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Machine learning could help diagnose depression early, according to the results of recently-published tests by scientists who homed in on patients who “ruminate” or think excessively about negative feelings or experiences.
The team “trained” an artificial intelligence algorithm to weigh up MRI scans and patients’ own reports of such rumination and in turn identify patterns related to the parts of the brain associated with the tendency, which they say is “a common symptom of depression.”
Such over-thinking or obsessing is a “cognitive style characterized by repetitive thoughts about one’s negative internal states,” and can leave people “stuck in a cycle of rumination that can aggravate and prolong distress, and thus contribute to multiple psychopathologies such as depression and anxiety,” according to the scientists, who were led by Jungwoo Kim of Sungkyunkwan University in South Korea and Jessica R. Andrews-Hanna of the University of Arizona.
Although previous investigations have linked rumination “to alterations in the default mode network” – the regions of the brain responsible for such introspection – there remains a lack of “predictive brain markers” for the trait or tendency.
However, that could be about to change. The team said their study “provides meaningful progress beyond previous literature by developing an integrated, predictive brain model of rumination that generalizes across multiple samples.”
