Chapter 51 Animal Behavior
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A Hybrid Computational Model for Collective Cell Durotaxis
Biomechanics and Modeling in Mechanobiology https://doi.org/10.1007/s10237-018-1010-2 ORIGINAL PAPER A hybrid computational model for collective cell durotaxis Jorge Escribano1 · Raimon Sunyer2,5 · María Teresa Sánchez3 · Xavier Trepat2,4,5,6 · Pere Roca-Cusachs2,4 · José Manuel García-Aznar1 Received: 13 September 2017 / Accepted: 17 February 2018 © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract Collective cell migration is regulated by a complex set of mechanical interactions and cellular mechanisms. Collective migration emerges from mechanisms occurring at single cell level, involving processes like contraction, polymerization and depolymerization, of cell–cell interactions and of cell–substrate adhesion. Here, we present a computational framework which simulates the dynamics of this emergent behavior conditioned by substrates with stiffness gradients. The computational model reproduces the cell’s ability to move toward the stiffer part of the substrate, process known as durotaxis. It combines the continuous formulation of truss elements and a particle-based approach to simulate the dynamics of cell–matrix adhesions and cell–cell interactions. Using this hybrid approach, researchers can quickly create a quantitative model to understand the regulatory role of different mechanical conditions on the dynamics of collective cell migration. Our model shows that durotaxis occurs due to the ability of cells to deform the substrate more in the part of lower stiffness than in the stiffer part. This effect explains why cell collective movement is more effective than single cell movement in stiffness gradient conditions. In addition, we numerically evaluate how gradient stiffness properties, cell monolayer size and force transmission between cells and extracellular matrix are crucial in regulating durotaxis. -
Mathematical Modelling and Analysis of Aspects of Planktonic Bacterial Motility
Mathematical modelling and analysis of aspects of planktonic bacterial motility Gabriel Aaron Rosser St Anne's College University of Oxford A thesis submitted for the degree of Doctor of Philosophy Michaelmas 2012 Contents 1 The biology of bacterial motility and taxis 8 1.1 Bacterial motility and taxis . .8 1.2 Experimental methods used to probe bacterial motility . 14 1.3 Tracking . 20 1.4 Conclusion and outlook . 21 2 Mathematical methods and models of bacterial motility and taxis 23 2.1 Modelling bacterial motility and taxis: a multiscale problem . 24 2.2 The velocity jump process . 34 2.3 Spatial moments of the general velocity jump process . 46 2.4 Circular statistics . 49 2.5 Stochastic simulation algorithm . 52 2.6 Conclusion and outlook . 54 3 Analysis methods for inferring stopping phases in tracking data 55 3.1 Analysis methods . 58 3.2 Simulation study comparison of the analysis methods . 76 3.3 Results . 80 3.4 Discussion and conclusions . 86 4 Analysis of experimental data 92 4.1 Methods . 92 i 4.2 Results . 109 4.3 Discussion and conclusions . 124 5 The effect of sampling frequency 132 5.1 Background and methods . 133 5.2 Stationary distributions . 136 5.3 Simulation study of dynamic distributions . 140 5.4 Analytic study of dynamic distributions . 149 5.5 Discussion and conclusions . 159 6 Modelling the effect of Brownian buffeting on motile bacteria 162 6.1 Background . 163 6.2 Mathematical methods . 166 6.3 A model of rotational diffusion in bacterial motility . 173 6.4 Results . 183 6.5 Discussion and conclusion . -
Thermotaxis Is a Robust Mechanism for Thermoregulation in Caenorhabditis Elegans Nematodes
12546 • The Journal of Neuroscience, November 19, 2008 • 28(47):12546–12557 Behavioral/Systems/Cognitive Thermotaxis is a Robust Mechanism for Thermoregulation in Caenorhabditis elegans Nematodes Daniel Ramot,1* Bronwyn L. MacInnis,2* Hau-Chen Lee,2 and Miriam B. Goodman1,2 1Program in Neuroscience and 2Department of Molecular and Cellular Physiology, Stanford University, Stanford, California 94305 Many biochemical networks are robust to variations in network or stimulus parameters. Although robustness is considered an important design principle of such networks, it is not known whether this principle also applies to higher-level biological processes such as animal behavior. In thermal gradients, Caenorhabditis elegans uses thermotaxis to bias its movement along the direction of the gradient. Here we develop a detailed, quantitative map of C. elegans thermotaxis and use these data to derive a computational model of thermotaxis in the soil, a natural environment of C. elegans. This computational analysis indicates that thermotaxis enables animals to avoid temperatures at which they cannot reproduce, to limit excursions from their adapted temperature, and to remain relatively close to the surface of the soil, where oxygen is abundant. Furthermore, our analysis reveals that this mechanism is robust to large variations in the parameters governing both worm locomotion and temperature fluctuations in the soil. We suggest that, similar to biochemical networks, animals evolve behavioral strategies that are robust, rather than strategies that rely on fine tuning of specific behavioral parameters. Key words: behavior; C. elegans; temperature; neuroethology; computational models; robustness Introduction model to investigate the ability of thermotaxis to regulate Tb and its robustness to genetic and environmental perturbation. -
