Brain scans were used in two recently published studies that sought to understand the brain mechanisms underlying different behavioral outcomes.
Two recently published studies of brain development in newborns may help predict cognitive outcomes and assist in developing early interventions. These studies, led by Wei Gao, PhD, director of neuroimaging research at the Biomedial Imaging Research Institute (BIRI) at Cedars-Sinai, sought to understand the brain mechanisms underlying different behavioral outcomes.
Currently, there are no clinically acceptable biomarkers for early diagnosis or prediction of these issues.
The first study, published in Brain and Behavior, tested the hypothesis that newborns characterized as "brain outliers" using fMRI scans would go on to develop as "IQ outliers" at 4 years of age. The study showed the scans could detect more than 40% of "IQ outliers" at 4 years of age with a high specificity (96.2%). While there are likely many other postnatal factors that could contribute to the 4-year IQ outcome, this finding may have significant translational implications for using newborn imaging for early identification/prediction of risks.
Wei Gao, PhD
"If independently validated, this could open up the possibility to identify risks for delay in IQ development at 4 years of age or beyond based on an MRI scan right after birth," said Gao, professor of Biomedical Sciences.
The second study, published in Cerebral Cortex, creates a novel way to detect subgroups of infants with diverse brain-behavioral relationships. Investigators stress that different people may use different brain-behavior mechanisms and therefore there is likely heterogeneity in their brain-behavior relationships. The results of this study support this conclusion and reveal two subgroups of infants with contrasting brain-behavior relationships and differential IQ implications.
"This supports the idea that there could be different brain mechanisms for the same behavior among infants, which is important to guide future subgroup-based personalized predictions since this is likely not a 'one-model-fits-all' scenario," Gao said.
Taken together, the studies hold promise for investigators, who hope to better facilitate in-time interventions to allow for the best developmental outcomes in newborns.
"We want to be able to predict future behavioral outcomes or problems based on objective brain biomarkers, imaging-based brain connectivity measures in this case, to facilitate earliest possible intervention," Gao said. "If we wait until behavioral symptoms to emerge, in most cases it’s already too late to reverse the abnormal brain processes that may be ongoing for years before the symptom."
Funding: Research reported in this article was supported by the National Institutes of Health under award numbers R01DA042988, R01DA043678, R34DA050255, R01MH064065, R01DA043678 , R01MH064065and R01HD05300; and by the Cedars-Sinai Precision Health Initiative Awards.
