Madison Chaos and Complex Systems Seminar

Spring 2013 Seminars

All seminars are Tuesday at 12:05 pm in 4274 Chamberlin Hall except as noted. Refreshments will be served.

Short List
Join us for lunch during the summer on the Memorial Union Terrace at noon each Tuesday, starting May 14th!

Abstracts

January 22, 2013

The Minus-1st Law: The conservation of information and how it leads to chaos

George Hrabovsky, Madison Area Science and Technology

The conservation of information is central to all of physics. It also seems so obvious to us physicists that we don't talk about it much in courses. It is a simple idea, the quantity of information in a closed system never changes. This simple idea requires us to think deeply about the nature of dynamical systems. The ramifications are dramatic; it leads to the second law of thermodynamics and to chaos.


January 29, 2013

What do smiles mean and how do we know?

Paula M. Niedenthal, UW Department of Psychology

Theories of embodied emotion suggest new ways to model the recognition of facial expression. Behavioral and neuroimaging studies indicate that the recognition of facial expressions of emotion, and in particular the elusive smile, involves the (re)production of the expression as well as of the corresponding emotion, or parts of it, in the self. In the present talk, I introduce a new model, The Simulation of Smiles Model (SIMS, Niedenthal et al., BBS, 2010). The SIMS relies on a social-functional typology of smiles. Accordingly, I first present research that seeks to validate the typology. The SIMS also outlines specific roles for facial mimicry and eye contact in representing smile meaning. Recent empirical evidence in favor of these roles is presented. Finally, the SIMS leaves room for the use of perceptual and conceptual processes in interpreting facial expression. I present research supportive of the hypothesis that the interpretation of smile meaning relies on prior beliefs and stereotypes when facial mimicry does not occur. Results of a recent study on smiling behavior from 9 different countries provides the basis for predictions about moderation by culture of the basic processes outlined in SIMS.


February 5, 2013

Are you thinking what I'm thinking?

Patricia B McConnell, UW Department of Zoology

It's hard enough to know what's going on inside the head of your best friend, much less a member of another species. But recent research by psychologists and neurobiologists have a lot to tell us about the mental lives of non-human animals. If you've ever wondered what's going on inside heads of the animals you live with, join Patricia McConnell in an inquiry into the emotional and cognition lives of mammals. The talk will include a look at how the emotional lives of mammals & birds might compare with ours, their comparative problem solving ability and the controversial concept of "Theory of Mind."


February 12, 2013

Was 2012 a failure for the polls? Was Nate Silver exceptionally accurate?

Charles Franklin, UW Department of Political Science

 In 2012 polls came in for exceptional scrutiny and criticism. Claims that polls where hopelessly skewed became a common meme of the fall campaign. And indeed, polling faces significant practical challenges. But did the polls, in the end, perform poorly? Interestingly, campaign leaders from both the Obama and the Romney campaign have been quoted saying the polls failed. And yet the Obama campaign made unprecedented use of polling in their data analytics. Meanwhile, Nate Silver came to personify the quantitative analysis of election campaigns. His successful predictions for 50 of 50 states is vindication of his forecasts. But did Nate do better than other forecasts?


February 19, 2013

Thom's catastrophe theory and Zeeman's model of the stock market

Joel Robbin, UW Department of Mathematics

Catastrophe theory is a method for describing the evolution of forms in nature. It was discovered by Ren�e Thom in the 1960�s. Thom expounded the philosophy behind the theory in his 1972 book Structural stability and morphogenesis. Catastrophe theory is particularly applicable where gradually changing forces produce sudden effects. The applications of catastrophe theory in classical physics (or more generally in any subject governed by a �minimization principle�) are noncontroversial and help us understand what diverse models have in common. The applications of the theory in the social and biological sciences have met with some resistance. (I don�t know if any workers in these areas have been influenced by Thom�s ideas.) In this talk I will discuss three examples: Zeeman�s toy (the �catastrophe machine�), light caustics, and Zeeman�s explanation of stock market booms and busts.

The constantly evolving slides for this talk are available on my website.


February 26, 2013

The brave cyberworld of science communication

Dominique Brossard, UW Department of Life Sciences and Communication

As more and more individuals turn to online environments to follow scientific issues and find information about science, recent research is science communication has focused on examining how these online environments may shape public attitudes toward science and public understanding of science. This introduction will discuss patterns of science communication online and present recent research findings in that area. Notably, I will introduce results of an experiment with a national sample of the American population testing the effects of comments on science blogs on readers� attitudes toward the scientific issues covered in such blogs. I will also explain the effects of current practices related to online searches on public understanding of science. In light of these results, challenges and opportunities for science as an institution as well as for science and society will be discussed.


