Much of the discussion of complexity focuses on the science of complexity. In this talk I will focus on the implications of complexity for public policy–how the advances in complexity science changes the way economists frame policy. I begin by reviewing how the economics profession developed its current neoclassical “market failure” policy frame. I then discuss how complexity science provides an alternative policy frame that encompases a wide range of political and ideological views.. I argue that this complexity policy frame reflects much more of a Millian classical economic policy approach in which economic science and policy are much more strongly separated than does the current neoclassical policy frame. I conclude with some specific examples of how economist’s policy analysis will change if the complexity vision of the economy is adopted.]]>
As our understanding of biological systems as increased, so has the complexity of our questions and the need for more advanced optical tools to answer them. For example, there is a hundred-fold gap between the resolution of conventional optical microscopy and the scale at which molecules self-assemble to form sub-cellular structures. Furthermore, as we attempt to peer more closely at the dynamic complexity of living systems, the actinic glare of our microscopes can adversely influence the specimens we hope to study. Finally, the heterogeneity of living tissue can seriously impede our ability to image at high resolution, due to the resulting warping and scattering of light rays. I will describe three areas focused on addressing these challenges: super-resolution microscopy for imaging specific proteins within cells down to near-molecular resolution; plane illumination microscopy using non-diffracting beams for noninvasive imaging of three-dimensional dynamics within live cells and embryos; and adaptive optics to recover optimal images from within optically heterogeneous specimens.]]>
Fear and anxiety disorder have a lifetime incidence of over 25% of the population. Although the neural circuitry involved in fear conditioning in mature organisms is well understood, the development of these circuits is less well studied. However, the extant literature does suggest that the third and forth weeks of life in rodents appear to be a time of significant change in both the cognitive and behavioral mechanisms of fear as well as the underlying neurobiology. The current experiments further examine the behavioral and neurological changes that occur during this period, with a focus on medial temporal lobe cortex, the hippocampus and the amygdala. Here, I will discuss two sets of experiments. The first examines ontogeny of contextual fear conditioning by separating the contextual and aversive learning. These experiments will conclude that some aspects of hippocampus-dependent learning may be occurring earlier than previously believed. The second set of experiments examines immediate early gene (IEG) expression in the amygdala, hippocampus, perirhinal cortex, and hypothalamus during auditory and contextual fear conditioning and expression. These studies will suggest that the amygdala and perirhinal cortex are likely sites of continuing development during the periweaning period.]]>
The goal of our research is to understand the mechanism of synaptic integration and excitability of neurons located in the basal ganglia. Initial efforts in the lab have focused primarily on synaptic and dendritic properties of dopamine-releasing neurons located in the substantia nigra, which play a central role in reward and motor behaviors. In particular, our work focuses on how synaptic inputs interact with active ionic conductances present in the dendrites of dopamine neurons to produce reward-relevant firing patterns such as “burst firing” – high-frequency bursts of action potentials that result in a transient spike in the concentration of dopamine released in the striatum, a brain region critical for action selection and goal-directed behaviors. The presentation will cover our recent work that examines how background tonic activity shapes dendritic excitability and burst firing in dopamine neurons.]]>
We recently developed a free-propagator reweighting (FPR) algorithm that solves reaction-diffusion (RD) dynamics of systems at single particle resolution both accurately and efficiently. The full spatio-temporal resolution of this RD method allows us to model complex biological systems where details like spatial gradients or particle assembly render simple rate-based kinetics insufficient. The treatment of proteins at single-particle resolution also allows us to begin building in further molecular details into the physics of the binding interactions, such as multiple domains in proteins, rotational and orientational effects, and interaction potentials. We have recently used our method to quantify the effect of membrane recruitment in altering the equilibrium and time-scales of protein binding interactions relative to their behavior in solution, which has implications for understanding the mechanisms of clathrin-coat formation in the early stages of endocytosis. Finally, we have used our RD simulations and new theoretical results to characterize the limitations of modeling reactions dynamics in 2D using simple rate-based kinetics. The use of rate equations assumes a well-mixed system over the lengthscale of the (sub)volume being modeled, and additionally assumes a single rate-constant parameterizes association between binding partners. In 2D, however, the second assumption of a single characteristic rate constant is not generally true. Understanding when this approximation breaks down is critical both for accurate simulations and for robust parameterization of experimental binding data. We determine in what regimes a single rate is appropriate, and when additional parameterization is necessary. Because the use of rate equations provide an efficient and widely used tool for simulating reaction dynamics, we introduce a concentration dependent rate constant in 2D as an approximate representation of the more microscopic dynamics dependent on the multi-parameter model.]]>
An abstract for this Monday Seminar is forthcoming, but the following is a description of Dr. Root’s recent book, which he will be discussing:
DYNAMICS AMONG NATIONS employs insights from the study of complex systems to examine the interdependent, networked environment of today’s global power transitions – as well as the rise and fall of empires in Europe and Asia.
For too long, policymakers and economists have tackled problems of institution building, governance, and economic policy reform by asking, “What is the best solution” or “What should we address first”? When the problems they face are complex – not just complicated – these are the wrong questions.
Complex problems arise from complex systems made up of networks of interacting agents – families, ruling coalitions, governmental bureaucracies, markets, unions – that influence each other within the larger system. The behavior of one agent affects the behavior of another, and the resulting dynamics produce novel and powerful self-organizing behaviors in other agents sharing the system, and create a spiral of feedback loops and linked responses.
When does a component recognize that it is a contributing agent? Do the parts know they are a wave? The study of complexity helps us recognize the significance of individual change in terms of the larger pattern or system of which it is a part.
Science Policy is more important than ever. With federal funding for basic research undergoing a secular stagnation, decisions about how to spend those scarce dollars for the greatest return on investment for the American taxpayer take on ever more importance. In my seminar, I will discuss some of the complexities regarding current science policy both with regards to the NSF and the broader federal R&D ‘waterfront’. The key take home point will be the importance of transparency and accountability for all the stakeholders — from Congress to the PI.]]>
Almost invariably, when a device is disassembled, it is taken apart in the reverse order from which it was assembled. There is growing evidence that the same logic applies to the human brain. Those faculties that breakdown first during aging are those that mature last during development. Dr. Dumas’ team has identified some of the final steps of hippocampal maturation in rodents on molecular, physiological and behavioral levels and found some overlap with reverse changes that happen in early aging. Dr. Dumas’ research is intended to better understand the mechanisms of memory loss related to normal aging and to be able to rectify them in order to improve quality of life for elderly individuals and reduce medical costs associated with senescence.]]>