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Longitudinal Charting of Infant Brain Connectomes in the First 6 Months of Life
Recent advances in graph theory and its application in brain imaging science (i.e., brain connectomes) have shed tremendous light on organizational principles of brain structure and function[1]. However, Research utilizing the technique to longitudinally follow the development of brain networks in infants is still rare. Such work will reveal new information with regard to the architecture of brain structure and function in brain development and has direct translational significance in many neurodevelopmental disorders, including autism spectrum disorder (ASD).
Objectives: To chart spatial and temporal details of brain networks of infants in their first 6 month of life using diffusion MRI and graph theory
Methods:
14 typically developing infants (corrected gestational age: 34-211 days, 4 females) were imaged up to 3 times under natural sleep in the first 6 months of life, resulting in 21 scans in total. The diffusion data were collected on Siemens Trio TIM system with a 32-channel head coil and multiband technique. The imaging parameters include: MB factor of 2, TR/TE=6200/74ms, FOV=184×184, matrix size of 92×92, diffusion directions of 61 with 6 b=0 images and a b-value of 700. Streamline probabilistic tractography based on the outputs of FSL was implemented in Camino, achieving approximately 7 million streamlines per subject. We assume that patterns of macro-scale region-to-region connections (i.e., brain connectivity pattern) of the brain in infants with different ages will be largely constant. It is the brain connectivity efficacy (defined as the inverse of the mean radial diffusivity (RD)) along the pathway linking the two regions that alters over time[3]. Thus, we first derived connectional matrices of 90 brain regions in 14 typical infant brains and then thresholded the averaged connectivity matrix at the network density of 10%. The weights of brain networks were quantified by the mean of 1/RD in each pathway. We then examined the relationship between a graph-theoretic metric, betweenness centrality(BC), and the corrected gestational age for changes of brain network maturation over time.
Results:
The global efficiency of whole brain networks is positively correlated with age(R=0.94, P<1.8e-10). The topological roles of each brain region in structural brain networks of infants vary with time and have divergent trends: quantified by BC, bilateral thalamus and right pre- and post- central gyri have decreasing centrality over time (Fig.1), even though the averaged connectivity efficacy (as measured by 1/RD) in these regions increases over time (THA.L: R=0.88, P<1.99e-7; PoCG.R: R=0.91, P<8.1e-9). In contrast, several cortical regions, such as left posterior cingulate gyrus (CINGpost), left middle frontal gyrus (MFG), right angular gyrus (ANGU) and right inferior occipital lobe (IOC) have increased BC over time, indicating their increasingly important roles in infant brain networks (Fig.1).
Conclusions:
Our study also seems to fit the two-process theory of early brain development[4], which proposes that early reflexive behaviors in young infants are mainly mediated by subcortical structures. Such experience-expectant subcortical control will gradually decline and be replaced by experience-dependent, cortical control. Recent work by our group suggests disruptions in this neurodevelopmental transition in infants subsequently diagnosed with ASD[5].