In 1971, when neuroscientist Hans-Lukas Teuber asked his class at Massachusetts Institute of Technology “How do we see a line as a line?”, Richard Granger's mind blew a circuit. The first-year computer scientist became preoccupied with understanding how information was received and processed in the brain. He decided to refocus his career by integrating his long-standing love of computers with his new-found passion for unlocking the mysteries of the mind. See CV

“A lot of the big questions are ones for which fields don't yet exist,” says Granger. During his PhD in computer science at Yale, he designed computational tools to analyse psychological data related to fundamental aspects of memory — how to store, access and retrieve it — in order to gain insights into the neurobiological mechanisms at work. In 1980, as a young faculty member at the University of California, Irvine, he learned about brain circuitry by sitting through a graduate-level series of neuroscience courses. The primitive state of neuroscience as a field, the limited mathematical models and the sorry state of computers made him worry that delving into computational neuroscience was premature. But that didn't dissuade him.

To circumvent these limitations, Granger built simplified, anatomically specific computer circuits to imitate real neurons from the bottom up. In 1990, while modelling the brain's olfactory cortex (which was well understood anatomically), his circuit did something novel and surprising — it gave a series of meaningful responses to a single input. Since then, he has tried to tackle major questions such as how neurons interact and pass on messages to perform organism-level behaviours. In the past few years, Granger has received US patents in areas ranging from neurological diagnostics to financial analysis.

Once he heard of Dartmouth College's new Neukom Institute for Computational Science, doing computation work in everything from scientific analyses to the creative arts, Granger knew the directorship was ideal for him. Carol Folt, Dartmouth's dean of the faculty, agrees. She says Granger is one of the few people with the expertise and enthusiasm necessary not only to bring people from disparate areas together, but to help shape this new field.

Granger hopes to provide the spark to jumpstart the institute and ignite multiple collaborations. From basic work on perception to commercial applications of enhanced pattern recognition, he sees endless potential. The key, he says, is to look beyond what is known, to what is possible.