Structure emerges faster during cultural transmission in children than in adults

How does children’s limited processing capacity affect cultural transmission of complex information? We show that over the course of iterated reproduction of two-dimensional random dot patterns transmission accuracy increased to a similar extent in 5- to 8-year-old children and adults whereas algorithmic complexity decreased faster in children. Thus, children require more structure to render complex inputs learnable. In line with the Less-Is-More hypothesis, we interpret this as evidence that children’s processing limitations affecting working memory capacity and executive control constrain the ability to represent and generate complexity, which, in turn, facilitates emergence of structure. This underscores the importance of investigating the role of children in the transmission of complex cultural traits

Natural scene statistics mediate the perception of image complexity

Humans are sensitive to complexity and regularity in patterns. The subjective perception of pattern complexity is correlated to algorithmic (Kolmogorov-Chaitin) complexity as defined in computer science, but also to the frequency of naturally occurring patterns. However, the possible mediational role of natural frequencies in the perception of algorithmic complexity remains unclear. Here we reanalyze Hsu et al. (2010) through a mediational analysis, and complement their results in a new experiment. We conclude that human perception of complexity seems partly shaped by natural scenes statistics, thereby establishing a link between the perception of complexity and the effect of natural scene statistics

Adults are more efficient in creating and transmitting novel signalling systems than children

Iterated language learning experiments have shown that meaningful and structured signalling systems emerge when there is pressure for signals to be both learnable and expressive. Yet such experiments have mainly been conducted with adults using language-like signals. Here we explore whether structured signalling systems can also emerge when signalling domains are unfamiliar and when the learners are children with their well-attested cognitive and pragmatic limitations. In Experiment 1, we compared iterated learning of binary auditory sequences denoting small sets of meanings in chains of adults and 5-7-year old children. Signalling systems became more learnable even though iconicity and structure did not emerge despite applying a homonymy filter designed to keep the systems expressive. When the same types of signals were used in referential communication by adult and child dyads in Experiment 2, only the adults, but not the children, were able to negotiate shared iconic and structured signals. Referential communication using their native language by 4-5-year old children in Experiment 3 showed that only interaction with adults, but not with peers resulted in informative expressions. These findings suggest that emergence and transmission of communication systems is unlikely to be driven by children, and point to the importance of cognitive maturity and pragmatic expertise of learners as well as feedback-based scaffolding of communicative effectiveness by experts during language evolution

Algorithmic Complexity for Short Binary Strings Applied to Psychology: A Primer

Since human randomness production has been studied and widely used to assess executive functions (especially inhibition), many measures have been suggested to assess the degree to which a sequence is random-like. However, each of them focuses on one feature of randomness, leading authors to have to use multiple measures. Here we describe and advocate for the use of the accepted universal measure for randomness based on algorithmic complexity, by means of a novel previously presented technique using the the definition of algorithmic probability. A re-analysis of the classical Radio Zenith data in the light of the proposed measure and methodology is provided as a study case of an application.Comment: To appear in Behavior Research Method

Sloane’s Gap: Do Mathematical and Social Factors Explain the Distribution of Numbers in the OEIS?

The Online Encyclopedia of Integer Sequences (OEIS) is a catalog of integer sequences. We are particularly interested in the number of occurrences of N(n) of an integer n in the database. This number N(n) marks the importance of n and it varies noticeably from one number to another, and from one number to the next in a series. “Importance” can be mathematically objective (2^10 is an example of an “important” number in this sense) or as the result of a shared mathematical culture (10^9 is more important than 9^10 because we use a decimal notation). The concept of algorithmic complexity (also known as Kolmogorov or Kolmogorov-Chaitin complexity) will be used to explain the curve shape as an “objective” measure. However, the observed curve does not conform to the curve predicted by an analysis based on algorithmic complexity because of a clear gap separating the distribution into two clouds of points. We shall call this phenomenon “Sloane’s gap”

The Philosophy of Taking Conspiracy Theories Seriously

During the last few decades, the proliferation of interest in conspiracy theories became a widespread phenomenon in our culture, and also in academia. In this piece, I review a new book on the topic of conspiracy theory theory (that is-the theory of conspiracy theories) Taking Conspiracy Theories Seriously, edited by M R. X. Dentith. To contextualize the review, I first turn to the '90s, to see what sparked current interest in conspiracy theories within the field of analytic philosophy. I then critically asses the current limitations of social epistemology, as a field. Among other things, I show how accepted assumptions in social epistemology cause cross-disciplinary disagreements with other social sciences, present the dilemma of trivializing whistle-blowers, and discuss few neglected roles technologies play in belief formation

Influence of diesel fuel on seed germination

The use of plant-based systems to remediate contaminated soils has become an area of intense scientific study in recent years and it is apparent that plants which grow well in contaminated soils need to be identified and screened for use in phytoremediation technologies. This study investigated the effect of diesel fuel on germination of selected plant species. Germination response varied greatly with plant species and was species specific, as members of the same plant family showed differential sensitivity to diesel fuel contamination. Differences were also seen within plant subspecies. At relatively low levels of diesel fuel contamination, delayed seed emergence and reduced percentage germination was observed for the majority of plant species investigated. Results suggest the volatile fraction of diesel fuel played an influential role in delaying seed emergence and reducing percentage germination. In addition, the remaining diesel fuel in the soil Lidded to this inhibitory effect on germination by physically impeding water and oxygen transfer between the seed and the surrounding soil environment, thus hindering the germination response

Evaluation of functional arterial spin labeling data using a perfusion template

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