MINNEAPOLIS/SAINT PAUL (March 19, 2013) – The Proceedings of the National Academy of Sciences (PNAS) Editorial Board has selected six papers published by PNAS to receive the 2012 Cozzarelli Prize, an award that recognizes outstanding contributions to the scientific disciplines represented by the National Academy of Sciences. Apostolos P. Georgopoulos, M.D., Ph.D., University of Minnesota Regents Professor of neuroscience, and four collaborators, Paloma T. Gonzalez-Bellido, Ph.D., Hanchuan Peng, Ph.D., Jinzhu Yang, Ph.D., and Robert M. Olberg, Ph.D., were selected by PNAS in the Biological Sciences category.
Papers selected were chosen from more than 3,700 research articles that appeared in the journal in 2012 and represent the six broadly defined classes under which the National Academy of Sciences (NAS) is organized.
The University of Minnesota-led paper, "Eight pairs of descending visual neurons in the dragonfly give wing motor centers accurate population vector of prey direction," deciphered the neural code for direction of motion in the central nervous system of the dragonfly. Georgopoulos developed the population vector algorithm for interpreting neural activity that helped determine neural processing of directional signals.
"It's an honor to be selected as one of the Cozzarelli Prize recipients," said Georgopoulos. "Our recognition by PNAS is due to truly superb neurophysiological work and an extremely effective way for interpreting directional brain activity."
The population vector code has been used widely in neuroprosthetic applications in monkeys and humans.
The annual award acknowledges papers that reflect scientific excellence and originality. The award was established in 2005 and named in 2007 to honor late PNAS editor-in-chief Nicholas R. Cozzarelli.
The 2012 awards will be presented at the PNAS Editorial Board meeting, and awardees will be recognized at an awards ceremony during the NAS Annual Meeting on April 28, 2013, in Washington, D.C.
The paper can be found here http://www.pnas.org/content/110/2/696.full.