Age-related differences in functional nodes of the brain cortex - a high model order group ICA study

Littow Littow

doi:10.3389/fnsys.2010.00032

Abstract

Functional MRI measured with blood oxygen dependent (BOLD) contrast in the absence of intermittent tasks reflects spontaneous activity of so-called resting state networks (RSN) of the brain. Group level independent component analysis (ICA) of BOLD data can separate the human brain cortex into 42 independent RSNs. In this study we evaluated age-related effects from primary motor and sensory, and, higher level control RSNs. One hundred sixty-eight healthy subjects were scanned and divided into three groups: 55 adolescents (ADO, 13.2 ± 2.4 years), 59 young adults (YA, 22.2 ± 0.6 years), and 54 older adults (OA, 42.7 ± 0.5 years), all with normal IQ. High model order group probabilistic ICA components (70) were calculated and dual-regression analysis was used to compare 21 RSN's spatial differences between groups. The power spectra were derived from individual ICA mixing matrix time series of the group analyses for frequency domain analysis. We show that primary sensory and motor networks tend to alter more in younger age groups, whereas associative and higher level cognitive networks consolidate and re-arrange until older adulthood. The change has a common trend: both spatial extent and the low frequency power of the RSN's reduce with increasing age. We interpret these result as a sign of normal pruning via focusing of activity to less distributed local hubs.

Highlights

In the mid 1990s, Biswal and Hyde were the first to notice that functionally connected regions of the brain are more synchronized in their activity than what could be expected from the noise in general
We evaluated age-related effects ranging from 25 independent resting state networks primary motor and sensory cortices to higher level control networks in 168 subjects divided into three age cohorts
There is a common trend in the age-related effects on resting state networks

Summary

Introduction

In the mid 1990s, Biswal and Hyde were the first to notice that functionally connected regions of the brain are more synchronized in their activity than what could be expected from the noise in general It was seen as there were modulated waves carrying information between different regions (Biswal et al, 1995). Spatial domain ICA (sICA) can separate BOLD signal sources that represent reactions to externally cued task-activations, background activity within functional brain (i.e., resting state) networks (RSN), and various physiological noise and artifact sources (McKeown et al, 1998; Calhoun et al, 2001; Kiviniemi et al, 2003; Beckmann and Smith, 2004; van de Ven et al, 2004; Beckmann et al, 2005) ICA methodology yields results that are consistent with the results of other contemporary methods of detecting large scale temporally coherent networks from the BOLD signal data (Long et al, 2008)

Methods

Results

Conclusion