Thought identification

Thought identification refers to the empirically verified use of technology to, in some sense, read people's minds. Advances in research have made this possible by using human neuroimaging to decode a person's conscious experience based on non-invasive measurements of an individual's brain activity.

Professor of neuropsychology Barbara Sahakian qualifies, "A lot of neuroscientists in the field are very cautious and say we can't talk about reading individuals' minds, and right now that is very true, but we're moving ahead so rapidly, it's not going to be that long before we will be able to tell whether someone's making up a story, or whether someone intended to do a crime with a certain degree of certainty."

Psychologist John Dylan-Haynes experienced breakthroughs in brain imaging research in 2006 by using fMRI. This research included new findings on visual object recognition, tracking dynamic mental processes, lie detecting, and decoding unconscious processing. The combination of these four discoveries revealed such a significant amount of information about an individual's thoughts that Haynes termed it "brain reading".

The fMRI has allowed research to expand by significant amounts because it can track the activity in an individual's brain by measuring the brain's blood flow. It is currently thought to be the best method for measuring brain activity, which is why it has been used in multiple research experiments in order to improve the understanding of how doctors and psychologists can identify thoughts.

The term "thought identification" started being used in 2009 after neuroscientist Marcel Just coined it in a 60 Minutes interview. His reasoning for this term pertains to his overall goal of his research "to see if they could identify exactly what happens in the brain when people think specific thoughts."

When humans think of an object, such as a screwdriver, many different areas of the brain activate. Marcel Just and his colleague, Tom Mitchell, have used fMRI brain scans to teach a computer to identify the various parts of the brain associated with specific thoughts.

This technology also yielded a discovery: similar thoughts in different human brains are surprisingly similar neurologically. To illustrate this, Just and Mitchell used their computer to predict, based on nothing but fMRI data, which of several images a volunteer was thinking about. The computer was 100% accurate, but so far the machine is only distinguishing between 10 images.

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