Amazing technology : tool that decodes Brain Signals

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A  new computational tools that can instantly decode brain signals involved in viewing images have been developed by the NewYork  researchers including an Indian

electrodes in patients’ temporal lobes carry information that, when analysed, The researchers found and this enables the  scientists to predict what object patients are seeing.

Human Brain consist of  Temporal lobes process sensory input and are a common site of epileptic seizures. Situated behind mammals’ eyes and ears, the lobes are also involved in Alzheimer’s and dementias and appear somewhat more vulnerable than other brain structures to head traumas.

 

nature-brain

The scientists decoded brain signals at nearly the speed of perception using electrodes implanted in the temporal lobes of awake patients.

Powerful computational software that extracted two characteristic properties of the brain signal  electrodes from multiple temporal-lobe locations were connected  “event-related potentials” and “broadband spectral changes.”  “hundreds of thousands of neurons being co-activated when an image is first presented,” and continued after intial  wave information

Patients’ neural responses to two categories of visual stimuli images of faces and houses enabled the scientists to subsequently predict which images the patients were viewing, and when, with better than 95 percent accuracy.

Rajesh Rao from the University of Washington explained “We were trying to understand, first, how the human brain perceives objects in the temporal lobe, and second, how one could use a computer to extract and predict what someone is seeing in real time?”

“Clinically, you could think of our result as a proof of concept toward building a communication mechanism for patients who are paralysed or have had a stroke and are completely locked-in,” he said.

This techonlogy is blowing the mind and it took long time for the development of this technology and it would be definitely a future of science for more inventions reading the Human Brain.

The research was published in the journal PLOS Computational Biology.