A new technique developed by
neuroscientists at U of T Scarborough can, for the first time, reconstruct
images of what people perceive based on their brain activity gathered by EEG. The
technique can digitally reconstruct images seen by test subjects based on
electroencephalography (EEG) data. For the study, test subjects hooked up to
EEG equipment were shown images of faces. Their brain activity was recorded and
then 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 reconstruct images based on visual stimuli using
neuro-imaging techniques. The current method was pioneered by Nestor who
successfully reconstructed facial images from functional magnetic resonance
imaging (fMRI) data in the past, but this is the first time EEG has been used.
And while techniques like fMRI, which
measures brain activity by detecting changes in blood flow, can grab finer
details of what’s going on in specific areas of the brain, EEG has greater
practical potential given that it’s more common, portable, and inexpensive by
comparison. EEG also has greater temporal resolution, meaning it can measure
with detail how a percept develops in time right down to milliseconds. This
study provides validation that EEG has potential for this type of image
reconstruction, something many researchers doubted was possible given its
apparent limitations. Using EEG data for image reconstruction has great
theoretical and practical potential from a neuro-technological standpoint,
especially since it’s relatively inexpensive and portable. In the future, it could
help people who are unable to verbally communicate.
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