by Brooks Hays
Cambridge, Mass. (UPI) Jan 7, 2015
Brain scans have been widely employed and remarkably useful in correlative and experimental research, helping scientists better understand the human brain structure and its relationship to biological systems and the diseases that disrupt them. But can brain imaging also be used to predict human behaviors?
A new survey of recent scientific literature on the subject -- conducted by researchers at MIT and published this week in the journal Neuron -- suggests the answer is yes, it can. And has.
According to the new survey, imaging of the brain has already proven capable of predicting a person's future learning abilities and disabilities, propensity for criminality, health-related behaviors, and reception to drug and behavioral treatments.
As part of the new survey, researchers point to previous studies which showed brain imaging could predict infants' future performances on reading and math examinations. Another study found a correlation between brain structure and the likelihood of a criminal becoming a repeat offender.
"Presently, we often wait for failure, in school or in mental health, to prompt attempts to help, but by then a lot of harm has occurred," lead author Dr. John Gabrieli, an MIT neuroscientist, said in a press release. "If we can use neuroimaging to identify individuals at high risk for future failure, we may be able to help those individuals avoid such failure altogether."
"Seventy or so studies have reported positive findings that analyzing brain measures beforehand can considerably improve knowing whether a person will be successful at something," Gabrieli told Fox News.
Gabrieli and his colleagues were sure to point out the ethical dilemmas and risks involved in this sort of scientific research. Their hope in shedding light on these studies is to illuminate new methods of intervention, not to instigate restrictive policies aimed at high-risk patients.
"We will need to make sure that knowledge of future behavior is used to personalize educational and medical practices, and not be used to limit support for individuals at higher risk of failure," explained Gabrieli. "For example, rather than simply identifying individuals to be more or less likely to succeed in a program of education, such information could be used to promote differentiated education for those less likely to succeed with the standard education program."
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