Age-related changes in topological patterns of large-scale brain functional networks during memory encoding and recognition
Introduction
The decline of memory and other cognitive functions has commonly been observed in normal aging (Park et al., 1996, Salthouse and Ferrer-Caja, 2003). A large body of evidence from functional neuroimaging studies has suggested that this decline is accompanied by focal changes in neuronal activity in many brain areas, such as the prefrontal cortex (Grady et al., 1995, Cabeza et al., 1997b, Logan et al., 2002, Madden et al., 2004, Mitchell et al., 2006, Nielson et al., 2006, Kukolja et al., 2009), medial temporal lobe (Grady et al., 1995, Cabeza et al., 2004, Gutchess et al., 2005, Nielson et al., 2006), parietal (Madden et al., 2004, Townsend et al., 2006, Persson et al., 2007, Miller et al., 2008) and occipital regions (Cabeza et al., 2004, Davis et al., 2008). There is also accumulating evidence that this decline is associated with alterations in the relationship among different brain regions (Grady et al., 1995, Cabeza et al., 1997a, Della-Maggiore et al., 2000, Grady et al., 2003, Daselaar et al., 2006, Andrews-Hanna et al., 2007, Taniwaki et al., 2007, Damoiseaux et al., 2008) in terms of functional or effective connectivity (Friston, 1994), possibly due to subtle anatomical disconnections between brain regions that ordinarily function in a coordinated fashion (O'Sullivan et al., 2001, Davis et al., 2009). It has been suggested that the performance of complex cognitive tasks, such as memory tasks, require highly segregated and integrated processing in these functionally linked, large-scale brain networks (Bressler and Kelso, 2001). However, it remains unclear to what extent the age-related abnormalities of both regional brain activation and functional connectivity affect these large-scale functional networks. To address this issue, in this study we sought to investigate changes in topological patterns of large-scale functional brain networks in normal aging during the performance of memory tasks.
Brain networks can be conceived of as neurocognitive entities that incorporate both local and global processes (Sporns and Tononi, 2002). Recently, there has been increasing interest in assessing cognitive brain networks using multivariate identification of whole-brain patterns of activity (Della-Maggiore et al., 2000, Grady et al., 2003, 2006). In recent years, the development of graph theoretical approaches has brought a fresh perspective to the investigation of complex brain networks (for reviews, see Boccaletti et al., 2006; Bullmore and Sporns, 2009). Many studies have consistently demonstrated that the normal brain is organized according to a highly efficient neuronal architecture, generally referred to as a small-world structure (Stam, 2004, Achard et al., 2006, He et al., 2007, Hagmann et al., 2008), which is characterized by high local specification and high global integration between brain regions. Moreover, this organization pattern is known to be disrupted in brain diseases (for recent reviews, see Bassett and Bullmore, 2009, He et al., 2009a). Recent findings indicate that development and normal aging are also accompanied by alterations in topology of functional brain networks (Achard and Bullmore, 2007, Fair et al., 2009, Meunier et al., 2009, Supekar et al., 2009). For instance, Achard and Bullmore (2007) showed that, compared with younger adults, older adults had decreased topological efficiency in spontaneous functional brain networks derived from resting-state functional magnetic resonance imaging (fMRI). Furthermore, they found that the age-related changes were mainly located at the connections between different functional clusters, such as fronto-parietal clusters (Meunier et al., 2009). As a whole, these studies have mainly investigated abnormal cognitive aging networks based on the spontaneous activity in the resting human brain. However, it has been found that specific cognitive tasks can provide novel information about brain activity (Morcom and Fletcher, 2007) compared to that obtained from resting-state data, and thus task-related functional connectivity is a useful tool for investigating interdependence among brain regions. In addition, previous studies on cognitive changes in aging have indicated that a single underlying mechanism may lead to age-related changes across multiple cognitive domains (Grady et al., 2006). In the current study we sought to investigate whether the effects of age on functional brain networks were task specific, or whether they reflected the influence of a common factor.
In this study, participants were scanned during the encoding and recognition portions of a memory task. Based on previous studies reporting age-related changes in brain activity and functional connectivity, we hypothesized that compared with younger adults, older adults would demonstrate altered topological patterns in large-scale functional brain networks during task performance. Additionally, based on converging evidence for a common factor underlying age-related changes (Grady et al., 2006) and for encoding–retrieval overlap in brain activation patterns (Nyberg, 2002), we hypothesized that each group would show a similar topological configuration in both the encoding and the recognition tasks. To address these hypotheses, we first measured functional connectivity among brain regions during the tasks in a group of younger and older adults, and then performed a weighted graph theoretical analysis to investigate both global and local network properties.
Section snippets
Participants
Data from 12 younger adults (5 males, 7 females; mean age: 23.2 years, range: 20–27) and 16 older adults (8 males, 8 females; mean age: 74.4 years, range: 75–87) were obtained from the fMRI Data Center (http://www.fmridc.org). All subjects were right-handed and screened for neurological and psychiatric illnesses. These subjects represented a subset of individuals whose data were previously analyzed (Grady et al., 2006) using partial least squares (McIntosh et al., 1996). The previous study also
Age-related changes in functional connectivity during memory tasks
We found that bilateral homogenous regions demonstrated strongly synchronized fluctuations in both groups and both conditions (Fig. 1), which was consistent with previous studies (Salvador et al., 2005, Achard et al., 2006). Visual inspection revealed that there were similar connectivity patterns in encoding and recognition tasks (left vs. right of Fig. 1C) but differences between the younger and older adults (top vs. bottom of Fig. 1C). Mean functional connectivity obtained from each subject
Discussion
The current study investigated age-related changes in the coordinated patterns of activity and topology in functional brain networks during performance of encoding and recognition phases of memory tasks. We found that the older adults showed impairments in long-range connections that were associated with decreased topological efficiency of information processing throughout the entire network. Additionally, normal aging was accompanied by reduced nodal centrality in several frontal and parietal
Conclusion
In this study, we provided evidence that changes in cognitive functions in aging are associated with changes in coordination between individual brain regions and their attendant network properties, which was demonstrated as a common factor to underlie the cognitive deficits. The results highlighted age-related alterations in the organization of functional brain networks relevant to goal-oriented tasks, thus potentially contributing, at the systems level, to our understanding how the brain
Acknowledgments
We are very grateful to Dr. Grady for providing the imaging dataset (http://www.fmridc.org) and two anonymous reviewers for valuable comments. The work was supported by the National Natural Science Foundation of China (Grant No. 30870667), Beijing Municipal Natural Science Foundation (Grant No. 7102090) and the Scientific Research Foundation for the Returned Overseas Chinese Scholars (State Education Ministry) to Dr. He; Michael Smith Foundation for Health Research (Grant No. CI-SCH-073(05-1))
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