Relevant bibliographies by topics / Animal behaviour modelling

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Animal behaviour modelling'

Author: Grafiati
Published: 4 June 2021
Last updated: 12 February 2022

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Journal articles on the topic "Animal behaviour modelling"

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Sumpter, David J. T., Richard P. Mann, and Andrea Perna. "The modelling cycle for collective animal behaviour." Interface Focus 2, no. 6 (August 15, 2012): 764–73. http://dx.doi.org/10.1098/rsfs.2012.0031.

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Collective animal behaviour is the study of how interactions between individuals produce group level patterns, and why these interactions have evolved. This study has proved itself uniquely interdisciplinary, involving physicists, mathematicians, engineers as well as biologists. Almost all experimental work in this area is related directly or indirectly to mathematical models, with regular movement back and forth between models, experimental data and statistical fitting. In this paper, we describe how the modelling cycle works in the study of collective animal behaviour. We classify studies as addressing questions at different levels or linking different levels, i.e. as local, local to global, global to local or global. We also describe three distinct approaches—theory-driven, data-driven and model selection—to these questions. We show, with reference to our own research on species across different taxa, how we move between these different levels of description and how these various approaches can be applied to link levels together.
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Matetić, Maja, Slobodan Ribarić, and Ivo Ipšić. "Qualitative Modelling and Analysis of Animal Behaviour." Applied Intelligence 21, no. 1 (July 2004): 25–44. http://dx.doi.org/10.1023/b:apin.0000027765.12621.6f.

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Mäekivi, Nelly. "Modelling Ex Situ Animal Behaviour and Communication." Biosemiotics 9, no. 2 (May 10, 2016): 207–26. http://dx.doi.org/10.1007/s12304-016-9264-5.

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Smouse, Peter E., Stefano Focardi, Paul R. Moorcroft, John G. Kie, James D. Forester, and Juan M. Morales. "Stochastic modelling of animal movement." Philosophical Transactions of the Royal Society B: Biological Sciences 365, no. 1550 (July 27, 2010): 2201–11. http://dx.doi.org/10.1098/rstb.2010.0078.

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Modern animal movement modelling derives from two traditions. Lagrangian models, based on random walk behaviour, are useful for multi-step trajectories of single animals. Continuous Eulerian models describe expected behaviour, averaged over stochastic realizations, and are usefully applied to ensembles of individuals. We illustrate three modern research arenas. (i) Models of home-range formation describe the process of an animal ‘settling down’, accomplished by including one or more focal points that attract the animal's movements. (ii) Memory-based models are used to predict how accumulated experience translates into biased movement choices, employing reinforced random walk behaviour, with previous visitation increasing or decreasing the probability of repetition. (iii) Lévy movement involves a step-length distribution that is over-dispersed, relative to standard probability distributions, and adaptive in exploring new environments or searching for rare targets. Each of these modelling arenas implies more detail in the movement pattern than general models of movement can accommodate, but realistic empiric evaluation of their predictions requires dense locational data, both in time and space, only available with modern GPS telemetry.
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Ravignani, Andrea, and Koen de Reus. "Modelling Animal Interactive Rhythms in Communication." Evolutionary Bioinformatics 15 (January 2019): 117693431882355. http://dx.doi.org/10.1177/1176934318823558.

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Time is one crucial dimension conveying information in animal communication. Evolution has shaped animals’ nervous systems to produce signals with temporal properties fitting their socio-ecological niches. Many quantitative models of mechanisms underlying rhythmic behaviour exist, spanning insects, crustaceans, birds, amphibians, and mammals. However, these computational and mathematical models are often presented in isolation. Here, we provide an overview of the main mathematical models employed in the study of animal rhythmic communication among conspecifics. After presenting basic definitions and mathematical formalisms, we discuss each individual model. These computational models are then compared using simulated data to uncover similarities and key differences in the underlying mechanisms found across species. Our review of the empirical literature is admittedly limited. We stress the need of using comparative computer simulations – both before and after animal experiments – to better understand animal timing in interaction. We hope this article will serve as a potential first step towards a common computational framework to describe temporal interactions in animals, including humans.
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Taylor, R. A. J., Marc Mangel, and Colin W. Clark. "Dynamic Modelling in Behaviour Ecology." Journal of Animal Ecology 59, no. 3 (October 1990): 1200. http://dx.doi.org/10.2307/5050.

