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

2019 ◽  
Vol 28 (6) ◽  
pp. 465-478 ◽  
Author(s):  
Jules Smith-Ferguson ◽  
Madeleine Beekman

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 understand how and why different forms of information processing evolve, it is insightful to study the minimal requirements for cognition. Here, we explore the minimally cognitive behaviour of the acellular slime mould, Physarum polycephalum, in order to discuss the ecological pressures that lead to the development of information processing mechanisms. We discuss evidence for memory, basic forms of learning and economically irrational choice in P. polycephalum. We compare P. polycephalum’s behaviour with a number of other non-neuronal organisms in order to question the evolutionary need for complex nervous systems to develop cognitive traits. By highlighting a few examples of common mechanisms, we conclude that all organisms contain the building blocks for more complex information processing. Returning the debate about cognition to the biological basics demystifies some of the confusion around the term ‘cognition’.

2019 ◽  
Vol 28 (4) ◽  
pp. 261-271
Author(s):  
Gašper Štukelj

Recent evidence suggests that the take-the-best heuristic—flagship of “fast and frugal heuristics” research program—might in fact not be as frugal as tallying, which is considered to be a more complex strategy. Characterizing a simple decision strategy has always seemed straightforward, and the debate around the simplicity of the take-the-best heuristic is mostly concerned with a proper specification of the heuristic. I argue that the predominate conceptions of “simplicity” and “frugality” need to be revised. To this end, a number of recent behavioral and neuroscientific results are discussed. The example of take-the-best heuristic serves as an entry point to a foundational debate on bounded agency. I argue that the fast and frugal heuristics needs to question some of its legacy from the classical AI research. For example, the assumption that the bottleneck of decision-making process is information processing due to its serial nature. These commitments are hard to reconcile with the modern neuroscientific view of a human decision-maker. In addition, I discuss an overlooked source of uncertainty, namely neural noise, and compare a generic heuristic model to a similar neural algorithm.


Author(s):  
John A. Sauceda ◽  
Karine Dubé ◽  
Brandon Brown ◽  
Ashley E. Pérez ◽  
Catherine E. Rivas ◽  
...  

HIV cure research carries serious risks and negligible benefits. We investigated how participants understand these risks and what influences their willingness to participate. Through internet-based and in-person convenience sampling, 86 HIV+ participants completed an experimental survey. Participants were randomized to read a standard consent form describing a hypothetical HIV cure study or one adapted using Fuzzy Trace Theory—a decision-making model to facilitate complex information processing. We measured consent understanding and cognitive (e.g., safe/harmful) and affective (e.g., concerning, satisfying) evaluations of HIV cure research. Participants who read the adapted consent form had improved consent understanding, but only positive affective evaluations were associated with a willingness to participate. Consent processes can use decision-making theories to facilitate comprehension of study information.


2019 ◽  
Vol 9 (7) ◽  
pp. 1297
Author(s):  
Shuai Liu ◽  
Carlo Cattani ◽  
Yudong Zhang

Fractal characteristic, one typical nonlinear characteristic, is applied as a key characteristic in complex information processing and used in many research domains [...]


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