It sounds like a bit of science-fiction - but scientists say they have found a way to read the human mind.
Researchers at University of California, Los Angeles have developed what they call a 'brain reading' that uses past history to determine future cognitive patterns and thought process.
They compare the results to Google's predictive search capability, when the website guesses what search terms users are typing before they finish.
Scientists exposed the test subjects to videos meant to induce cravings. Some smokers were presented 'neutral' videos and some watched no video at all. They were then instructed to attempt to fight off any nicotine cravings.
MRI brain wave data was analysed to determine which regions of the brain and which neural networks are responsible for resisting nicotine addiction.
A computer learning machine used a method based on the Markov processes, allowing scientists to predict cognitive behaviour much like in the way Google predicts search terms or a mobile device might predict a word the user is typing before he is finished.
A spokesman for the research team told LA Weekly: 'Machine learning algorithms were able to anticipate changes in subjects' underlying neurocognitive structure, predicting with a high degree of accuracy (90 percent for some of the models tested) what they were watching and, as far as cravings were concerned, how they were reacting to what they viewed.'
Anderson said that researchers 'were predicting and detecting what kind of videos people were watching and whether they were resisting their cravings.'
'In essence, the algorithm was able to complete or "predict" the subjects' mental states and thought processes,' the spokesman said.
The research was presented last week at the Neural Information Processing Systems' Machine Learning and Interpretation in Neuroimaging workshop in Spain, which is interested in using the method to help addicts control drug cravings.
In the future, the scientists plan to use machine learning methods in a biofeedback context that will show 'real-time' brain readings that will alert them to when subjects are experiencing cravings in hopes of training them to suppress and control them.
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