Adaptation and Learning in Fish: Effect of individual behavioral and informational variation on collective outcomes

Die in dieser Arbeit vorgestellten Arbeiten zielten darauf ab, verschiedene Formen des Lernens und der Verhaltensanpassung in Tieren zu testen. Hierbei wurder der Großteil dieser Arbeit an einer natürlich vorkommenden klonalen Fischart, der Amazonas-Molly Poecilia formosa, durchgeführt. Diese gesellige, ausschließlich weibliche Art erzeugt durch ungeschlechtliche Fortpflanzung genetisch identische Nachkommen. Mit dem Aufkommen von immer detaillierteren Ansätzen zur Unterscheidung von Verhaltensunterschieden sind solche klonalen Arten in der Ethologie von entscheidender Bedeutung, da sie als perfektes natürliches Modell dienen, um individuelle Verhaltensunterschiede und deren Entwicklung zu testen. Da genetische Variationen als Störfaktor weitgehend ausgeschlossen werden können, kann die Aufmerksamkeit auf die Unterschiede zwischen Individuen aufgrund ihrer Vorerfahrungen gelenkt werden. In den ersten drei Kapiteln der hier vorgestellten Arbeit wurden die individuellen Erfahrungen durch operante Konditionierung oder durch das Aussetzen der Tiere gegenüber neuen oder bekannten Situationen verändert. Das jeweilige Verhalten wurde sowohl alleine, als auch im sozialen Kontext untersucht. Auf diese Weise wurde die Auswirkung des sozialen Kontexts sowie der physischen Umgebung auf Verhaltensaspekte wie Schwimmgeschwindigkeit und Sprungwahrscheinlichkeit ermittelt. Kleinere Verhaltensunterschiede wurden dann im folgenden Kapitel durch den Vergleich von manuellen Ansätzen und automatischen Quantifizierungsinstrumenten bewertet und evaluiert. Schließlich wurde ein methodischer Ansatz augearbeitet, bei dem die Leistungsfähigkeit künstlicher intelligenz in Form von neuronalen Netze genutzt wurde, um Individuen in komplizierten, natürlichen Szenen während Räuber-Beute-Interaktionen zu verfolgen.The work presented in this thesis set out to test various forms of learning and behavior adaptation. The bulk of this work was done using a naturally occurring clonal fish species, the Amazon molly Poecilia formosa. This sociable, all female species produces genetically identical offspring through asexual reproduction. With the advent of increasingly detailed approaches to discriminate behavioral differences, such clonal species are vital in ethology as they serve as a perfect natural model to test for individual behavioral differences and the development of such. Since genetical variation can largely be excluded as a confounding factor, attention can be drawn towards the differences among individuals due to their prior experience. In the first three chapters of the work presented here, the individual information and experience was altered by applying operant conditioning or by exposing the animals to novel or well-known situations. This was done both individually and in a group setting. By doing so, the effect of the social context, as well as the physical surroundings on behavioral aspects such as swimming speed and jumping probability was determined. Minute behavioral differences were then evaluated in the following chapter by comparing manual approaches and automated quantification tools. Lastly, a methodological approach was taken in which the power of artifical neural networks was harnessed to track individuals in convoluted natural scenes during predator-prey interactions

The Invention of Good Games: Understanding Learning Design in Commercial Videogames

This work sought to help inform the design of educational digital games by the studying the design of successful commercial videogames. The main thesis question was: How does a commercially and critically successful modern video game support the learning that players must accomplish in order to succeed in the game (i.e. get to the end or win)? This work takes a two-pronged approach to supporting the main argument, which is that the reason we can learn about designing educational games by studying commercial games is that people already learn from games and the best ones are already quite effective at teaching players what they need to learn in order to succeed in the game. The first part of the research establishes a foundation for the argument, namely that accepted pedagogy can be found in existing commercial games. The second part of the work proposes new methods for analysing games that can uncover mechanisms used to support learning in games which can be employed even if those games were not originally designed as educational objects. In order to support the claim that ‘good’ commercial videogames already embody elements of sound pedagogy an explicit connection is made between game design and formally accepted theory and models in teaching and learning. During this phase of the work a significant concern was raised regarding the classification of games as ‘good’, so a new methodology using Borda Counts was devised and tested that combines various disjoint subjective reviews and rankings from disparate sources in non-trivial manner that accounts for relative standings. Complementary to that was a meta-analysis of the criteria used to select games chosen as subjects of study as reported by researchers. Then, several games were chosen using this new ranking method and analysed using another new methodology that was designed for this work, called Instructional Ethology. This is a new methodology for game design deconstruction and analysis that would allows the extraction of information about mechanisms used to support learning. This methodology combines behavioural and structural analysis to examine how commercial games support learning by examining the game itself from the perspective of what the game does. Further, this methodology can be applied to the analysis of any software system and offers a new approach to studying any interactive software. The results of the present study offered new insights into how several highly successful commercial games support players while they learn what they must learn in order to succeed in those games. A new design model was proposed, known as the 'Magic Bullet' that allows designers to visualize the relative proportions of potential learning in a game to assess the potential of a design

