Now, seven months later, the students talk back and forth across the tables. Papers rustle as they share notes and calculations. “If it gets too quiet,” Morkin says, “they know I'm going to bother them. It's tough for me not to talk too much, but as long as they have each other, they don't need me.”

Several students confirm what she says. Premed freshman Weinberger says, “It's nice to have your peers explain concepts to you. Their thinking is more similar to yours than the professor's is.”

Adds classmate Ryan Makinson, who wants to attend graduate school in neuroscience: “I understand a theory better by explaining it to a classmate. It's pretty cool.”

According to Lynn, the success of Morkin's experimental course is spurring the department to “completely change the way chemistry is taught” at Emory. At the department's urging, the university has begun restructuring its principal lecture hall into an “active-learning environment,” while redesigning courses to fit it.

Marsteller, who helped the chemistry department launch Morkin's course with HHMI support for its development, thinks active learning is a useful tool for boosting math competence among science students. She hopes other Emory courses will adopt a similar active-learning approach. “We've been training a lot of scientists who don't understand the quantitative methods they are using,” she says. “Students need to struggle with them. If they're just hearing the solution, all they do is write it down and forget it.”

For students in Morkin's class and others like it around the country, the numbers have started to add up. They will know how to get the answers they need long after the course grades are in.

		Long before Einstein offered up his famous equation about the relationship between matter and energy, physicists were using mathematics-based theories to predict experimental results. Nowadays, given the increasingly apparent complexity and sophistication of living systems, biology stands to benefit from similar approaches. That's why Dmitri Chklovskii figured that a doctorate in theoretical physics from MIT might be helpful in studying why the brain is structured the way it is. “What determines the treelike structure of dendrites?” asks Chklovskii, now a group leader at HHMI's Janelia Farm Research Campus. “Why is there a centrally organized brain? Those were ways that evolution found for optimizing the cost of carrying out vital life functions”—that is, for making the best use of an organism's anatomy and energy to build and maintain a central nervous system. Using this evolutionary “wiring cost” idea, his group has been applying theory confirmed through real data to understand laws that govern the wiring of central nervous systems, in laboratory model organisms and in human brain structures. In theorizing about the optimal way to wire a relatively simple central nervous system—that of the roundworm Caenorhabditis elegans—Chklovskii's group started with existing descriptions of the worm's neuronal wiring diagram (see www.hhmi.org/bulletin/may2006/features/archives.html). He then adapted placement algorithms developed by computer chip designers, who face a similar wiring cost challenge, to predict where neurons should ideally be located in the body. The prediction of neuronal placement that Chklovskii's group came up with proved almost a precise match for the roundworm's actual neural circuitry. He could then study the relatively few neurons that did not fit the predictions, and those exceptions provided new experimental directions for understanding what factors other than wiring cost are important for neuronal placement. Using his emerging theories, Chklovskii can also hypothesize about the far greater complexity of higher organisms, including that of the human brain. “It's an exciting time in neurobiology,” he says, “because you get to be a pioneer in doing theoretical work.” —M.W.

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