Emory University researchers have decoded visual images from a dog's brain.
The researchers captured functional magnetic resonance imaging (fMRI) neural data of two dogs as they viewed videos for 90 minutes in total, then analyzed their brain-data patterns using a machine learning algorithm.
They time-stamped the video data into classifiers, including object-based classifiers and action-based classifiers; the time stamps mapped the brain data onto the classifiers.
The Ivis algorithm decoded the action classifiers, but not the object classifiers, with 75% to 88% accuracy.
"We showed that we can monitor the activity in a dog's brain while it is watching a video and, to at least a limited degree, reconstruct what it is looking at," explained Emory's Gregory Berns.
From Emory University
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