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Who's Coming?

Alumni College Sessions


David J. Anderson
Seymour Benzer Professor of Biology; Investigator, Howard Hughes Medical Institute

How Brain Circuits Control Instinctive Behaviors

Animals often have to make rapid decisions between different, competing behaviors, such as fighting, mating, or freezing. These decisions are controlled by sensory cues, the animal's internal state and its previous history. In humans, these innate behaviors are associated with emotion states such as fear, anger and love. We are studying the control of aggression vs. mating, in both mice and fruit flies, as a model for understanding how internal states, such as arousal or other so-called "emotion primitives," influence decisions between innate behaviors. This talk will focus on how aggression circuits are organized in the brain, and their relationship to circuits that control mating behavior. Our studies have revealed that mice and flies contain "modules" (relatively small groups of neurons) that control both aggression and mating, suggesting that this is an evolutionarily ancient circuit "motif." The role of these modules, and their relationship to decision-making and internal brain states, will be discussed. The long-term objective of these studies is to provide insights into the brain mechanisms that link emotion and decision-making, and their evolutionary origins.





  Session I

John Preskill
Richard P. Feynman Professor of Theoretical Physics;
Director of the Institute for Quantum Information and Matter

Quantum Computing and the Entanglement Frontier

The quantum laws governing atoms and other tiny objects seem to defy common sense, and the information encoded in quantum systems has weird properties that baffle our feeble human minds. Being less weird than a quantum computer, and easier to understand, I will explain why I love quantum entanglement—the elusive feature making quantum information fundamentally different from information in the macroscopic world. I will show how quantum computers should be able to solve otherwise intractable problems by exploiting quantum entanglement, as well as its far-reaching applications to cryptology, materials science, and fundamental physical science. 





  Session II

Nai-Chang Yeh
Professor of Physics;
Fletcher Jones Foundation Co-Director of the Kavli Nanoscience Institute

A Perspective of Materials Frontiers

The development of advanced materials has been playing a major role in many aspects of modern science and technology. In particular, the interplay of functional, nano-, and meta-materials can open up new frontiers never envisioned before. I will discuss three classes of representative materials, including (1) superconductors, which are materials exhibiting macroscopic quantum-phase coherence and zero resistance below a critical temperature; (2) topological matter, which involves materials with electronic properties and quantum phases classified by topology rather than symmetry; and (3) graphene, which consists of a single layer of carbon atoms forming a honeycomb lattice structure. I will introduce the underlying concepts that are most relevant to the novel properties of these materials and then discuss how these functional and/or nano-materials can enable boundless frontiers that range from purest fundamental scientific research to cutting-edge technology. Some examples of the applications include cosmology, quantum information technology, metrology, ultrasensitive detectors, nano-electronics/photonics/optoelectronics, nano-biotechnology, medical diagnostics, brain research, fast transportation, superlubricant mechanical bearing, ultrastrong and ultralight membranes, renewable energy, energy storage, low-loss power transmission, and water purification.



  Session III

Thomas Heaton

Professor of Engineering Seismology

Has Performance Based Engineering Broken the Power Law?

What is the survivability of modern California high-rise buildings in the future large earthquakes that will inevitably attack our urban areas? I will describe the characteristics of ground shaking that would cause building collapse and discuss the probability that those ground motions will occur using an alternate set of data that doesn’t rely on the current standard, the Gutenberg-Richter law. The Gutenberg-Richter law is a power law in which the majority of tectonic deformation comes from the largest earthquakes; it has fat tails that are difficult to deal with since most of the action comes from infrequent events. Most probabilistic seismic hazard analyses (PSHA) imply that extreme events are too infrequent to significantly affect the overall hazard. When considering building collapse, I instead am interested in near-source ground motions and will show that high-frequency near-source ground motions are log-normally distributed, as opposed to low-frequency ground motions, which are a difficult-to-characterize power law. The current use of log-normal statistics is significantly underestimating the probability that long-period buildings will fail in future large earthquakes.



  Session IV

Colin Camerer

Robert Kirby Professor of Behavioral Economics

The Neuroscience of Stock Price Bubbles

Price bubbles in asset markets reflect pathological valuation in human group-level behavior. Bubbles can have huge consequences, disrupt the way that good companies get financed, and harm economies for years. Bubbles are defined as large gaps between an asset’s price and its fundamental (or intrinsic) value. However, the fundamental value for many assets is not easily observed. To explore the neuroscience of price bubbles, my research starts by using an experimental method in which we create assets with known fundamental values. Then we explore the brain’s neural circuitry associated with the formation and crash of bubbles in a simple experiment. Neural activity in the nucleus accumbens (NAcc) tracks the price bubbles in all subjects, but the lowest-earning in the group have a higher brain-driven propensity to buy as a function of NAcc activity. In the highest earners, we report a signal in the anterior insular cortex that precedes the impending price peak and correlates with a higher propensity to sell instead. These results indicate the potential for neurobehavioral measures to inform our understanding of bubble formation and behavior in other settings in which group interactions may misassign value to complex future events.