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Ruxton, Graeme D., John D. Armstrong, and Stuart Humphries. "Modelling territorial behaviour of animals in variable environments." Animal Behaviour 58, no. 1 (July 1999): 113–20. http://dx.doi.org/10.1006/anbe.1999.1114.

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Clark, Colin W. "Modelling the behaviour of fishers and fishes." ICES Journal of Marine Science 75, no. 3 (December 9, 2017): 932–40. http://dx.doi.org/10.1093/icesjms/fsx212.

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Abstract I describe my personal evolution as a modeller of behaviour, both human and (non-human) animal behaviour, using dynamic state-variable models. At first I worked in renewable resource Economics, especially the economics of marine fisheries where I collaborated extensively with Gordon R. Munro. Subsequently, in collaboration with Marc Mangel (and many field biologists) I worked in Behavioural Ecology. Mathematical models have played a major role in both of these subjects, but until recently mostly static models were used, on the grounds that dynamic (not to mention stochastic) models were too difficult to work with. I express the hope that our use of relatively simple (but not too simple) dynamic models has established the fact that such models can be extremely helpful, perhaps essential, in understanding many aspects of behaviour.
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Browne, K. A., M. N. Tamburri, and R. K. Zimmer-Faust. "Modelling quantitative structure-activity relationships between animal behaviour and environmental signal molecules." Journal of Experimental Biology 201, no. 2 (January 15, 1998): 245–58. http://dx.doi.org/10.1242/jeb.201.2.245.

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Quantitative structure-activity relationships (QSARs) between the physicochemical properties of environmental signal molecules and animal behaviour have been determined. Past work has shown that oyster and barnacle larval settlement and mud crab abdominal pumping (for larval dispersal) are stimulated by small peptide cues. In all the peptides examined that were active at ecologically relevant concentrations, arginine or lysine was found at the carboxy terminus, but the amino acids found at preceding positions were highly variable. We used the multivariate partial least squares algorithm to relate composite properties for the hydrophilicity, size and charge of each amino acid and the sequence position to oyster, barnacle and crab behaviour patterns. From the information in these QSAR models, the apparent variability in amino acid sequences eliciting behavioural responses was explained in each case, and more potent peptide analogues are hypothesized on the basis of untested amino acid sequences. Remarkably, these peptide signals are all structurally related to the carboxy-terminal sequence of mammalian C5a anaphylatoxin, a potent white blood cell chemoattractant. Even more striking is the fact that these different animal species should rely on apparently similar environmental signal molecules when residing within a common habitat (southeastern US estuaries). Through the physicochemical properties of amino acids, the current QSAR models clearly differentiate between the optimal sequences for eliciting oyster, barnacle and mud crab behaviour. Thus, QSARs provide a novel and powerful method not only for relating the physicochemical properties of molecules to animal behaviour but also for differentiating responses to chemicals by individuals of different species.
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Larson, Stephen D., Padraig Gleeson, and André E. X. Brown. "Connectome to behaviour: modelling Caenorhabditis elegans at cellular resolution." Philosophical Transactions of the Royal Society B: Biological Sciences 373, no. 1758 (September 10, 2018): 20170366. http://dx.doi.org/10.1098/rstb.2017.0366.

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It has been 30 years since the ‘mind of the worm’ was published in Philosophical Transactions B (White et al . 1986 Phil. Trans. R. Soc. Lond. B 314 , 1–340). Predicting Caenorhabditis elegans ' behaviour from its wiring diagram has been an enduring challenge since then. This special theme issue of Philosophical Transactions B combines research from neuroscientists, physicists, mathematicians and engineers to discuss advances in neural activity imaging, behaviour quantification and multiscale simulations, and how they are bringing the goal of whole-animal modelling at cellular resolution within reach. This article is part of a discussion meeting issue ‘Connectome to behaviour: modelling C. elegans at cellular resolution’.
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Dissertations / Theses on the topic "Animal behaviour modelling"

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Blackwell, Paul Gavin. "The stochastic modelling of social and territorial behaviour." Thesis, University of Nottingham, 1990. http://eprints.nottingham.ac.uk/13594/.

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This thesis considers mathematical models of the interaction between social and territorial behaviour in animals, mainly by probabilistic methods. Chapter 1 introduces the Resource Dispersion Hypothesis, which suggests that territorial behaviour plus dispersed food resources can explain the existence of social groups, and describes an existing model of the process, due to Carr and Macdonald. In Chapter 2 the model of Carr and Macdonald is analysed, and in Chapter 3 an improved model is suggested and its main properties derived, primarily using renewal theory. Chapters 4 and 5 consider various spatial models for territory formation, and the effect, of spatial factors on social behaviour, using analytic and simulation-based methods. Chapter 6 considers the evolution of social behaviour using both discrete-time deterministic models and branching processes to investigate the viability of different strategies of social behaviour in the presence of dispersed resources.
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Sumida, Brian Hiroshi. "Models of decision making." Thesis, University of Oxford, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.329967.

