Technique Developed by Neuroscientists can Rebuild Images People Perceive
The technique innovated by Dan Nemrodov, a postdoctoral fellow in Assistant Professor Adrian Nestor’s lab at University of Toronto Scarborough, is capable to digitally rebuild images seen by test subjects based on electroencephalography (EEG) data.
“When we see something, our brain creates a mental percept, which is essentially a mental impression of that thing. We were able to capture this percept using EEG to get a direct illustration of what’s happening in the brain during this process,” says Nemrodov.
For the research, test subjects linked up with EEG equipment were shown images of faces. Their brain activity was recorded and was used to digitally recreate the image in the subject’s mind using a technique based on machine learning algorithms. It’s not the first time researchers have been able to rebuild images based on visual stimuli using neuroimaging techniques. The current method was innovated by Nestor who successfully rebuilt facial images from functional Magnetic Resonance Imaging (fMRI) data in the past, however this is the first time EEG has been used.
While techniques such as fMRI which measures brain activity by detecting changes in blood flow aids in collecting finer details of activities going on in specific areas of the brain, EEG has comparatively greater practical capability given that it’s more cliché, portable, and inexpensive. “EEG also has greater temporal resolution, meaning it can measure with detail how a percept develops in time right down to milliseconds,” explains Nemrodov.
In terms of next steps, work is currently underway in Nestor’s lab to test how image rebuilding based on EEG data could be done using memory and applied to a wider range of objects beyond faces. However, it could later have a wide-focused clinical applications.
The scientific development in the field of new devices and sensors is elaborated in the Global Biometric Sensors Market, a report published by Coherent Market Insights.
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