Madison Chaos and Complex Systems Seminar

Fall 1997 Seminars

Dates, speakers, titles and abstracts will be listed as they become available. Meetings will be noon Tuesdays in 4274 Chamberlin Hall unless otherwise noted.

Short List

9 September. Ray Kent, UW Communicative Disorders: ``Sounding Off in the First Year of Life: The Complex System of Infant Vocalization.''

Abstract: Beginning with the birth cry and proceeding through grunts, babbles, and maybe first words, the typical infant accomplishes a number of vocal milestones in this so-called ``prespeech'' period from birth to one year of age. This talk reviews some recent perspectives from complex systems theory as they relate to vocal development.

16 September. Cosma Shalizi, UW Physics: ``Uncovering Structure and Understanding How Nature Computes: The Program of Computational Mechanics.''

Abstract: The problem of discovering structures or regularities in nature is ancient, but one of best example of why it is a problem comes from the fairly recent study of chaotic dynamical systems, where the surface data (apparently pure noise) conceal very regular patterns (strange attractors), which eluded detection for decades. ``Computational mechanics'' is a still-developing body of techniques, drawing on statistical physics, and the theories of dynamical systems and computation, for discovering causal structures and characterizing them in computational terms. In addition to its use in the natural sciences, it may help settle long-standing and acrimonious debates about the sense in which natural objects (like brains) can be said to compute. I will start with a little on the philosophical and methodological background, go over some (simple) examples of how the techniques can be applied, and conclude by hand-waving about computation in nervous systems.

23 September. George E. Hrabovsky, UW Physics: ``Tornadoes and the Development of Unpredictability.''

Abstract: For forty years the meteorological community has wrestled with the problem of predicting severe weather in general, and tornadoes in particular. Beginning with the SELS (SEvere Local Storms) unit, several large-scale atmospheric correspondences were noted in the mid- to late-fifties. These observations allowed the first severe weather watches to be issued. In the sixties we saw the advent of weather radar in widespread use and weather reconnaisance satellites both of which improved the success rate of the severe weather watches. In the seventies we saw the advent of Doppler radar, numerical simulations of thunderstorms, and the first true scientific storm chasing; these developments combined to produce a model of tornado formation which has stood until the last three years. It was thought until recently that Doppler radar could detect tornadic circulations as much as a half hour before the tornado formed, all that had to be done was to warn the public; it seemed to be a panacea. We are beginning to realize that Doppler radar cannot do this and may not be able to detect tornadic circulations farther than a few kilometers from the radar. This then is the development of unpredictability.

30 September. Edward R. Pope, UW Art: ``Algorithmic Art: Beginnings, Some Present Directions.''

Abstract: This talk will provide a brief review of the history of algorithmic art, and a discussion, with visual examples, of the aesthetic concepts and realization of such work contemporarily.

7 October. Deric Bownds, UW Zoology: ``The Evolution of Human Minds.''

Abstract: This talk is a brief review of contemporary models describing each of us as a society of mind that emerges from our evolutionary history and the details of how our brains form as we grow up in a particular natural ecology and cultural setting.

14 October. Rick Lindroth, UW Entomology: ``Chemical Ecology of Aspen: Environment-Plant-Insect-Pathogen Interactions.''

Abstract: Quaking aspen (Populus tremuloides) is the most widely distributed tree species in North America. It occurs in a great diversity of habitats and plays a central role in the ecological dynamics of early successional forests. Fundamental insights into the ecological interactions of aspen have been afforded by evaluation of the role of chemistry (especially ``defensive'' compounds) in such interactions. Aspen exhibits tremendous chemical variation in the field. Such variation is a consequence of genetic variability interacting with differential availability of resources (light, nutrients, CO2). Chemical variation in turn influences the interactions of aspen with insect herbivores, and the interactions of herbivores with their own natural enemies. This complex interplay of bottom-up and top-down ecological processes through evolutionary time is responsible for production of the current mosaic of chemical phenotypes in aspen forests.

21 October. Teresa Hayden, UW Psychology: ``Complex Systems and Problematic Human Behavior.''

Abstract: How might Clinical psychologists apply some of the concepts of complex systems theory to understanding everyday personal problems? In this non-mathematical talk I will derive a meta-model of problematic human behavior from the four major schools of Psychotherapy. This meta-model describes patterns of problematic behavior which are often repeated in various situations and for long periods of time. Given the repetitive character of problematic behavior, we could then ask about some possible features of these iterating patterns: Will new properties emerge? What are some candidates for control parameters in these systems? What might be the role of consciousness in change?

