Mind Reading
Researchers using electrodes in patients’ temporal lobes have found that the signals carry information that let scientists predict what object patients are seeing, almost in real time.
Using electrodes implanted in the temporal lobes of awake patients, scientists have decoded brain signals at nearly the speed of perception. Further, analysis of patients’ neural responses to 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.
The research has been published in PLOS Computational Biology.
University of Washington computational neuroscientist Rajesh Rao and University of Washington Medicine (UW) neurosurgeon Jeff Ojemann, working their student Kai Miller and with colleagues in Southern California and New York, conducted the study.
Rao has also attained notoriety lately for his experiments in the field of brain-brain communication.
“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?” explained Rao, a UW professor of computer science and engineering. Rao also directs the National Science Foundation’s Center for Sensorimotor Engineering, headquartered at UW.
In the image above, the numbers 1-4 denote electrode placement in temporal lobe, and neural responses of two signal types being measured.
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“Clinically, you could think of our result as a proof of concept toward building a communication mechanism for patients who are paralyzed or have had a stroke and are completely locked-in,” he said.The study centered around seven epilepsy patients receiving care at Harborview Medical Center in Seattle. Each was experiencing epileptic seizures not relieved by medication, Ojemann said, so each had undergone surgery in which their brains’ temporal lobes were implanted – for about a week – with electrodes to try to locate the seizures’ focal points.
“They were going to get the electrodes no matter what; we were just giving them additional tasks to do during their hospital stay while they are otherwise just waiting around,” Ojemann said.
In the experiment, the electrodes from multiple temporal-lobe locations were connected to powerful computational software that extracted two characteristic properties of the brain signal: “event-related potentials” and “broadband spectral changes.”
Rao characterized the former as likely arising from “hundreds of thousands of neurons being co-activated when an image is first presented,” and the latter as “continued processing after the initial wave of information.”
The subjects, watching a computer monitor, were shown a random sequence of pictures of human faces and houses, interspersed with blank gray screens. Their task was to watch for an image of an upside-down house.
Neuroscientist Rajesh Rao and neurosurgeon Jeff Ojemann
“We got different responses from different (electrode) locations; some were sensitive to faces and some were sensitive to houses,” Rao said.
"Our result as a proof of concept toward building a communication mechanism for patients who are paralyzed or have had a stroke and are completely locked-in."
The software used sampled and digitized the brain signals 1,000 times per second to extract their characteristics. The software also analyzed the data to determine which combination of electrode locations and signal types correlated best with what each subject actually saw. In that way it yielded highly predictive information.
By training an algorithm on the subjects' responses to the known set of images, the researchers could examine the brain signals representing the final third of the images, whose labels were unknown to them, and predict with 96 percent accuracy whether and when (within 20 milliseconds) the subjects were seeing a house, a face or a gray screen.
This accuracy was attained only when event-related potentials and broadband changes were combined for prediction, which suggests they carry complementary information.
“Traditionally scientists have looked at single neurons,” Rao said. “Our study gives a more global picture, at the level of very large networks of neurons, of how a person who is awake and paying attention perceives a complex visual object.”
The scientists' technique, he said, is a steppingstone for brain mapping, in that it could be used to identify in real time which locations of the brain are sensitive to particular types of information.
“The computational tools that we developed can be applied to studies of motor function, studies of epilepsy, studies of memory. The math behind it, as applied to the biological, is fundamental to learning,” Ojemann said.
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