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Mlynski, David. "On the multivariate analysis of animal networks." Thesis, University of Bath, 2016. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.690727.

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From the individual to species level, it is common for animals to have connections with one another. These connections can exist in a variety of forms; from the social relationships within an animal society, to hybridisation between species. The structure of these connections in animal systems can be depicted using networks, often revealing non-trivial structure which can be biologically informative. Understanding the factors which drive the structure of animal networks can help us understand the costs and benefits of forming and maintaining relationships. Multivariate modelling provides a means to evaluate the relative contributions of a set of explanatory factors to a response variable. However, conventional modelling approaches use statistical tests which are unsuitable for the dependencies inherent in network and relational data. A solution to this problem is to use specialised models developed in the social sciences, which have a long history in modelling human social networks. Taking predictive multivariate models from the social sciences and applying them to animal networks is attractive given that current analytical approaches are predominantly descriptive. However, these models were developed for human social networks, where participants can self-identify relationships. In contrast, relationships between animals have to be inferred through observations of associations or interactions, which can introduce sampling bias and uncertainty to the data. Without appropriate care, these issues could lead us to make incorrect or overconfident conclusions about our data. In this thesis, we use an established network model, the multiple regression quadratic assignment procedure (MRQAP), and propose approaches to facilitate the application of this model in animal network studies. Through demonstrating these approaches on three animal systems, we make new biological findings and highlight the importance of considering data-sampling issues when analysing networks. Additionally, our approaches have wider applications to animal network studies where relationships are inferred through observing dyadic interactions.
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Liljenstolpe, Carolina. "Consumer valuation studies and structural modelling of the pig industry : a focus on animal welfare /." Uppsala : Dept. of Economics, Swedish University of Agricultural Sciences, 2008. http://epsilon.slu.se/200835.pdf.

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Bottinelli, Arianna. "Modelling collective movement and transport network formation in living systems." Doctoral thesis, Uppsala universitet, Tillämpad matematik och statistik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-303943.

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The emergence of collective patterns from repeated local interactions between individuals is a common feature to most living systems, spanning a variety of scales from cells to animals and humans. Subjects of this thesis are two aspects of emergent complexity in living systems: collective movement and transport network formation. For collective movement, this thesis studies the role of movement-mediated information transfer in fish decision-making. The second project on collective movement takes inspiration from granular media and soft mode analysis and develops a new approach to describe the emergence of collective phenomena from physical interactions in extremely dense crowds. As regards transport networks, this thesis proposes a model of network growth to extract simple, biologically plausible rules that reproduce topological properties of empirical ant trail networks.  In the second project on transport networks, this thesis starts from the simple rule of “connecting each new node to the closest one”, that describes ants building behavior, to study how balancing local building costs and global maintenance costs influences the growth and topological properties of transport networks. These projects are addressed through a modeling approach and with the aim of identifying minimal sets of basic mechanisms that are most likely responsible of large-scale complex patterns. Mathematical models are always based on empirical observations and are, when possible, compared to experimental data.
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Lecheval, Valentin. "Experimental analysis and modelling of the behavioural interactions underlying the coordination of collective motion and the propagation of information in fish schools." Thesis, Toulouse 3, 2017. http://www.theses.fr/2017TOU30361/document.

