NEUROSCIENCE
The Matrix' is a step closer to reality: neuroscientists break code on sight
http://www.physorg.com/news7879.html
http://www.membrana.ru/articles/global/2005/11/07/202700.html
neuroscientists in the McGovern Institute at MIT have been able to decipher a part of the code involved in recognizing visual objects. Practically speaking, computer algorithms used in artificial vision systems might benefit from mimicking these newly uncovered codes.
the researchers trained monkeys to recognize different objects grouped into categories, such as faces, toys and vehicles. The images appeared in different sizes and positions in the visual field. Recording the activity of hundreds of IT neurons produced a large database of IT neural patterns generated in response to each object under many different conditions.
the researchers used a computer algorithm, called a classifier, to decipher the code. The classifier was used to associate each object -- say, a monkey's face -- with a particular pattern of neural signals, effectively decoding neural activity. Remarkably, the classifier found that just a split second's worth of the neural signal contained specific enough information to identity and categorize the object, even at positions and sizes the classifier had not previously "seen."
It was quite surprising that so few IT neurons (several hundred out of millions) for such a short period of time contained so much precise information. "If we could record a larger population of neurons simultaneously, we might find even more robust codes hidden in the neural patterns and extract even fuller information," Poggio said.
Science, Nov. 2005
Fast Readout of Object Identity from Macaque Inferior Temporal Cortex
Исследователи, безусловно, молодцы: опыт несложный и в то же время интересный. Но с выводами о расшифровке распознавательного кода я бы не торопился. Нельзя быть уверенным, что различия в паттернах связаны исключительно с характеристиками визуальных образов...В любом случае, получены достаточно ценные результаты.
http://www.physorg.com/news7879.html
http://www.membrana.ru/articles/global/2005/11/07/202700.html
neuroscientists in the McGovern Institute at MIT have been able to decipher a part of the code involved in recognizing visual objects. Practically speaking, computer algorithms used in artificial vision systems might benefit from mimicking these newly uncovered codes.
the researchers trained monkeys to recognize different objects grouped into categories, such as faces, toys and vehicles. The images appeared in different sizes and positions in the visual field. Recording the activity of hundreds of IT neurons produced a large database of IT neural patterns generated in response to each object under many different conditions.
the researchers used a computer algorithm, called a classifier, to decipher the code. The classifier was used to associate each object -- say, a monkey's face -- with a particular pattern of neural signals, effectively decoding neural activity. Remarkably, the classifier found that just a split second's worth of the neural signal contained specific enough information to identity and categorize the object, even at positions and sizes the classifier had not previously "seen."
It was quite surprising that so few IT neurons (several hundred out of millions) for such a short period of time contained so much precise information. "If we could record a larger population of neurons simultaneously, we might find even more robust codes hidden in the neural patterns and extract even fuller information," Poggio said.
Science, Nov. 2005
Fast Readout of Object Identity from Macaque Inferior Temporal Cortex
Исследователи, безусловно, молодцы: опыт несложный и в то же время интересный. Но с выводами о расшифровке распознавательного кода я бы не торопился. Нельзя быть уверенным, что различия в паттернах связаны исключительно с характеристиками визуальных образов...В любом случае, получены достаточно ценные результаты.