatures with minimal minds. In section B (chapters two to eight), I attempt to identify the necessary conditions for intentional agency in creatures, by examining several broad categories of behavioural and biological properties that have been proposed in the philosophical and scientific literature as relevant to having a mind, and sifting through them, all the while attempting to put together a constructive definition of a "minimal mind". In particular, I discuss sensory capacities (including discriminatory ability and perception); memory; flexible behaviour patterns; the ability to learn; self-directed movement and control; the ability to correct one's mistakes; and the ability to form concepts. Within each category of "mind-relevant" properties, I examine the different ways in which these properties are realised by different kinds of organisms, at various levels of complexity. The

The Anatomy of a Minimal Mind

Sensing, communication, navigation, decision-making, memory and learning are key components in a standard cognitive tool-kit that enhance an animal's ability to successfully survive and reproduce. However, these tools are not only useful for, or accessible to, animals-they evolved long ago in simpler organisms using mechanisms which may be either unique or widely conserved across diverse taxa. In this article, I review the recent research that demonstrates these key cognitive abilities in the plasmodial slime mould Physarum polycephalum, which has emerged as a model for non-animal cognition. I discuss the benefits and limitations of comparisons drawn between neural and non-neural systems, and the implications of common mechanisms across wide taxonomic divisions. I conclude by discussing future avenues of research that will draw the most benefit from a closer integration of Physarum and animal cognition research. 

/pdf/thoughts-from-the-forest-floor-a-review-of-cognition-in-the-3crjnrkb.pdf

Thoughts from the forest floor: a review of cognition in the slime mould Physarum polycephalum

Learning in technical artefacts is based on programming tools, like artificial neural nets These tools still restrict the individual development of an artefact too much To allow a proper unrestricted development in changing environments, new principles have to be applied in the construction of technical artefacts In order to study elementary mechanisms of learning and associated factors, we draw on two biological examples The study of unicellular biochemical networks can help to detect regularities, which are also present on higher levels of evolution Imprinting, as a form of individual learning, is based on mechanisms, which show the evolutionary rules of stochasticity, selection and reproducibility on the level of cell tissues The differences and analogies of biochemical and neural networks show elementary mechanism and principles as well as missing factors for the construction of programming tools in technical artefacts

Life-like learning in technical artefacts: biochemical vs. neuronal mechanisms

The electronic sports industry has been growing rapidly in the last years and is expected to grow further in the following years. Players are interested in getting better at games, which leads players to watch professional players or even hire coaches. We propose a method to automatically detect mistakes made in games based on artificial intelligence. Our method is going to help players gain more insight into how individual game events affect the outcome of the game and notify them about what they could have done differently to improve the probability of their team to win the game. We trained a neural network on matches of professional players to predict which actions players are going to perform. This allowed us to automatically detect situations where the difference between the predicted and acted behavior was high and the player probably could have performed a better action.

Detection of disadvantageous individual decisions for a game with fantastic elements

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Life-like learning in technical artefacts: biochemical vs. neuronal mechanisms

Detection of disadvantageous individual decisions for a game with fantastic elements