Way-Finding in Displaced Clock-Shifted Bees Proves Bees Use a Cognitive Map
Way-finding in displaced clock-shifted bees proves bees use a cognitive map James F. Cheesemana,b,1, Craig D. Millarb,c, Uwe Greggersd, Konstantin Lehmannd, Matthew D. M. Pawleya,e, Charles R. Gallistelf,1, Guy R. Warmana,b, and Randolf Menzeld aDepartment of Anaesthesiology, School of Medicine, and bSchool of Biological Sciences, University of Auckland, Auckland, 1142, New Zealand; cAllan Wilson Centre for Molecular Ecology and Evolution, Palmerston North, PN4442, New Zealand; dInstitute of Biology–Neurobiology, Free University of Berlin, 14195 Berlin, Germany; eInstitute of Natural and Mathematical Sciences, Massey University, Auckland, 0745, New Zealand; and fDepartment of Psychology and Center for Cognitive Science, Rutgers University, Piscataway, NJ 08854-8020 Contributed by Charles R. Gallistel, May 1, 2014 (sent for review January 22, 2014) Mammals navigate by means of a metric cognitive map. Insects, whether these abilities rest on the construction and use of most notably bees and ants, are also impressive navigators. The a metric cognitive map (11–18). question whether they, too, have a metric cognitive map is Way-finding, the ability to set a course from one familiar but important to cognitive science and neuroscience. Experimentally otherwise arbitrarily chosen location to another location that is captured and displaced bees often depart from the release site in not perceptible from the first, is the signature of a metric cog- the compass direction they were bent on before their capture, nitive map. Displacing an animal from its current location to an even though this no longer heads them toward their goal. When experimenter-chosen location within the territory the animal is they discover their error, however, the bees set off more or less presumed to be familiar with, and then observing its subsequent directly toward their goal. -
The Honey Bee Dance Language
The Honey Bee Dance Language Background Components of the dance language Honey bee dancing, perhaps the most intriguing aspect of their biology, is also one of the most fascinating behaviors When an experienced forager returns to the colony with in animal life. Performed by a worker bee that has returned a load of nectar or pollen that is sufficiently nutritious to to the honey comb with pollen or nectar, the dances, in warrant a return to the source, she performs a dance on the essence, constitute a language that “tells” other workers surface of the honey comb to tell other foragers where the where the food is. By signaling both distance and direction food is. The dancer “spells out” two items of information— with particular movements, the worker bee uses the dance distance and direction—to the target food patch. Recruits language to recruit and direct other workers in gathering then leave the hive to find the nectar or pollen. pollen and nectar. Distance and direction are presented in separate compo- The late Karl von Frisch, a professor of zoology at the Uni- nents of the dance. versity of Munich in Germany, is credited with interpret- ing the meaning of honey bee dance movements. He and Distance his students carried out decades of research in which they carefully described the different components of each dance. When a food source is very close to the hive (less than 50 Their experiments typically used glass-walled observation meters), a forager performs a round dance (Figure 1). She hives and paint-marked bee foragers. -
Neuroethlogy NROC34 Course Goals How? Evaluation
Course Goals Neuroethlogy NROC34 • What is neuroethology? • Prof. A. Mason – Role of basic biology – Model systems (mainly invertebrate) • e-mail: – Highly specialized organisms – [email protected] – Biomimetics – [email protected] • Primary literature and the scientific process – No textbook – subject = NROC34 – But if you really want one, there are a couple of suggestion on the • Office Hours: Friday, 1 – 4:00 pm, SW566 syllabus • Basic principles of integrative neural function • Weekly Readings: download from course webpage – More on this a bit later www.utsc.utoronto.ca/amason/courses/coursepage/syllabus2012.html NROC34 2012:1 1 NROC34 2012:1 2 How? Evaluation • Case studies of several model systems – Different kinds of questions – Different kinds of research (techniques) • Weekly readings 5% – Sensory, motor, decision-making… • Mid-term 35-45% • Selected papers each week • Final Exam 45-60% – Read before, discuss during: usually readings are challenging and “discussion” means me explaining (so • Presentation (optional) 10% don’t be discouraged) • Most topics include current work • Weekly reading marks: each week several – Take you to the leading edge of research in selected people will be selected at random to areas contribute 3 questions about the papers. NROC34 2012:1 3 NROC34 2012:1 4 1 Information Neuroethology • Who are you people? • The study of the neural mechanisms • What do you expect to learn in this course? underlying behaviour that is biologically • What previous course have you taken in: relevant to the animal performing it. – neuroscience • This encompasses many basic mechanisms – Behaviour of the nervous system. • Is this a req’d course for you? • Combines behavioural analysis and neurophysiology NROC34 2012:1 5 NROC34 2012:1 6 Neurobiology Behavioural Science • What do I mean by “integrative neural function”? • What does the nervous system do? • Ethology • Psychology – detect information in the environment – biological behaviour – abstract concepts (e.g. -
