Learning Infant Brain Developmental Connectivity for Cognitive Score Prediction

Abstract

During infancy, the human brain develops rapidly in terms of structure, function and cognition. The tight connection between cognitive skills and brain morphology motivates us to focus on individual level cognitive score prediction using longitudinal structural MRI data. In the early postnatal stage, the massive brain region connections contain some intrinsic topologies, such as small-worldness and modular organization. Accordingly, graph convolutional networks can be used to incorporate different region combinations to predict the infant cognitive scores. Nevertheless, the definition of the brain region connectivity remains a problem. In this work, we propose a crafted layer, the Inter-region Connectivity Module (ICM), to effectively build brain region connections in a data-driven manner. To further leverage the critical cues hidden in the development patterns, we choose path signature as the sequential data descriptor to extract the essential dynamic information of the region-wise growth trajectories. With these region-wise developmental features and the inter-region connectivity, a novel Cortical Developmental Connectivity Network (CDC-Net) is built. Experiments on a longitudinal infant dataset within 3 time points and hundreds of subjects show our superior performance, outperforming classical machine learning based methods and deep learning based algorithms.

Development of sensorimotor-visual connectome gradient at birth predicts neurocognitive outcomes at 2 years of age

“… 31 , 32 Previous studies suggest that the individual cognitions at two years of age are robustly predicted by neonatal white matter structures and cortical morphological features. 33 , 34 The present study highlights that the sensorimotor-to-visual gradient in the functional connectome at birth is a good predictor of cognitive and language scores at two years of age. These results form a consensus that the establishment of brain functional organization during the third trimester has important implications for postnatal cognitive growth.…”

Development of Sensorimotor-Visual Connectome Gradient at Birth Predicts Cognitive Outcomes at 2 Years of Age

“…The development of individual mental functions is thought to be a consequence of the maturation of human brain structure and function (Casey et al, 2005; Johnson, 2005). Previous studies suggest that the individual cognitions at two years of age are robustly predicted by neonatal white matter structures and cortical morphological features (Li et al, 2021; Ouyang et al, 2020). The present study highlights that the sensorimotor-to-visual gradient in functional connectome at birth can well predict the cognitive scores at two years of age.…”