Researchers used brain imaging to predict later development of ADHD and depression among children
For a team of researchers at the University of California at Berkeley, the theory of predicting the development of psychiatric disorders in children later in life through brain imaging was implemented and published in the journal JAMA Psychiatry.
According to the findings, brain imaging could in fact aid in identifying children at risk of common psychiatric disorders, like attention deficit hyperactivity disorder and major depressive disorder, strengthening the use of preventive treatments.
Between 2010 and 2013, 94 children from Vanderbilt University participated in the study. The results were achieved after a 4-year longitudinal cohort study examining any particular patterns associated with resting-state functional connectivity for predicting changes in psychiatric symptoms among children with no prior history of mental illness.
“A community cohort of 94 children was recruited from Vanderbilt University between 2010 and 2013. They were followed up longitudinally for 4 years and the data were analyzed from 2016 to 2019,” Susan Whitfield-Gabrieli, co-author of the study, stated.
“Based on preregistered hypotheses and an analytic plan, we examined whether specific brain connectivity patterns would be associated with longitudinal changes in scores on the Child Behavior Checklist (CBCL), a parental-report assessment used to screen for emotional, behavioral, and social problems and to predict psychiatric illnesses.”
The results indicated that specific brain regions, as measured by resting-state functional magnetic resonance imaging (fMRI), could play a major factor in identifying childhood neuromarkers of risk for psychiatric disorders. “These findings extend the use of neuroimaging to identify childhood neuromarkers of risk for psychopathology from highly selected children, such as those with identified familial risk, to a sample of children more representative of the population as a whole,” the findings explained.
“Resting-state functional connectivity is thought to reflect habitual network activations that can be remodeled by various long-term and even brief behavioral interventions and pharmacological interventions.”
“These resting-state fMRI metrics are promising biomarkers for the early identification of children at risk of developing MDD or attention-deficit/hyperactivity disorder,” researchers concluded.