March 5, 2013

How are complex adaptations built? Using cultural and genetic convergence to understand evolving systems

John Hawks, UW Department of Anthropology

Adaptation by natural selection is a genetically heterogeneous process. Some adaptive phenotypes are the result of simple genetic changes under positive natural selection. But some adaptive phenotypes are more complex, requiring changes to a network of interacting genes, possibly in addition to gene-environment interactions. Is there any general process by which such complex adaptations can be understood, or are they a simple stochastic accumulation of simple changes? The record of recent human evolution provides a wealth of cases of genetic and cultural changes that have unfolded convergently in different populations. Genetic adaptation to new pathogens, new diets and new physical environments allows us to probe the networks of genetic interactions and the timing of changes on multiple human genes. Cultural adaptation to new diets and modes of social organization also allow us to examine how evolutionary dynamics may constrain the path taken by complex adaptations. I lay out a research agenda that distinguishes functional networks from evolutionary networks, giving us a way to discuss the origins of complexity through evolutionary time.


March 12, 2013

Climate change, disturbance, and forest resilience

Brian Harvey, UW Department of Zoology

The direct and indirect consequences of climate change on forests of North America are only beginning to unfold. Tree health will be directly affected by changing temperature and precipitation patterns. However, just as important are the effects of a changing climate on many of the natural disturbance processes such as wildfire and insect outbreaks that have shaped forest ecosystems for millennia. As trees are relatively long-lived organisms, climate-driven changes to forest ecosystems may be subtle until a disturbance catalyzes change and sends the system along a new trajectory. This talk will include a look into what we can expect in western forests under new climatic and disturbance regimes.


March 19, 2013

The textual structure of REM dreaming

Art Schmaltz, Prairie State College 

The human brain during REM dreaming is a singular neurological event that may well be the most complex event known to science. As a biologically evolved system, dreaming long predates the evolution of human language.

In this presentation, I will parse out one of the ten lines of evidence that argues that human language evolved "down" from the complexity of dreaming, and not "up" from a simpler biological system.


April 2, 2013

The effects of human capital depreciation on occupational gender segregation

Hsueh-Hsiang (Cher) Li, UW Department of Economics

This paper analyzes how human capital depreciation affects occupational gender segregation. Prior studies are generally biased because, given an occupational depreciation rate, female workers endogenously choose the duration of leave. I address this problem by proposing an alternative depreciation measure utilizing involuntary job displacement shocks. Using this depreciation proxy along with additional pecuniary and non-pecuniary occupational attributes, I estimate a conditional logit model of occupational choices separately for male and female college graduates. My results show that women have a stronger distaste than men for occupations with high human capital depreciation.


April 9, 2013

Why do people believe crazy things?

Tim Rogers, UW Department of Psychology

Theories of human knowledge acquisition (ie learning) vary in many of their particulars but typically embrace the common assumption that learning is rational: through learning, people acquire reasonably accurate statistical models of the environment that allow them, given some new information, to make approximately optimal probabilistic inferences about unobserved states of the world. My own work on knowledge acquisition resides firmly in this tradition, but I have always found it difficult to reconcile this view with the everyday observation that many people appear to pretty firmly believe some pretty crazy things. We can see that this is true even without having to agree what the crazy beliefs are. For instance, the President either was or was not born in Hawaii. These are the only two logical possibilities, and there is a fact of the matter. Of the two groups prepared to vociferously argue each side of the proposition, one must be wrong. The incorrect belief persists in this group despite the fact that we all live to some extent in the same world and are presumably applying largely similar reasoning mechanisms to bear on largely the same evidence. The same point can be made with reference to controversies about global warming, evolution, whether vaccines cause autism, the efficacy of trickle-down economics or gun control policy, the relative payscales of public and private sector workers, and any number of other important issues facing public life. If we are all such optimal learners, why do people arrive at such starkly opposing sets of beliefs?

There is a long tradition of research addressing aspects of this problem. One idea is that human reasoning is "motivated"--there are emotional costs associated with different beliefs, and in deciding which beliefs to endorse, people jointly minimize an error cost (ie, fit of the beliefs to evidence) and the emotional cost associated with the belief. But this approach fails to address the central question of where the emotional cost comes from, or why people should be "motivated" to entertain incorrect beliefs in the first place. A second hypothesis is that the cognitive mechanisms that support human learning and inference were only optimal in an evolutionary context, and are not suited to the modern environment in which we now find ourselves. But such accounts seem similarly underconstrained without some specific accounting of what the learning mechanisms are and how and why specifically they are unsuited to our current environment.

I'd like to discuss a third possibility that arises from a consideration of the dynamics of learning in social groups. Models of human learning typically view the learner as an independent entity living in an environment that provides independent samples from a static distribution, occasionally or even frequently paired with category labels provided by an "oracle" that is always correct. In the real world, the labels we receive are not provided by an all-knowing oracle, but by other individuals who may themselves have mistaken or uncertain beliefs, or may be trying to deceive us. When learners are not viewed as independent and passive statistical engines, but as agents who communicate their own current beliefs, the problem of what constitutes the "correct" rational behavior changes. I will illustrate two simple examples of cases where individual learning models are "coupled" by having each learner occasionally provide labels to, and occasionally receive labels from, other learners in a social group, in addition to occasionally directly observing the correct label. The beliefs formed across the group thus constitute a dynamical system, which can exhibit different steady-states depending upon how each learner decides to weight information coming from other sources. In some circumstances the group all converges to the truth; in other cases, it fractionates into communities that endorse very different beliefs. To the best of my understanding, I think this formulation differs from cooperative, competitive, and communication games, but I expect it bears resemblance, and may even be identical to, other kinds of dynamical systems, and I am interested in getting feedback about analogous problems in other domains. I will also describe new empirical evidence concerning how human beings weight evidence coming from multiple different conflicting sources, depending upon their own current beliefs. This evidence suggests that people may indeed fall prey to the problematic dynamics exhibited by the simplified learning models.


