Using fMRI and machine learning for "brain reading"
December 23, 2011 by Editor

(Credit: iStockphoto)
In another Minority Report-like research finding, a UCLA research team has made crucial advances in "brain reading," using fMRI and machine learning methods to predict reactions of smokers experiencing nicotine cravings.
The research, presented last week at the Neural Information Processing Systems Machine Learning and Interpretation in Neuroimaging workshop in Spain, was funded by the National Institute on Drug Abuse, which is interested in using these methods to help people control drug cravings.
At UCLAs Laboratory of Integrative Neuroimaging Technology, researchers use functional MRI brain scans to observe brain signal changes that take place during mental activity. They then employ computerized machine learning (ML) methods to study these patterns and identify the cognitive state -- or sometimes the thought process -- of human subjects. The technique is called "brain reading" or "brain decoding."
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