Much the same way it’s difficult to quantify pain on a scale of 1 to 10, subjective measures of cravings can be imprecise. This can make it difficult for clinicians trying to help a patient who is abusing a substance to determine the kind of care needed.
Now, scientists may have a more accurate tool for measuring cravings: employing a machine learning algorithm, an international team of scientists has identified a brain signature that, in their experiments, distinguished people with substance abuse disorders from people without them with a high degree of accuracy. The finding, published December 19 in Nature Neuroscience, could one day be used to help clinicians treat people with addictions by adding less subjective context to their reported cravings.
“It’s an interesting and well-done analysis,” says John Gabrieli, a neuroscientist at MIT who wasn’t involved in the research. “We want to somehow use our knowledge about the ...