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Les bancs de poissons sont des entités pouvant regrouper plusieurs milliers d'individus qui se déplacent de façon synchronisée, dans un environnement sujet à de multiples perturbations, qu'elles soient endogènes (e.g. le départ soudain d'un congénère) ou exogènes (e.g. l'attaque d'un prédateur). La coordination de ces bancs de poissons, décentralisée, n'est pas encore totalement comprise. Si les mécanismes sous-jacents aux interactions sociales proposés dans des travaux précédents reproduisent qualitativement les structures collectives observées dans la nature, la quantification de ces interactions et l'accord quantitatif entre ces mesures individuelles et les motifs collectifs sont encore rares dans les recherches récentes et forment l'objet principal de cette thèse. L'approche de ce travail repose sur une étroite combinaison entre les méthodes expérimentales et de modélisation dans l'objectif de découvrir les liens entre les comportements individuels et les structures observées à l'échelle collective. Nous avons caractérisé et quantifié les interactions et mécanismes à l'origine, d'abord, de la coordination des individus dans les bancs de poissons et, ensuite, de la propagation d'information, quand le groupe subit une perturbation endogène ou exogène. Ces travaux, tous réalisés en étudiant la même espèce de poisson d'eau douce, le nez-rouge (Hemigrammus rhodostomus), ont mobilisé une diversité de méthodes expérimentales, d'analyses statistique et de modélisation, à l'interface de l'éthologie, de la physique statistique et des sciences computationnelles
Fish schools are systems in which thousands of individuals can move in a synchronised manner in a changing environment, with endogenous perturbations (e.g. when a congener leaves the group) or exogenous (e.g. the attack of a predator). The coordination of fish schools, decentralised, is not completely understood yet. If the mechanisms underlying social interactions discussed in previous studies qualitatively match the social patterns observed in nature, the quantification of these interactions and the quantitative match between individual measurements and collective patterns are still sparse in recent works and are the main focus of this thesis. This work combines closely experimental and modelling methods in order to investigate the links between the individual behaviours and the patterns observed at the collective scale. We have characterised and quantified the interactions and mechanisms at the origin of, first, the coordination of individuals in fish schools and, second, the propagation of information, when the group is under endogenous or exogenous perturbations. This thesis focuses on one freshwater fish species, the rummy-nose tetra (Hemigrammus rhodostomus), and is the result of a diversity of experimental methods, statistical analyses and modelling, at the interface of ethology, statistical physics and computational sciences
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Astudillo, Fernandez Aina. "Influence of the Allee effect and collective behaviour on population dynamics: the case of the two-spotted spider mite." Doctoral thesis, Universite Libre de Bruxelles, 2011. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209875.

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The Allee effect corresponds to a positive relationship between population size and individual fitness. This positive relationship can cause thresholds, that is, critical population sizes below which the population becomes extinct. For species submitted to the Allee effect, the formation and cohesion of groups is therefore crucial to survival. Animals can achieve this collective behaviour through local interactions. Each individual interacts locally with conspecifics and, at the scale of the group, a unity of behaviour emerges: the animals move together, rest in the same place, or choose the same habitat patch to settle on.

We use a combination of mathematical modelling and experimental work to study certain mechanisms of collective behaviour. In particular we assess the extent to which different individual interactions can induce collective patterns and thereby influence the dynamics of dispersal and settlement of populations. First, we study the collective settlement induced by the arresting effect of a marker secreted by conspecifics. Then, two potential mechanisms for collective movement are examined: following the conspecifics and following a trail laid by conspecifics. Finally, we integrate explicit mechanisms of dispersal behaviour in a dynamic model involving a set of interconnected populations. This allows the study of the interplay between collective movements and Allee effects at the scale of the metapopulation.

Our work is inspired by the lifestyle of the two-spotted spider mite, Tetranychus urticae, a phytophagous pest of recognised agricultural importance. These subsocial mites live in aggregates on the leaf surface, protected by a collectively spun silk web. Experimental evidence suggests that its population dynamics are subject to the Allee effect. Moreover, these mites show a tendency to migrate collectively, which makes them an appropriate biological model.
Doctorat en Sciences
info:eu-repo/semantics/nonPublished

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McKeown, Jennifer J. "Modelling the evolution of sexual behaviour." Thesis, University of Stirling, 2014. http://hdl.handle.net/1893/21823.

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This thesis presents two studies where natural and sexual selection have interacted to evolve sexual behaviours. The thesis uses mathematical modelling to understand how these forces have caused each behaviour to evolve. This is useful because the results allow for reflection on the potential role of sexual selection in adaptation of these species to a changing environment. The first study is of early male arrival to spring breeding grounds in migratory avian species, this is termed protandry. The study explores the main hypotheses for avian protandry and then tests the susceptibility of each hypothesis to changing environment. The second study is of convenience polyandry in species where there is conflict over mating rate. Females have multiple strategies to avoid harassive males but strategies vary in cost and success rate; she must balance her strategy use to minimise her fitness depreciation. The study identifies the main factors that cause convenience polyandry to evolve and paves the way for future studies to investigate if sexual selection over resistance strategy provides these species a future advantage in adaptation to a changing environment.
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Toal, Mark. "The behaviour of radiocaesium in woodland ecosystems : measurement and modelling." Thesis, University of Liverpool, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.366731.

