New technology gleans the gist of stories a person hears while laying in a brain scanner
Functional magnetic resonance imaging captures coarse, colorful snapshots of the brain in action. While this specialized type of magnetic resonance imaging has transformed cognitive neuroscience, it isn’t a mind-reading machine: neuroscientists can’t look at a brain scan and tell what someone was seeing, hearing or thinking in the scanner.
“There’s a lot more information in brain data than we initially thought,” said Jerry Tang, a computational neuroscientist at the University of Texas at Austin and the study’s lead author, during a press briefing. The research, published on Monday in Nature Communications, is what Tang describes as “a proof of concept that language can be decoded from noninvasive recordings of brain activity.”
“Overall, there is definitely a long way to go, but the current results are better than anything we had before in fMRI language decoding,” says Anna Ivanova, a neuroscientist at the Massachusetts Institute of Technology who was not involved in the study. Neuroscientists have been working to decipher fMRI brain scans for decades to connect with people who can’t outwardly communicate. In a key 2010 study, scientists used fMRI to pose “yes or no” questions to an individual who couldn’t control his body and outwardly appeared to be unconscious.
After uncovering these patterns, the model took a new series of brain images and predicted what a person was hearing at the time they were taken. It worked gradually through the story, comparing the new scans to the AI’s predicted patterns for a host of candidate words. To prevent having to check every word in the English language, the researchers used GPT-1 to predict which words were most likely to appear in a particular context.
Still, the technology is many years away from being used as a brain-computer interface in everyday life. For one thing, the scanning technology isn’t portable—fMRI machines occupy entire rooms at hospitals and research institutions and cost millions of dollars. But Huth’s team is working to adapt these findings for existing brain-imaging systems that can be worn like a cap such as functional near-infrared spectroscopy and electroencephalography .
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