Effect of Age on Postural Balance and Control: Graph Based Connectivity Analysis on Brain Network

Abstract

Human brain undergoes various level of morphological changes with aging, volumetric atrophy of certain region being most common. Healthy aging is accompanied with deficits in motor and cognitive functions. Age-related atrophy of the motor cortical regions usually correlates with motor disabilities like postural imbalance, gait and coordination deficits etc. In this paper, we try to understand the changes in brain reorganization that occurs in normal healthy aging, specifically in regions involved in postural control. A brain network model has been developed implementing graph theory approach, using Diffusion Tensor Imaging (DTI) data for structural analysis, and resting-state functional MRI (fMRI) data for functional analysis, acquired from Nathan Kline Institute (NKI)-Rockland database. The data set have been divided in ‘young’ and ‘old’ group, based on age of individuals. Different conventional graph metrics have been evaluated for whole brain network as well as for specific regions like basal ganglia circuit, thalamus and brain stem in both structural and functional domain to analyze effect of aging. Results indicate network specific changes in cortico-basal ganglia region. Age related decreasing trend in graph metric parameters like local efficiency, modularity and clustering coefficient and an increasing trend for path length in both functional and structural connectivity analysis have been noticed. The insights from this study can be useful to identify healthy aging characteristics versus pathological changes.