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Aarts, Geert. "Modelling space-use and habitat preference from wildlife telemetry data." Thesis, St Andrews, 2007. http://hdl.handle.net/10023/327.

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Books on the topic "Animal behaviour modelling"

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Modelling complex projects. Chichester: Wiley, 2002.

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Williams, Terry. Modelling complex projects. Chichester: Wiley, 2002.

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Williams, Terry. Modelling complex projects. Chichester: Wiley, 2002.

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Williams, Terry. Modelling complex projects. Chichester: Wiley, 2002.

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Modelling Complex Projects. Wiley & Sons, Incorporated, John, 2003.

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Bradstock, Ross A., A. Malcolm Gill, and Richard J. Williams, eds. Flammable Australia. CSIRO Publishing, 2012. http://dx.doi.org/10.1071/9780643104839.

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In Flammable Australia: Fire Regimes, Biodiversity and Ecosystems in a Changing World, leading researchers in fire ecology and management discuss how fire regimes have shaped and will continue to shape the distribution and abundance of Australia’s highly diverse plants and animals. Central to this is the exploration of the concept of the fire regime – the cumulative pattern of fires and their individual characteristics (fire type, frequency, intensity, season) and how variation in regime components affects landscapes and their constituent biota. Contributions by 44 authors explore a wide range of topics including classical themes such as pre-history and evolution, fire behaviour, fire regimes in key biomes, plant and animal life cycles, remote sensing and modelling of fire regimes, and emerging issues such as climate change and fire regimes, carbon dynamics and opportunities for managing fire regimes for multiple benefits. In the face of significant global change, the conservation of our native species and ecosystems requires an understanding of the processes at play when fires and landscapes interact. This book provides a comprehensive treatment of this complex science, in the context of one of the world’s most flammable continents.
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Simpson, Stephen J., Carlos Ribeiro, and Daniel González-Tokman. Feeding behavior. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198797500.003.0008.

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Insects need to ingest nutrients at appropriate levels to attain a balanced diet and maximize fitness. They do so by integrated responses that involve physiological mechanisms for sensing current nutritional needs, releasing systemic signals, and producing specific appetites for key required nutrients. Historically, the study of insect feeding behavior was appreciated for its importance in the understanding and control of crop pests and disease vectors. However, current evidence has shown that some mechanisms regulating feeding are highly conserved in animals, from insects to humans, bringing additional interest in insects as models in medicine. The study of insect feeding behavior and nutrition has also given rise to an integrative modelling approach called the geometric framework for nutrition. This approach has proven useful beyond the insects, and allows the understanding of the impact of multiple nutrients on individuals and their interactions in populations, communities, and ecosystems.
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(Editor), T. Kumazawa, L. Kruger (Editor), and K. Mizumura (Editor), eds. The Polymodal Receptor - A Gateway to Pathological Pain (Progress in Brain Research). Elsevier Science, 1996.

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Takao, Kumazawa, Kruger Lawrence, and Mizumura Kazue, eds. The polymodal receptor: A gateway to pathological pain. Amsterdam: Elsevier, 1996.

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Book chapters on the topic "Animal behaviour modelling"

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Quinn, Matt, and Jason Noble. "Modelling Animal Behaviour in Contests: Conventions for Resource Allocation." In Advances in Artificial Life, 367–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44811-x_39.

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Gallagher, Elizabeth M., and Joanna J. Bryson. "Agent‐Based Modelling." In Encyclopedia of Animal Cognition and Behavior, 1–9. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-47829-6_224-1.

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Jørgensen, Søren V., Yves Demazeau, Jakob Christensen-Dalsgaard, and John Hallam. "Biomimetic Agent Based Modelling Using Male Frog Calling Behaviour as a Case Study." In From Animals to Animats 13, 88–97. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08864-8_9.

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Li, Cai, Robert Lowe, and Tom Ziemke. "Modelling Walking Behaviors Based on CPGs: A Simplified Bio-inspired Architecture." In From Animals to Animats 12, 156–66. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33093-3_16.

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Tolkamp, B. J., J. A. Howie, and I. Kyriazakis. "Modelling short-term feeding behaviour." In Modelling nutrient digestion and utilisation in farm animals, 103–11. Wageningen: Wageningen Academic Publishers, 2011. http://dx.doi.org/10.3920/978-90-8686-712-7_11.

