Programmed for Success

Think of the best thing that could ever happen to you and how it would make you feel. On a scale of 1 to 10, the average person probably would expect to feel like a 10—and they would be wrong. “When we predict our reactions to events, we tend to focus so much on that one event that we forget all the other things that would be happening at the same time,” says Kate Gunthert, professor of psychology.

She explains, “If you ask someone how they think they would feel if they won the lottery, and for how long they think they would feel that way, they would most likely predict that they would be extremely happy for a very long time. The truth is, you would be really happy for a little while—and then go back to normal.” Negative predictions relative to an event or a situation follow the same pattern, which researchers refer to as focalism.

How does depression or anxiety affect an individual’s degree of focalism? Sue Wenze (PhD clinical psychology ’09) is exploring this question. With funding from a Mellon grant, a National Honor Society in Psychology graduate research grant, and Gunthert’s faculty research grant, Wenze has collected an intensive body of data from 140 AU undergraduates over the past year. “Almost every study in the field has been about errors the average person has made [selfpredicting their moods],” says Gunthert, who is Wenze’s project advisor. “Sue is looking at whether or not it might be the case that depression and anxiety make these errors worse.”

Wenze hypothesizes that depressed participants tend to overpredict negative feelings and underpredict positive ones, while participants suffering from anxiety overpredict anxious feelings but don’t necessarily underpredict positive emotions. She explains, “If the research does show that a depressed person overpredicts their negative feelings, this could become a red flag if you are working with someone who is depressed.”

Gunthert offers an example: “If they don’t want to go to a party because they are predicting that they are going to have a horrible time anyway, their clinician can point out that their prediction is likely not to match their experience.”

To collect her data, Wenze asked 140 undergraduates to complete a mood measure questionnaire to forecast the feelings they would experience during the following week based on events to come. Each participant carried a Palm Pilot; four times a day, at random, the device prompted the student to answer questions concerning how they were feeling at the time. At the end of the week, participants responded to questions relating to the moods they experienced.

By monitoring the students’ feelings in real time, Wenze says, “We’re getting data from their real lives, with their real class schedules [and] real time with friends factored in. The data represents their actual experiences and their actual moods.”

The average passenger car produces more than 12,000 pounds of polluting emissions yearly, according to the Environmental Protection Agency (EPA). This number could be reduced to zero by discovering an efficient chemical pathway for producing hydrogen—the problem is finding it.

“Hydrogen-fueled vehicles only produce water as a byproduct, but the dilemma is how you go about producing this hydrogen without producing other greenhouse gases,” says Jack Shultz (MS professional science/biotechnology ’06). Shultz has been analyzing enzyme reactions in hopes of discovering one that releases hydrogen molecules, thus providing a cheap, clean method of producing the gas.

To date, scientists have discovered one such reaction, which occurs in the Chlamydomonas reinhardtii alga during its final stage of photosynthesis. But the oxygen produced from splitting water

damages hydrogenase, the enzyme that catalyzes the reaction, making this method of hydrogen production inefficient. There may be other enzyme catalysts, however, and analysis of more than 47,509 publicly accessible protein structures may identify one. By running computerized simulations of these naturally occurring reactions, Shultz hopes to identify the key to producing inexpensive hydrogen fuel.

Constraints in time and computing power would make so many simultaneous simulations on a standard PC nearly impossible, but Shultz uses a secret weapon: Berkeley Open Infrastructure for Network Computing (BOINC). BOINC projects can use the CPU power from a network of computers. “Running 47,509 simulations could be a lengthy process,” says Shultz, “but if you have hundreds of computers distributing the work, then it isn’t so bad.”