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JPEG for the mind: How the brain compresses visual information
Date:2/10/2011

ere quite different when the model was trained to limit the number of virtual V4 cells responding to each image. As this limit on responsive cells was tightened, the selectivity of the cells shifted from shallow to acute curvature. The tightest limit produced an eight-fold decrease in the number of cells responding to each image, comparable to the file size reduction achieved by compressing photographs into the .jpeg format. At this level, the computer model produced the same strong bias toward high curvature observed in the real V4 cells.

Why would focusing on acute curvature regions produce such savings? Because, as the group's analyses showed, high-curvature regions are relatively rare in natural objects, compared to flat and shallow curvature. Responding to rare features rather than common features is automatically economical.

Despite the fact that they are relatively rare, high-curvature regions are very useful for distinguishing and recognizing objects, said Connor, a professor in the Solomon H. Snyder Department of Neuroscience in the School of Medicine, and director of the Zanvyl Krieger Mind/Brain Institute.

"Psychological experiments have shown that subjects can still recognize line drawings of objects when flat edges are erased. But erasing angles and other regions of high curvature makes recognition difficult," he explained

Brain mechanisms such as the V4 coding scheme described by Connor and colleagues help explain why we are all visual geniuses.

"Computers can beat us at math and chess," said Connor, "but they can't match our ability to distinguish, recognize, understand, remember, and manipulate the objects that make up our world." This core human ability depends in part on condensing visual information to a tractable level. For now, at least, the .brain format seems to be the best compression algorithm around.


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Contact: Lisa DeNike
Lde@jhu.edu
443-287-9960
Johns Hopkins University
Source:Eurekalert  

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