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Nikodem, Jan. "Modelling of Collective Animal Behavior Using Relations and Set Theory." In Computer Aided Systems Theory - EUROCAST 2013, 110–17. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-53856-8_14.

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Najar, T., M. Rejeb, and M. Ben M. Rad. "Modelling of the effects of heat stress on some feeding behaviour and physiological parameters in cows." In Modelling nutrient digestion and utilisation in farm animals, 130–36. Wageningen: Wageningen Academic Publishers, 2011. http://dx.doi.org/10.3920/978-90-8686-712-7_14.

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Giger-Reverdin, S., M. Desnoyers, C. Duvaux-Ponter, and D. Sauvant. "Modelling within-day variability in feeding behaviour in relation to rumen pH: application to dairy goats receiving an acidogenic diet." In Modelling nutrient digestion and utilisation in farm animals, 121–29. Wageningen: Wageningen Academic Publishers, 2011. http://dx.doi.org/10.3920/978-90-8686-712-7_13.

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Chon, Tae-Soo, and Hungsoo Kim. "Modelling animal behavior to monitor effects of stressors." In Developments in Environmental Modelling, 87–114. Elsevier, 2015. http://dx.doi.org/10.1016/b978-0-444-63536-5.00005-3.

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Parrington, John. "Next Year’s Models." In Redesigning Life, 111–32. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198766834.003.0006.

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Animal ‘models’ of health and disease have been central to biomedical science since at least when William Harvey used dogs to illustrate the fact that blood is pumped by the heart through the arteries and then through the veins back to the heart. In the 1980s, a major step forward came with the discovery of embryonic stem cells and ways to manipulate these genetically and then inject into mouse embryos, resulting in the creation of knockout and knockin mice with deletions, or more subtle changes, in specific genes. Unfortunately, it has been impossible to isolate embryonic stem cells from any other species besides mice, and more recently rats and humans. Yet rodents are far from the best animals for modelling, say the body’s metabolism or heart function and disease, or brain function and mental disorders. Instead, pigs and primates are potentially far better models for these respective areas of research. CRISPR/Cas genome editing has made it possible for the first time to create precisely genome edited versions of pigs, monkeys, and any other species that may provide a better model of specific aspects of human health and disease, than rodents. So genetically modified pigs might be used to study heart disease, but also provide hearts for human transplantation, while GM monkeys might help us better understand the biological basis of mental disorders such as depression or schizophrenia. However, this area of research is raising ethical issues about the creation of monkeys with human versions of particular genes, and how this might affect their behaviour and personality.
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Conference papers on the topic "Animal behaviour modelling"

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Scogings, Chris J., and Ken A. Hawick. "Modelling Predator Camouflage Behaviour and Tradeoffs in an Agent-based Animat Model." In Modelling and Simulation. Calgary,AB,Canada: ACTAPRESS, 2013. http://dx.doi.org/10.2316/p.2013.802-032.

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Rashid, Badar, Michel Destrade, and Michael D. Gilchrist. "Hyperelastic and Viscoelastic Properties of Brain Tissue in Tension." In ASME 2012 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/imece2012-85675.

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Mechanical characterization of brain tissue at high loading velocities is particularly important for modelling Traumatic Brain Injury (TBI). During severe impact conditions, brain tissue experiences a mixture of compression, tension and shear. Diffuse axonal injury (DAI) occurs in animals and humans when the strains and strain rates exceed 10% and 10/s, respectively. Knowing the mechanical properties of brain tissue at these strains and strain rates is thus of particular importance, as they can be used in finite element simulations to predict the occurrence of brain injuries under different impact conditions. In this research, uniaxial tensile tests at strain rates of 30, 60 and 90/s up to 30% strain and stress relaxation tests in tension at various strain magnitudes (10%–60%) with an average rise time of 24 ms were performed. The brain tissue showed a stiffer response with increasing strain rates, showing that hyperelastic models are not adequate and that viscoelastic models are required. Specifically, the tensile engineering stress at 30% strain was 3.1 ± 0.49 kPa, 4.3 ± 0.86 kPa, 6.5 ± 0.76 kPa (mean ± SD) at strain rates of 30, 60 and 90/s, respectively. The Prony parameters were estimated from the relaxation data. Numerical simulations were performed using a one-term Ogden model to analyze hyperelastic and viscoelastic behavior of brain tissue up to 30% strain. The material parameters obtained in this study will help to develop biofidelic human brain finite element models, which subsequently can be used to predict brain injuries under impact conditions.
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