Insights into brain network dynamics across ages using group-ICA functional parcellation

Abstract

Aging is a natural and inevitable process in human life that involves changes in the brain. The brain becomes structurally, functionally, and interconnected differently. The evolution of brain activity and its anatomy follows separate paths, causing them to not always align. Independent Component Analysis (ICA), a Blind Source Separation (BSS) method, enables brain parcellation considering an individual's functional patterns. This is advantageous when studying brain function at different stages of life, allowing for a more comprehensive and flexible approach that accounts for age-related differences. This study aims to investigate the relationship between age and functional networks, exploring the differences in the functional parcellations of two different age groups and their networks. We propose a method utilizing group-ICA that identifies functional connectivity patterns to estimate coherent networks. We found variations in the distribution of the age-related networks and the brain portions they covered; some networks in old adults encompassed smaller areas in comparison to the networks in young adults.

Keywords

• Brain parcellation
• fMRI
• Functional network
• Independent component analysis
• Resting-state