Wednesday, April 23, 2014
Beckman Institute Auditorium

The Art of Scientific Presentations

Wednesday, April 2, 2014
Beckman Institute Auditorium

Juggling Teaching at a Community College and Research at Caltech

Friday, March 14, 2014
Avery Dining Hall

Workshop: Comedy as a Teaching Tool

Caltech's "Secrets" to Success

Everyone who really knows Caltech understands that it is unique among universities around the world. But just what makes Caltech so special? We've asked that question before, and the numbers don't tell the full story. So, is it our focus? Our culture? Our people?

The UK's Times Higher Education magazine recently tackled the topic, asking more specifically, "How does a tiny institution create such an outsized impact?" Caltech faculty share their perspectives in the cover story of the magazine's latest issue.

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Pinpointing the Brain’s Arbitrator

Caltech researchers ID a brain mechanism that weighs decisions

We tend to be creatures of habit. In fact, the human brain has a learning system that is devoted to guiding us through routine, or habitual, behaviors. At the same time, the brain has a separate goal-directed system for the actions we undertake only after careful consideration of the consequences. We switch between the two systems as needed. But how does the brain know which system to give control to at any given moment? Enter The Arbitrator.

Researchers at the California Institute of Technology (Caltech) have, for the first time, pinpointed areas of the brain—the inferior lateral prefrontal cortex and frontopolar cortex—that seem to serve as this "arbitrator" between the two decision-making systems, weighing the reliability of the predictions each makes and then allocating control accordingly. The results appear in the current issue of the journal Neuron.

According to John O'Doherty, the study's principal investigator and director of the Caltech Brain Imaging Center, understanding where the arbitrator is located and how it works could eventually lead to better treatments for brain disorders, such as drug addiction, and psychiatric disorders, such as obsessive-compulsive disorder. These disorders, which involve repetitive behaviors, may be driven in part by malfunctions in the degree to which behavior is controlled by the habitual system versus the goal-directed system.

"Now that we have worked out where the arbitrator is located, if we can find a way of altering activity in this area, we might be able to push an individual back toward goal-directed control and away from habitual control," says O'Doherty, who is also a professor of psychology at Caltech. "We're a long way from developing an actual treatment based on this for disorders that involve over-egging of the habit system, but this finding has opened up a highly promising avenue for further research."

In the study, participants played a decision-making game on a computer while connected to a functional magnetic resonance imaging (fMRI) scanner that monitored their brain activity. Participants were instructed to try to make optimal choices in order to gather coins of a certain color, which were redeemable for money.

During a pre-training period, the subjects familiarized themselves with the game—moving through a series of on-screen rooms, each of which held different numbers of red, yellow, or blue coins. During the actual game, the participants were told which coins would be redeemable each round and given a choice to navigate right or left at two stages, knowing that they would collect only the coins in their final room. Sometimes all of the coins were redeemable, making the task more habitual than goal-directed. By altering the probability of getting from one room to another, the researchers were able to further test the extent of participants' habitual and goal-directed behavior while monitoring corresponding changes in their brain activity.

With the results from those tests in hand, the researchers were able to compare the fMRI data and choices made by the subjects against several computational models they constructed to account for behavior. The model that most accurately matched the experimental data involved the two brain systems making separate predictions about which action to take in a given situation. Receiving signals from those systems, the arbitrator kept track of the reliability of the predictions by measuring the difference between the predicted and actual outcomes for each system. It then used those reliability estimates to determine how much control each system should exert over the individual's behavior. In this model, the arbitrator ensures that the system making the most reliable predictions at any moment exerts the greatest degree of control over behavior.

"What we're showing is the existence of higher-level control in the human brain," says Sang Wan Lee, lead author of the new study and a postdoctoral scholar in neuroscience at Caltech. "The arbitrator is basically making decisions about decisions."

In line with previous findings from the O'Doherty lab and elsewhere, the researchers saw in the brain scans that an area known as the posterior putamen was active at times when the model predicted that the habitual system should be calculating prediction values. Going a step further, they examined the connectivity between the posterior putamen and the arbitrator. What they found might explain how the arbitrator sets the weight for the two learning systems: the connection between the arbitrator area and the posterior putamen changed according to whether the goal-directed or habitual system was deemed to be more reliable. However, no such connection effects were found between the arbitrator and brain regions involved in goal-directed learning.  This suggests that the arbitrator may work mainly by modulating the activity of the habitual system.

"One intriguing possibility arising from these findings, which we will need to test in future work, is that being in a habitual mode of behavior may be the default state," says O'Doherty. "So when the arbitrator determines you need to be more goal-directed in your behavior, it accomplishes this by inhibiting the activity of the habitual system, almost like pressing the breaks on your car when you are in drive."

The paper in Neuron is titled "Neural computations underlying arbitration between model-based and model-free learning." In addition to O'Doherty and Lee, Shinsuke Shimojo, the Gertrude Baltimore Professor of Experimental Psychology at Caltech, is also a coauthor. The work was completed with funding from the National Institutes of Health, the Gordon and Betty Moore Foundation, the Japan Science and Technology Agency, and the Caltech-Tamagawa Global COE Program. 

