• The study combined functional magnetic resonance imaging (fMRI) and machine-learning techniques that use brain activation patterns to scan and decode the contents of a person's thoughts of objects or emotions
  • Machine-learning algorithms classified individuals as autistic or non-autistic with 97 percent accuracy based on the fMRI thought-markers
  • Implications of this research could extend to other psychiatric disorders, such as being suicidal or having obsessive-compulsive disorder, in which certain types of thoughts are altered.

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