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Scientists enter the brain's 'Matrix'

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Scientists have performed a Matrix-style hack into the brain's own computer code.

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(CNN) -- In a breakthrough that brings the technology of futuristic film "The Matrix" closer to reality, scientists say they have cracked part of the brain's own computer code.

A team of neurology experts from the Massachusetts Institute of Technology (MIT) say they have deciphered brain waves used in the recognition of visual images.

The development, reported in the journal Science, is reminiscent of the cult sci-fi film in which Keanu Reeves "jacks" into a computer system using a cable hardwired to his brain.

Neuroscientists at MIT's McGovern Institute hope they will be able to mimic brain codes to improve computer algorithms used in artificial vision.

"We want to know how the brain works to create intelligence," Tomaso Poggio, who carried out the research with James DiCarlo, told MIT's news office.

"Our ability to recognize objects in the visual world is among the most complex problems the brain must solve. Computationally, it is much harder than reasoning."

Just as the fictional Matrix recreates a virtual universe using a rapid stream of binary code, the brain's processing of visual data also involves high velocity computations, creating a major challenge for the scientists.

To learn how the brain processes visual input, the researchers trained monkeys to recognize different objects such as faces, toys and vehicles.

As the monkeys were confronted by each object, the activity of hundreds of neurons within the vision-related areas of the animals' brains was recorded.

Using a computer to crunch the numbers, the scientists discovered that our gray matter actually takes just a split second and uses relatively small numbers of neurons to transmit precise information.

Poggio said his team wanted to take more accurate snapshots of the brain's high-speed calculations in the hope of hacking more of the code.

"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," he said.

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