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Uncovering the Secrets of the Brain

David Freedman receives 2016 Troland Research Award from the National Academy of Sciences

David Freedman, PhD, a neuroscientist who studies the neural underpinnings of learning, memory and decision-making, has been awarded the 2016 Troland Research Award from the National Academy of Sciences.

The honor is given annually to two young investigators in recognition of unusual achievement in the research of human behavior and the processes that underlie it. The award is accompanied by a $75,000 prize.

“We have a long way to go to fully understand the brain mechanisms of higher cognitive functions,” Freedman said. “But it means a great deal to receive this acknowledgement from the National Academy for the progress we have made in understanding how the brain learns and recognizes visual categories."

Freedman, associate professor of neurobiology and Chair of the Graduate Program in Computational Neuroscience, received the award for his innovative work investigating how the brain learns and recognizes visual categories. To effectively interact with their daily environment, human and primate brains are able to rapidly place objects they see into categories. By learning and storing information about visual categories, the brain can generate meaning—recognizing whether something is a car or a cow, a rock or a soccer ball, fruit or a tree, for example—and initiate an appropriate behavioral response.

Freedman’s creative experimental and computational models have allowed him to not only record from neurons in the brains of subjects as they perform visual categorization tasks, but to also study neurons before, during and after the process of learning.

His efforts have yielded numerous discoveries about how different areas of the brain work together to recognize, store and recall visual categories. He has shown that, remarkably, individual neurons in the parietal and frontal cortices are able to encode information about categories—the activity of single neurons can be used to predict a subject’s categorical decisions. In addition, he has found that these categorical judgements are controlled by populations of neurons that respond differently to visual images that belong in different categories, even if those images have a similar appearance.

Freedman’s research sheds light on how the brain carries out some of its largely mysterious higher functions, and provides a greater understanding of the neural mechanisms involved in memory, learning and visual recognition. His work may also someday help inform the study of diseases in which these functions are impaired, such as Alzheimer’s, stroke and schizophrenia.

"The progress we've made toward understanding the categorization process is due in large part to the hard work of the members of my research laboratory and also my graduate and postdoctoral advisors (Earl Miller and John Assad), since I got my start studying visual categorization in their labs," he said.

Freedman received his PhD in systems neuroscience from the Massachusetts Institute of Technology in 2002 and conducted his postdoctoral research at both MIT and Harvard Medical School. He joined the faculty of the University of Chicago in 2008, and is an active leader in UChicago’s neuroscience community. In addition to serving as Chair of the Graduate Program in Computational Neuroscience, he a member of the Steering Committee for the Grossman Institute for Neuroscience, Quantitative Biology and Human Behavior, and a member of the Graduate Program in Neurobiology.

His numerous honors include a National Science Foundation CAREER Award, Sloan Research Fellowship, a McKnight Scholar Award and a Distinguished Junior Investigator Award in Biomedical Sciences from the University of Chicago. When not in the lab, Freedman can be found playing lead guitar with his soul-funk band in various venues across Chicago.

Freedman, along with fellow award recipients, will be honored in a ceremony on Sunday, May 1, during the National Academy of Sciences' 153rd annual meeting. For more information, visit www.nasonline.org.