Neural Data Science

Human brain is least understood organ of human body. Neuroimaging has revolutionized field of psychology and cognitive neuroscience. Neuroscience coupled with machine learning has a great potential for uncovering mysteries of human brain. Neuroimaging studies have linked individual variability in brain to individualized personality traits. Objective of this study is to construct prediction model taking considerations of Resting state functional magnetic resonance image and use connectome based predictive modeling to predict personality traits. Personality traits of the five-factor model (FFM) were assessed by the NEO Five Factor Inventory. Human connectome project (HCP) dataset of 810 subjects with different set of parcellations, time series and connectivity matrices are used. PTN data in HCP used to predict neuroticism. Using a feature selection strategy from Connectome based predictive modeling. Support vector regression and neural networks were applied on data.