The Behavior of Fishes by Antonios Pappantoniou
The Behavior of Fishes by Antonios Pappantoniou I. A GENERAL OVERVIEW OF FISH BEHAVIOR This article is the first in a series of articles on the behavior of North American freshwater fishes. Althou~h this first ~rticle will not stress any species in particular, each !~ture article will focus on the behavior of a single species or group of closely related fishes. It is the intent of the articles to supply the readers with a knowledge of fish behavior so that they may better understand and enjoy their aquarium fishes. The articles will draw on information from the scien tific literat~re and the authors' own observations. The behavior of fishes is very much dictated by their environment. Two factors, temperature and light, are probably the most critical environmental factors control ling fish behavior. Fish are classed as ectothermic animals. Ectothermic means they must rely on outside sources of he~r. to maintain their body temperature. Temperature governs biochemical and physiological activities which in turn control fish behavior. The preferred te~perature of fish varies with the species. Fish species adapted to swift-flowing streams prefer cooler temperatures than those species adapted to life in a small pond. Temperatures may fluctuate on a daily or seasonal basis. Daily fluctuations, especially in the s~~er months, can cause onshore - offshore movements in species of lake fish. Seasonal changes in temperature are partly responsible for initiati~g physiological changes which lead to reproductive activity in fish. Light is the other critical environmental factor controlling fish behavior. 1 fish may be diurnal. Such a fish would be active during the day. -
Behavioral Ecology
AP BIOLOGY BEHAVIORAL ECOLOGY 1. Define the following terms: Ethology Behavior 2. Match the description/example with the correct behavior category. A. Classical conditioning E. Insight B. Fixed-action pattern F. Instinct (innate) C. Habituation G. Observational learning D. Imprinting H. Operant conditioning Behaviors that are inherited Performed virtually the same by all individuals regardless of environmental conditions In mammals, the female parent cares for offspring Highly stereotyped sequence of behaviors that, once begun, is usually carried to completion Triggered by a sign stimulus When a graylag goose sees an egg outside her next, she will methodically roll the egg back into the nest. The egg outside the nest is the stimulus. Even if the egg is removed or slips away, she completes the behavior by returning an “imaginary” egg to the nest Male stickleback fish defend their territory against other males. The red belly of males is the stimulus for aggressive behavior. Nikolass Tinbergen discovered any object with a red underside triggers the same aggressive behavior Learning that occurs during a specific time period; generally irreversible Konrad Lorenz discovered that during the first two days of life, graylag goslings will accept any moving object as their mother (even a human) Association of irrelevant stimulus with a fixed physiological response Animal performs a behavior in response to a substitute stimulus rather than the normal stimulus Pavlov’s dogs; dogs were conditioned to salivate in response to a bell Trial and error learning -
AP Biology Lab 11: Roly Poly Enhanced Interrogation Animal
AP Biology Lab 11: Roly Poly Enhanced Interrogation Animal Behavior1 Overview In this lab you will observe the behavior of pill bugs and design an experiment to investigate their responses to environmental variables. Objectives Before doing this lab you should understand: 1. The concept of distribution of organisms in a resource gradient, and 2. The difference between kinesis and taxis. After doing this lab you should be able to: 1. describe some aspects of animal behavior, such as orientational behavior, agonistic behavior, dominance display, or mating behavior, and 2. Understand the adaptiveness of the behaviors you studied. 3. How to quantitively analyze your results using chi-square. Introduction Ethology is the study of animal behavior. Behavior is an animal’s response to sensory input and falls into two basic categories: learned and innate (inherited). Orientation behaviors place the animal in its most favorable environment. In taxis, the animal moves toward or away from a stimulus. Taxis are often exhibited when the stimulus is light, heat, moisture, sound, or chemicals. Kinesis is a movement that is random and does not result in orientation with respect to a stimulus. If an organism responds to bright light by moving away, that is taxis. If an organism responds to bright light by random movements in all directions, that is kinesis. Agonistic behavior is exhibited when animals respond to each other by aggressive or submissive responses. Often the agonistic behavior is simply a display that makes the organism look big or threatening. It is sometimes studied in the laboratory with Bettas (Siamese fighting fish). Mating behaviors may involve a complex series of activities that facilitate finding, courting, and mating with a member of the same species. -