AI News, Machine Learning Links Dimensions of Mental Illness to Brain Network Abnormalities

Machine Learning Links Dimensions of Mental Illness to Brain Network Abnormalities

Summary: Researchers use machine learning technology to identify brain based dimensions of mental health disorders.Source: University of Pennsylvania.

new study using machine learning has identified brain-based dimensions of mental health disorders, an advance towards much-needed biomarkers to more accurately diagnose and treat patients.

Satterthwaite, MD, an assistant professor in the department of Psychiatry, mapped abnormalities in brain networks to four dimensions of psychopathology: mood, psychosis, fear, and disruptive externalizing behavior.

Currently, psychiatry relies on patient reporting and physician observations alone for clinical decision making, while other branches of medicine have incorporated biomarkers to aid in diagnosis, determination of prognosis, and selection of treatment for patients.

While previous studies using standard clinical diagnostic categories have found evidence for brain abnormalities, the high level of diversity within disorders and comorbidity between disorders has limited how this kind of research may lead to improvements in clinical care.

“For example, when a patient comes in to see a doctor with most problems, in addition to talking to the patient, the physician will recommend lab tests and imaging studies to help diagnose their condition.

This research effort aims to link mental health issues and their associated brain network abnormalities to psychiatric symptoms using a data-driven approach.”

To uncover the brain networks associated with psychiatric disorders, the team studied a large sample of adolescents and young adults (999 participants, ages 8 to 22).

“Specifically, a pair of brain networks called default mode network and frontal-parietal network, whose connections usually grow apart during brain development, become abnormally integrated in all dimensions.”

These two brain networks have long intrigued psychiatrists and neuroscientists because of their crucial role in complex mental processes such as self-control, memory, and social interactions.

“This study shows that we can start to use the brain to guide our understanding of psychiatric disorders in a way that’s fundamentally different than grouping symptoms into clinical diagnostic categories.

doi:10.1038/s41467-018-05317-y Abstract Linked dimensions of psychopathology and connectivity in functional brain networks Neurobiological abnormalities associated with psychiatric disorders do not map well to existing diagnostic categories.

We find that four dimensions of psychopathology – mood, psychosis, fear, and externalizing behavior – are associated (r = 0.68–0.71) with distinct patterns of connectivity.

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