Causality based Feature Fusion for Brain Neuro-Developmental Analysis

REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE - CLICK HERE TO EDIT) 1 Abstract -- Human brain development is a complex and dynamic process that is affected by several factors such as genetic s, sex hormones, and environmental changes . A number of recent studies on brain development have examined functional connectivity (FC) defi ned by the temporal correlation between time series of different brain regions. We propose to add the directional flow of information during brain maturation . To do so, w e extract effective connectivity (EC) through Granger causality (GC) for two different groups of subjects, i.e., children and young adults. The motivation is that the inclusion of causal interaction may further discriminate brain connections between two age groups and help to discover new conn ections between brain regions. The contributions of this study are three fold. First, t here has been a lack of attention to EC - based feature extraction in the context of brain development . T o this end, we propose a new kernel - based GC ( K GC) method to learn nonlinearity of complex brain network, where a reduced Sine hyperbolic polynomial ( RSP) neural network wa s used as our proposed learner . S econd, we use d causality values as the weight for the directional connectivity between brain regions . Our f indings indicate d that the strength of connections was significantly higher in young adult s relative to children. In addition, our new EC - based feature outperform ed FC - based analysis from Philadelphia neurocohort (PNC) study wi th better discrimination of the different age groups . Moreover, the fusion of these two sets of features (FC EC) improve d brain age prediction accuracy by more than 4 %, indicating that they should be used together for brain development stud ies . I NTRODUCTION uman brain development is a prolonged process that is initiated from the third gestational week (GW) to late adolescence, and presumably to the entire lifespan [ 1 ].