A brain scan that can recognize an individual's thoughts may provide doctors with more definitive diagnoses for Alzheimer's disease and schizophrenia.
It has been reported that an innovative brain imaging system that can recognize an individual’s simple thoughts may provide doctors with more definitive diagnoses for Alzheimer's disease and schizophrenia.
Researchers at Stanford University in California used functional magnetic resonance imaging (fMRI) to classify brain activity patterns linked to differing mental states.
Firstly, fourteen participants of the study were requested to perform one of four tasks during a ten minute time period while their brains were scanned by the fMRI. Participants were asked to either sing songs silently to themselves, recall the events of the day, count backwards in threes, or to simply relax.
The scans taken from these participants were compared to scans from other volunteers performing the same task through computer algorithms searching for patterns of connectivity. Michael Greicius, Assistant Professor of Neurology and Neurological Science, believed that this method encouraged "natural" brain activity more like that which occurs in normal thought.
Once the computer algorithms had established the brain activity necessary for each task, Greicius asked ten new volunteers to do one of the four tasks.
Without prior knowledge concerning what each participant was assigned to think about, the system effectively recognized 85% of the tasks they were engaged performing. "Out of forty scans of the new people, we could identify thirty-four mental states correctly," he said.
The computer algorithm also correctly deduced that subjects were performing any of the four original tasks when it analyzed scans of participants thinking about moving around their homes.
Instead of having ambitions to use this technology to interrogate prisoners of the justice system or to potentially “read minds” for Big Brother, Greicius desires to see this tool help identify errors in the brain connections needed to perform daily tasks in Alzheimer's and schizophrenia patients.
"The most important potential for this is in the clinic where classifying and diagnosing and treating psychiatric disease could be really important," stated Brodersen. "At the moment, psychiatry is often just trial and error."
Some experts are skeptical, however.
“There would be a pretty coarse limit on what you could distinguish," said John Duncan of the UK Medical Research Council's Cognitive and Brain Sciences Centre in Cambridge. "The distinctiveness of an activity predicts the distinctiveness of brain activity associated with it," he added.
Kay Brodersen of the Swiss Federal Institute of Technology in Zurich, Switzerland, agreed. "You might be able to tell if someone is singing to themselves," he says. "But try to distinguish a Lady Gaga song from another and you would probably fail."
Regardless of this dubious prospect, there is no doubt that this is a powerful machine, with many potential medical benefits; with such a tool, psychiatric diagnosis would certainly never be quite the same.