Riesenhuber, who came to Georgetown University Medical Center in 2003 after postgraduate study at the Massachusetts Institute of Technology, is the principal investigator for the Laboratory for Computational Cognitive Neuroscience.
As a gateway into understanding information processing in the brain, Riesenhuber’s research focuses on vision, and specifically on object recognition. Using the NSF grant, he plans to use a variety of methods, including behavioural and imaging studies, to dissect how people recognise things, such as faces, in different scenes.
“How is it that the visual system can recognise certain objects, such as a friend in the crowd, or words on a page, despite the changing environment in which these objects are seen?” he asks. “Despite the apparent ease in which we see, visual recognition is a very difficult computational problem.”
Riesenhuber’s task, therefore, is to use mathematics and computer modelling to make sense of a massive amount of information - everything from what people say they see to the firing of groups of neurons seen in brain scans - that goes into visual perception.
Comprehending how a brain “sees” has a variety of applications, Riesenhuber said. A computational model of vision can be used in artificial intelligence to help machines see, and for applications involving human object recognition tasks, ranging from baggage screening to satellite image analysis.
"We will use a combination of computational modelling and experiments to go beyond current qualitative theories of how neural information processing differs in typically developing and autistic brains," Riesenhuber said. "This technique might also help us shed light on the neural bases of other disorders that involve a loss or impairment of object recognition abilities, such as dyslexia."
MEDICA.de; Source: Georgetown University Medical Center