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
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