April 16, 2013

The Ascaris nervous system - a simple nervous system.  Hah!

Tony Stretton, UW Department of Zoology

Numerically, nematodes have very simple nervous systems.  The female parasitic nematode Ascaris suum has only 298 neurons, and the hermaphroditic free-living Caenorhabditis elegans has 302.  A. suum is large (ca 35 cm), and has large neurons suitable for electrophysiological recording.   We assembled a functional circuit from the morphological synapses, scored by electron microscopy, and the physiological properties of the neurons and their synapses.  The predicted activity of this circuit matched that actually recorded from neurons in dissected preparations that were opened to allow microelectrode penetration.  However, it differed dramatically from the activity recorded from these same neurons in semi-intact behaving preparations.  Something was missing from the circuit description.  We have now shown that there are numerous neuropeptides (at least 250) present in A. suum, and the ones we have sequenced have potent activity on individual neurons.   We think that they were washed out of the dissected preparations, thus losing their modulatory activity on individual neurons.  For peptide identification, initially peptides were purified by HPLC and sequenced by Edman degradation.  Now we are using mass spectrometry, which has speeded up the discovery process more than one hundred-fold.   In particular, we are now dissecting single identified neurons and subjecting them to MALDI-TOF MS and tandem MS for sequence determination.  All neurons examined so far contain peptides.  Most contain previously unknown peptides, and the unknown peptides often outnumber the known peptides.   This is a powerful method of peptide discovery.   It has the distinct advantage that it simultaneously solves the identity and the cellular expression of the peptide.  It also has the advantage that it identifies the peptide actually expressed by a particular neuron, rather than relying on predictions from cDNA or genomic DNA sequences, and on reporter constructs for expression patterns.  Neuropeptides are processed from precursor proteins, and the rules of the proteolytic cleavage are not yet robust enough for accurate prediction of processing.


April 23, 2013

Reading Mayan Glyphs : a story of politics ,adventure, cultural misunderstanding and scholarship

Lewis Leavitt, UW Department of Pediatrics

In 1843 an American diplomat John Lloyd Stephens published an account of his travels in Central America which described extraordinary cities and monuments which were the remnants of an ancient Mayan civilization. On these monuments were a form of writing which was beautiful to behold but undecipherable. The story of the decipherment of this writing by non-Mayans has a history which dates from the Spanish conquest of Mesoamerica. A Spanish bishop Diego de Landa Calderon had made great strides in attempting decipherment in 1566 but due to a tragic cultural misunderstanding failed to see the key which had been revealed. In the 20th century Eric Thompson made great strides in deciphering Mayan calendric dating but when Yuri Knosorov made the crucial determination of the phonetic basis for Mayan writing in 1952 Soviet-American mistrust, isolation of Soviet scholars, and �received wisdom� of American experts led to his insights being ignored for decades. It was not until the 1970s and 80s that the phonetic decipherment of Mayan writing led to a new understanding of Mayan civilization and the texts left by that civilization.


April 30, 2013

Aldo Leopold, phenology and climate change

Stan Temple, Nelson Institute
 
Aldo Leopold, best known as the author of A Sand County Almanac, was a keen observer of the natural world. Throughout his life he kept daily journals recording observations of seasonal events, especially those occurring at his beloved "shack" on the Leopold farm which was the setting for many essays in A Sand County Almanac. Leopold's meticulous phenological observations have provided us with an unparalleled record of when plants bloomed, birds migrated and other natural events. Analyzing his historical observations of hundreds of natural events as well as recent records helps us understand how climate change is affecting the ecological community.


May 7, 2013

Lessons learned from 19 years of chaos and complexity

Clint Sprott, UW Department of Physics

As we conclude the nineteenth year of the Chaos and Complex Systems Seminar, I would like to discuss some of the lessons I have learned from listening to over 500 talks, from my own research, and from the many books and articles I have read on the subject. This will be a rather personal and subjective talk and thus probably controversial. In particular, I will argue that the feedback, nonlinearities, and self-organization that characterize all real dynamical systems are more likely to ameliorate the dire consequences that others have predicted than to exacerbate them as so many fear. This is not a prediction that our problems will vanish or an argument for ignoring them. On the contrary, our choices and actions are the means by which society will reorganize to become even better in the decades to follow, albeit surely not a Utopia.

This talk is available as a PowerPoint presentation and a condensed written version.
See photos taken at this seminar.