Reciprocity and reputation: a review of direct and indirect social information gathering

Direct reciprocity, indirect reciprocity, and reputation are important interrelated topics in the evolution of sociality. This non-mathematical review is a summary of each. Direct reciprocity (the positive kind) has a straightforward structure (e.g., “A rewards B, then B rewards A”) but the allocation might differ from the process that enabled it (e.g., whether it is true reciprocity or some form of mutualism). Indirect reciprocity (the positive kind) occurs when person (B) is rewarded by a third party (A) after doing a good deed towards somebody else (C) — with the structure “A observes B help C, therefore A helps B.” Here too, the allocation differs from the process: if there is underlying cognition, then indirect reciprocity is based on some ability to keep track of the reputations of others (to remember that “B helped C”). Reputation is a kind of social impression based on typicality, derived from three channels of experience (direct encounters, bystander observation, and gossip). Although non-human animals cannot gossip verbally, they can eavesdrop on third parties and learn vicariously. This paper ends with a proposal to investigate the topic of social expertise as a model for understanding how animals understand and utilise observed information within their social groups

Among Umwelten: Meaning-Making in Critical Posthumanism

Conceptualizations of meaning ground formulations of human/nonhuman animal similarity and difference. Anthropocentric accounts of meaning-making are increasingly untenable in light of contemporary knowledge of nonhuman life, yet they remain influential, implicit and intractable even within conceptual frameworks that otherwise reject their explicit premises. This study traces dynamic, process-oriented notions of meaning from Jakob von Uexkll's seminal work through autopoietic, phenomenological, biosemiotic and Deleuzian thought. I critically examine how this lineage counters Cartesian dualist and humanist notions of meaning-making in favour of a view of meaning as dynamic process. The relationship between organism and environment is characterized by Uexkll as a relationship of meaning. Uexkll envisions life as myriad complex melodic relations that entwine organism and environment in a practice of meaning-making. Uexkll's work and its extensions across a range of disciplines form a rich theoretical foundation for contemporary critical posthumanist efforts to change how human/nonhuman animal difference and similarity is conceptualized. Contemporary critical posthumanism especially the work of Karen Barad, Rosi Braidotti, Elizabeth Grosz and Cary Wolfe works to resituate human meaning-making within a wider ecological context. Yet a cohesive and comprehensive view of meaning grounded in critical posthumanism and its foundational works is fragmented across a broad and complex disciplinary and conceptual terrain. I draw out and develop from this literature the key components for a critical posthumanist concept of meaning

Computing Interpretable Representations of Cell Morphodynamics

Shape changes (morphodynamics) are one of the principal ways cells interact with their environments and perform key intrinsic behaviours like division. These dynamics arise from a myriad of complex signalling pathways that often organise with emergent simplicity to carry out critical functions including predation, collaboration and migration. A powerful method for analysis can therefore be to quantify this emergent structure, bypassing the low-level complexity. Enormous image datasets are now available to mine. However, it can be difficult to uncover interpretable representations of the global organisation of these heterogeneous dynamic processes. Here, such representations were developed for interpreting morphodynamics in two key areas: mode of action (MoA) comparison for drug discovery (developed using the economically devastating Asian soybean rust crop pathogen) and 3D migration of immune system T cells through extracellular matrices (ECMs). For MoA comparison, population development over a 2D space of shapes (morphospace) was described using two models with condition-dependent parameters: a top-down model of diffusive development over Waddington-type landscapes, and a bottom-up model of tip growth. A variety of landscapes were discovered, describing phenotype transitions during growth, and possible perturbations in the tip growth machinery that cause this variation were identified. For interpreting T cell migration, a new 3D shape descriptor that incorporates key polarisation information was developed, revealing low-dimensionality of shape, and the distinct morphodynamics of run-and-stop modes that emerge at minute timescales were mapped. Periodically oscillating morphodynamics that include retrograde deformation flows were found to underlie active translocation (run mode). Overall, it was found that highly interpretable representations could be uncovered while still leveraging the enormous discovery power of deep learning algorithms. The results show that whole-cell morphodynamics can be a convenient and powerful place to search for structure, with potentially life-saving applications in medicine and biocide discovery as well as immunotherapeutics.Open Acces