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.