Creativity and the Brain - What We Know and What We Don't HomeCurrently selectedThe Debs Center About the Debs CenterHistory of the Debs CenterTitle IX Related Policy and TrainingStaff NewsEvents Global Engagement InitiativeAlumniGalaPast Events Study Abroad at AUBGlobal Engagement Initiative Upcoming EventsPast Events and GEI Media Library Degree and Employment VerificationContact UsRecent Page ContentDuring this briefing, AUB Professor of Psychology Arne Dietrich and Platypus Neuro CEO David Bach debunk myths and misconceptions surrounding the creative process and attempt to explain its underlying mechanics. Dietrich defines creativity “in terms of the product that it produces." That product, he says, must be new, functional, and surprising. He mentions the alternative uses test as a means of measuring creativity which asks test takers to come up with as many possible alternative uses for a given object. This test measures divergent thinking; however, convergent think—intense focus, rather than a wandering mind—produces creativity as well. The difficulty in nailing down a skill or thinking pattern that reliably and exclusively predicts creativity makes testing creative capacity difficult. Scientists and laypeople have speculated on the origins of creativity for millennia, producing myriad myths and fallacies according to Deitrich. "Creativity is in the right brain. That is an idea that ought to be treated like nuclear waste and buried for a million years. It's phrenology straight up... Complex psychological functions are not done in one particular brain area. There's no brain area where you have your belief in Santa Claus." Dietrich debunks the idea that creativity sits in the prefrontal cortex, as one can be creative when that part of the brain is inactive. He suggests neuroscientists stop trying to locate creativity in a particular area of the brain, but instead embrace the idea that it is present everywhere. He says we must break creativity into types to better study it. Ultimately, he characterizes creativity as a sort of evolutionary algorithm that involves the testing of solutions to challenges. Read a full text summary of the discussion here.