Abstract
A major contribution to our understanding of the aging brain comes either from studies comparing young with older adults or from studies investigating pathological aging and using the healthy aging older adults as control group. In consequence, we know relatively well, what distinguishes young from old brains or pathological aging from healthy but that does not mean that we really understand the structural and functional transformations characterizing the healthy aging brain. By analyzing task-free fMRI data from a large cross-sectional sample of 186 older adults (mean age = 70.4, 97 female), we aimed to elucidate age-related changes in the intrinsically active functional architecture of the brain in our study group covering an age range from 65 to 85 years. First, we conducted an intrinsic connectivity contrast analysis (ICC) in order to detect the brain regions whose degree of connectedness was significantly correlated with increasing age. Secondly, using connectivity analyses we investigated how the clusters highlighted by the ICC analysis functionally related to the other major resting-state networks. The most important finding was the right anterior insula's loss of connectedness in the older participants of the study group because of the region's causal role in the switching from the task-negative to the task-positive state of the brain. Further, we found a higher functional dedifferentiation of two of the brain's major intrinsic connectivity networks, the DMN, and the cingulo-opercular network, caused by a reduction of functional connection strength, especially in the frontal regions. At last, we showed that all these age-related changes have the potential to impair older adult's performance of working memory tasks.
Highlights
Growing old is associated with the aging brain’s structural degeneration like progressive gray matter atrophy or loss of white matter integrity as evidenced by structural neuroimaging methods (Raz et al, 1997; Good et al, 2001; Sowell et al, 2003; Salat et al, 2004; Fjell et al, 2009; Jäncke et al, 2015) and with cognitive and behavioral changes
Of the extracted 30 components, 13 components could be identified as neurophysiologically relevant intrinsic connectivity network (ICN) by visual inspection and by comparing them with the results of previous studies that likewise used a low-dimensional Independent Component Analysis (ICA) approach to parcellate the brain into ICNs (Damoiseaux et al, 2006; Shirer et al, 2012)
Results of the Connectivity Analyses: The Connection Profiles of the Intrinsic Connectivity Contrast Power (ICCp) Clusters a) ICCp cluster in the right SFG: The seed correlations analysis (SCA) had highlighted this cluster as a part of the DMN and its connection profile confirmed this network affiliation since the clusters showed the strongest positive connections with target ROISs of the anterior DMN followed by ROIs of the language network and the left executive control network (LECN)
Summary
Growing old is associated with the aging brain’s structural degeneration like progressive gray matter atrophy or loss of white matter integrity as evidenced by structural neuroimaging methods (Raz et al, 1997; Good et al, 2001; Sowell et al, 2003; Salat et al, 2004; Fjell et al, 2009; Jäncke et al, 2015) and with cognitive and behavioral changes. While task-induced fMRI studies investigating the aging brain generally observe roughly the same age-typical changes in the BOLD-signal patterns, the interpretations of these age-related patterns can be quite different, ranging from functional dedifferentiation (Persson et al, 2007; Meinzer et al, 2012; Berlingeri et al, 2013) to successful compensation (Cabeza, 2002; Davis et al, 2008). Studies using different forms of connectivity analyses, analyzing task-induced as well as task-free fMRI data, were able to show that the aging brain can generally be characterized by reduced functional connection strengths in comparison to the brain of younger adults. This affects the entire functional architecture of the brain. The within-network connections decrease and the between-network connections of the brain are affected and the different networks eventually seem to merge into each other and become more and more functionally dedifferentiated with age (Meunier et al, 2009; Betzel et al, 2014; Geerligs et al, 2014)
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