The human brain develops at an incredible rate during the first several years of life. During this period, the brain is extremely plastic as it is vulnerable. My technical team complements the efforts of the clinical team led by Drs. Jim Barkovich and Donna Ferriero to leverage imaging in order to improve diagnosis and treatment monitoring of newborn patients. I personally chose this area of research partly as a scientific challenge. Subject motion is not the only issue that we deal with, as the anatomy, function, and metabolism of the brain are rapidly evolving. This is compounded by the fact that only in very rare instances can we obtain comprehensive imaging data on truly healthy children.
This particular manuscript describes our current efforts in studying the brain as a network, which is also termed “connectome.” By using water diffusion properties and the oxygenation level of brain tissue, we are able to build structural and functional networks of the brain. In many cases, the brain may appear normal, but as a network, it may not be functioning correctly; this is evident in cases of patients with initially similar-looking scans but very different outcomes. There are indications that early network parameters may predict eventual outcome, as we have shown a correlation in network differences between subjects with normal and abnormal outcomes. We are continuing to collect data and building a robust process to predict brain function by leveraging all available imaging methods.
To further note recent developments in the connectome field, Li and Tian1 studied the lateralization of the parieto-frontal network and correlations with IQ in children and adolescents. This is added evidence that the brain network matures and evolves with age, which highlights the fact that with an early enough indicator, we will eventually be able to predict neurologic outcome at a much earlier stage.
- Li C, Tian L. Association between resting-state coactivation in the parieto-frontal network and intelligence during late childhood and adolescence. AJNR Am J Neuroradiol 2014;35:1150–56, 10.3174/ajnr.A3850