28 October. Dave Albers, UW Physics: ``Routes to Chaos in Neural Networks with Random Weights.''

Abstract: Neural networks are universal approximators; they can be used to model any dynamical system. I will discuss a Monte Carlo study of the dynamical behavior of neural networks with randomly chosen connection strengths. I will show that as the networks become more complicated, the probability that they exhibit chaotic dynamics approaches unity. I will present theoretical and experimental results showing that as the dimension of the networks increases, the quasi-periodic route to chaos dominates. I will also qualitatively describe the dynamics along the route to chaos.

4 November. Bill Lytton, UW Neurology: ``Dynamics of Stroke Recovery.''

Abstract: A simple neural network was used to model physiological data from cells surviving a stroke in visual cortex. Immediate changes observed experimentally included both expansions and contractions in the range of stimuli (receptive field) to which an individual cell would respond, and alterations in maximal activation levels. Observed changes could be largely explained by the dynamics of the network, without any changes in connection weights. Death of individual units directly altered the patterns of excitation even without any change in connectivity. These activity changes might be regarded as ``dynamic plasticity'' that would then determine the pattern of subsequent true plastic changes through Hebbian mechanisms (increases in connection strength between simultaneously active units). We have now extended the network to make behavioral predictions. This will aid in development of new strategies for improving patients' recovery after stroke.

11 November. Rus Yukhananov, UW Anesthesiology: ``Bifurcation Model of Drug Dependence.''

Abstract: Addiction is not an acute but a chronic relapsing disorder. The current model of addiction, based on principles of homeostasis, cannot explain why the disorder persists long after the cessation of drug administration. This is an attempt to modify the homeostatic model to explain the transition from the normal to the addicted state. Using nonlinear equations I try to describe a possible scenario for nervous system transformation from normal to an addicted state, which can last indefinitely even in the absence of narcotics.

18 November. Jean-Paul Chavas, UW Agricultural and Applied Economics: ``Chaos in Dairy Land.''

Abstract: The U.S. dairy markets have seen a sharp increase in instability over the last two years. A nonlinear dynamic model is developed and estimated. It shows that market instability and chaos are linked to there important factors: the dynamics of the cow herd, the inelasticity of demand for dairy products, and recent changes in government dairy pricing policy.

25 November. Marcie J. Myers, UW Biology Core Curriculum: ``Can Nonlinear Methods Help Us Understand the Dynamics of Human Movement?''

Abstract: Rhythmic movement in humans and other animals is presumably the result of complex dynamic interactions between morphology (musculo-skeletal system, inertial properties), neural input (central nervous system pattern generators, peripheral inputs, intentional influences), physiological constraints (minimization of metabolic energy or muscular force), and environmental perturbations. Describing, predicting and understanding the dynamic behavior of rhythmic movements should benefit greatly from, if not require, the application of chaos and nonlinear dynamics theory. Indeed, during the last 10 years, nonlinear methods have been used to model the dynamics of developmental transitions in newly running infants, walk-to-run gait transitions in adults, movement pattern learning, stride interval fluctuations, and the coordination of oscillating limbs. I will review briefly some of these applications. I will also give some background on the physics of locomotion, and explore (in a discussion format) the usefulness of nonlinear methods in helping us to understand the energetics of locomotion.

2 December. Clint Sprott, UW Physics: ``The Science of Complexity.''

Abstract: Many interesting phenomena arise from the interaction of a large number of individual components. Examples include turbulent fluids, the stock market, the ecosystem, and the brain. Recent advances in computing permit such systems to be studied using simple models with a large number of variables. These models exhibit many of the general properties of natural complex systems such as self-organization, evolution, adaptation, and artificial intelligence. Some of these models will be described, and their dynamical behavior will be illustrated with computer animations.

9 December. Joseph P. Newman, UW Psychology: ``Response Modulation Deficits in Psychopaths.''

Abstract: The antisocial behavior of psychopaths leads many to conclude that they are fundamentally callous and fearless. Our physiological, animal model of psychopathy and the results of numerous studies generated by the model suggest that psychopaths have a response modulation deficit. Response modulation entails a brief and relatively automatic shift of attention from the organization and implemention of goal-directed behavior to its evaluation. Whereas response modulation enables nonpsychopaths to process contextual cues that provide perspective on behavior and facilitate self-regulation, the psychopath's difficulty processing such cues results in a profound, though situation specific, failure to regulate behavior.
Up to the Chaos and Complex Systems Seminar page.
Last change worth mentioning Sun 23 Nov 1997