Neuroscientists have developed a new technique that enables them
to decode what people are perceiving just by looking at a readout of
their brain signals. This ability to spontaneously decipher human
consciousness in real-time could have wide-ranging implications,
potentially leading to novel treatments for brain injuries or helping
people with locked-in syndrome to communicate.
The researchers collaborated with seven epilepsy patients at a hospital in Seattle, who had a number of electrodes called electrocorticographic (ECoG) arrays implanted into their brains. These targeted the temporal and occipital lobes of the brain's cortex, concerned with hearing and vision, respectively.
Patients were each shown a series of grayscale images of faces and houses, which flashed up on a screen in a random order for 400 milliseconds each. Using a novel framework for interpreting subjects’ brain activity data, the researchers were able to tell exactly when each patient had seen an image, and what that image contained. A report of this process has been published in the journal PLOS Computational Biology.
Lead researcher Kai Miller told IFLScience that “there have been other studies where scientists have been able to tell when a patient is looking at one type of an image or another, but the timing of this stimulus had always been known ahead of time.
“However, we were able to decode spontaneously from the signal, so we were able to look at the brain signal and say at this point in time they saw this particular type of image.” To achieve this, the team focused on two types of brain signals: event-related potentials (ERPs) and broadband.
Electrodes were implanted into the temporal and occipital lobes of epilepsy patients, and used to measure their brain activity when viewing a series of images. Kai Miller, Stanford University
ERPs are electrical signals emitted by neurons in each individual region of the brain. Deflections in these signals indicate that some sort of stimulation has occurred, and can therefore be used to accurately predict the timing of this stimulus. However, Miller explains that “these deflections have different shapes in different brain regions, so it’s hard to know what aspect of these signals is the most important [when attempting to decipher the nature of the stimulus].”
Broadband signals, however, provide a better indication of the average electrical output across the brain, and were found by the researchers to provide a better indication of what type of stimulus had occurred. Therefore, by using ERPs to determine the timing and broadband to determine the nature of the image that had been shown, the team was able to predict exactly what each subject had seen, and when, with greater than 95 percent accuracy.
“The breakthrough was that I was able to take different aspects of the signals that we measured and put them together in a novel way, both to show that the different aspects of the signal carry different types of information, and to read these signals to continuously decode what was going on,” said Miller.
By developing this technique further, he believes it may be one day be possible to retrain brain circuits in those who have suffered neurological damage as a result of injuries or strokes. In such cases, different brain regions may have lost the ability to communicate with one another, although Miller hopes that by reading the signals originating in one area of the brain and then artificially stimulating the region for which this information was intended, brain functionality could be restored.
“You could also imagine this being used for people who are looked in, meaning they can see but that’s about it,” he says. For instance, by decoding what they are experiencing, it may be possible to improve their prospects of communicating with others.
Source: www.iflscience.com
The researchers collaborated with seven epilepsy patients at a hospital in Seattle, who had a number of electrodes called electrocorticographic (ECoG) arrays implanted into their brains. These targeted the temporal and occipital lobes of the brain's cortex, concerned with hearing and vision, respectively.
Patients were each shown a series of grayscale images of faces and houses, which flashed up on a screen in a random order for 400 milliseconds each. Using a novel framework for interpreting subjects’ brain activity data, the researchers were able to tell exactly when each patient had seen an image, and what that image contained. A report of this process has been published in the journal PLOS Computational Biology.
Lead researcher Kai Miller told IFLScience that “there have been other studies where scientists have been able to tell when a patient is looking at one type of an image or another, but the timing of this stimulus had always been known ahead of time.
“However, we were able to decode spontaneously from the signal, so we were able to look at the brain signal and say at this point in time they saw this particular type of image.” To achieve this, the team focused on two types of brain signals: event-related potentials (ERPs) and broadband.
Electrodes were implanted into the temporal and occipital lobes of epilepsy patients, and used to measure their brain activity when viewing a series of images. Kai Miller, Stanford University
ERPs are electrical signals emitted by neurons in each individual region of the brain. Deflections in these signals indicate that some sort of stimulation has occurred, and can therefore be used to accurately predict the timing of this stimulus. However, Miller explains that “these deflections have different shapes in different brain regions, so it’s hard to know what aspect of these signals is the most important [when attempting to decipher the nature of the stimulus].”
Broadband signals, however, provide a better indication of the average electrical output across the brain, and were found by the researchers to provide a better indication of what type of stimulus had occurred. Therefore, by using ERPs to determine the timing and broadband to determine the nature of the image that had been shown, the team was able to predict exactly what each subject had seen, and when, with greater than 95 percent accuracy.
“The breakthrough was that I was able to take different aspects of the signals that we measured and put them together in a novel way, both to show that the different aspects of the signal carry different types of information, and to read these signals to continuously decode what was going on,” said Miller.
By developing this technique further, he believes it may be one day be possible to retrain brain circuits in those who have suffered neurological damage as a result of injuries or strokes. In such cases, different brain regions may have lost the ability to communicate with one another, although Miller hopes that by reading the signals originating in one area of the brain and then artificially stimulating the region for which this information was intended, brain functionality could be restored.
“You could also imagine this being used for people who are looked in, meaning they can see but that’s about it,” he says. For instance, by decoding what they are experiencing, it may be possible to improve their prospects of communicating with others.
Source: www.iflscience.com
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