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Kimm Fesenmaier
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Moneyball Comes to Caltech

The winter 2014 quarter at the California Institute of Technology (Caltech) is premiering a unique course, The Theory and Practice of Moneyball, taught by Caltech professor of political science and dean of undergraduate students Rod Kiewiet, and Fred Claire, former general manager of the Los Angeles Dodgers and current sports consultant and educator.

Moneyball—the title of a 2003 book by Michael Lewis and a 2011 film starring Brad Pitt—has entered the contemporary lexicon as the informal name for sabermetrics, a term coined by baseball analyst Bill James in 1980, who defines it as "the search for objective knowledge about baseball." (James came up with the term sabermetrics as a reference to the Society for American Baseball Research [SABR].)

Of course, managers, coaches, and players have long attempted to bring objective knowledge to bear on their attempts to find more winning ways to play the game. But it was not until recent decades, with the development of new modes of collecting data about baseball (from the angle of a pitcher's arm to the exact spin on a ball) and ever more sophisticated statistical methods and computer technologies, that sabermetrics really took off and became the burgeoning business it is today. Most major ball clubs have a sabermetrician on staff, and baseball fans are increasingly fluent in the theories that sabermetrics have brought to the forefront. Is a batting average a helpful metric in predicting wins? Sabermetrics says no. Is there a strategic advantage associated with bunting or stealing bases? Common wisdom has said yes for generations, but sabermetrics typically says no, and both practices have become less common in the past decade of professional baseball.

To shed light on this last debate, Kiewiet and Claire invited a special guest to their moneyball class on January 21: Maury Wills, former Dodgers shortstop and the National League's Most Valuable Player in 1962, the year he stole 104 bases, breaking Ty Cobb's 1915 record for bases stolen in a single season. Wills, of course, has every reason to doubt the conventional sabermetric wisdom about the deficiencies of the "small ball" game of bunts and stolen bases. He was an expert at both during his years as a major-league player; at age 81, he continues to coach Dodgers players on the art of setting down the perfect bunt.

As Wills, Claire, and Kiewiet agreed, the statistical techniques employed in sabermetrics can be enlightening, but can also be misleading if they are not sophisticated enough. Bunting and stealing bases may not look like winning strategies in the aggregate, but when deployed properly within the game—by the right players at the right time—they can contribute to a team's success. This is, says Wills, because baseball is a "mental game": "You can be tall, short, skinny, fat, fast, slow, handsome . . . and not-so-handsome. Yet you can be a good baseball player. That's why the game is so great."

Freshman seminars were introduced at Caltech in 2011 to give first-year students more direct contact with faculty in a small class setting (12–15 students total) and the opportunity, says Kiewiet, "to have fun, and not just be grinding away." In addition to The Theory and Practice of Moneyball, this year has also offered freshman seminars on earthquakes, gravitational waves, and courses with evocative names like Albatrosses, Beetles, and Cetaceans—a reflection on scaling in nature—and The Origin of Ideas.

"I feel very strongly about the value of freshman seminars," says Kiewiet, "and as dean, I'm anxious to keep these going, so I thought I should put my money where my mouth is and do one myself." Moneyball was a natural choice for Kiewiet. A baseball fan from childhood, he studied sabermetrics in the late 1980s, when Bill James's work came to greater prominence. Kiewiet mentored Caltech undergraduate Ari Kaplan, BS '92, a baseball player, in a SURF fellowship on pitching statistics that eventually led Kaplan to a career as a sports consultant. Kaplan has now worked for over half the major-league baseball teams in America, in addition to his ongoing career in business software; he co-owns a sabermetrics company, AriBall, with Claire.

As for Kiewiet, he has kept up with baseball statistics, though his scholarly efforts are primarily directed toward research into public-school finance, voting in British elections, and other pursuits typical of a professor of political science. Kiewiet did serve as the sabermetrics specialist for the film Moneyball, though he claims this was "only because they couldn't get Kaplan, because he was busy working for the Cubs."

Kiewiet recently got approval from the faculty board to open freshman seminars to upperclass students. Freshmen have the opportunity to register first, but if there are remaining spaces in these classes after freshmen have signed up, more advanced students can take them too. As a result, Kiewiet and Claire's moneyball seminar has attracted five upperclass students along with four freshmen, almost all of whom are student athletes. "Moneyball is a good laboratory for looking at economic theories," says Kiewiet. "It's got all the issues of strategy and information and of maximizing efficiency with budget constraints. But frankly, I just really like baseball."

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Cynthia Eller
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Monday, May 5, 2014
Moore 070

Teaching Statement Workshop - 2-Part Event

Monday, May 12, 2014
Center for Student Services 360 (Workshop Space)

Teaching Statement Workshop - 2-Part Event

Friday, April 4, 2014
Center for Student Services 360 (Workshop Space)

Spring TA Training

Tuesday, April 1, 2014
Center for Student Services 360 (Workshop Space)

Spring Head TA Lunch

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