University of Texas: People’s Minds Can Be Revealed Using a Brain Activity Decoder
In Brief
Researchers at The University of Texas at Austin developed a semantic decoder, which can translate a person’s brain activity into a continuous stream of text.
It does not require surgical implants and does not need to use only words from a prescribed list.
Recent advances in AI systems have made it possible to decode the brain activity of an individual when they are listening to a story or imagining one themselves. This breakthrough, enabled by a new system called a semantic decoder developed by researchers at the University of Texas in Austin, can uncover stories from individual brains in a non-invasive way without having to implant surgical devices.
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When a person listens to a story or imagines telling one, neural signals are generated in the brain that can be measured using an fMRI scanner. With extensive training, AI systems can be taught to translate brain activity into a continuous stream of text, like the sentence “She has not even started to learn to drive yet” when the speaker says, “I don’t have my driver’s license yet.” The accuracy of this translation is remarkable, making it possible to extract stories from an individual’s brain without the need for external cues.
The researchers at The University of Texas created a semantic decoder that is capable of understanding some of the videos that a participant is watching as they undergo brain scans using an fMRI machine. The system accurately described different events from the videos without the need for external cues.
However, this semantic decoder is not practical outside of the laboratory. This is because it requires an extensive amount of time to be put into the training of the AI and a long session to be conducted on a fMRI machine which is not affordable for all and may not be available in every clinical facility.
Although the use of this AI system is still in its early stages, it has great potential and can be further developed in the future. Its ability to reveal a person’s thoughts and decode stories from their minds is an intriguing aspect of AI. If further research is done in the development of this system, it can be used in a variety of applications, including in clinical settings, to reveal stories behind the thinking of individuals and to help mental health professionals.
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Damir is the team leader, product manager, and editor at Metaverse Post, covering topics such as AI/ML, AGI, LLMs, Metaverse, and Web3-related fields. His articles attract a massive audience of over a million users every month. He appears to be an expert with 10 years of experience in SEO and digital marketing. Damir has been mentioned in Mashable, Wired, Cointelegraph, The New Yorker, Inside.com, Entrepreneur, BeInCrypto, and other publications. He travels between the UAE, Turkey, Russia, and the CIS as a digital nomad. Damir earned a bachelor's degree in physics, which he believes has given him the critical thinking skills needed to be successful in the ever-changing landscape of the internet.
