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Relationship Between Structural and Functional Connectivity Change Across the Adult Lifespan: a Longitudinal Investigation

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Relationship Between Structural and Functional Connectivity Change Across the Adult Lifespan: a Longitudinal Investigation r Human Brain Mapping 00:00–00 (2016) r Relationship Between Structural and Functional Connectivity Change Across the Adult Lifespan: A Longitudinal Investigation Anders M. Fjell,1,2* Markus H. Sneve,1 Ha˚kon Grydeland,1 Andreas B. Storsve,1 Inge K. Amlien,1 Anastasia Yendiki,3 and Kristine B. Walhovd1,2 1Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Norway, Pb. 1094 Blindern, Oslo 0317, Norway 2Department of Physical Medicine and Rehabilitation, Unit of neuropsychology, Oslo University Hospital, Norway 3Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts r r Abstract: Extensive efforts are devoted to understand the functional (FC) and structural connec- tions (SC) of the brain. FC is usually measured by functional magnetic resonance imaging (fMRI), and conceptualized as degree of synchronicity in brain activity between different regions. SC is typically indexed by measures of white matter (WM) properties, for example, by diffusion weighted imaging (DWI). FC and SC are intrinsically related, in that coordination of activity across regions ultimately depends on fast and efficient transfer of information made possible by structural connections. Convergence between FC and SC has been shown for specific networks, especially the default mode network (DMN). However, it is not known to what degree FC is con- strained by major WM tracts and whether FC and SC change together over time. Here, 120 partic- ipants (20–85 years) were tested at two time points, separated by 3.3 years. Resting-state fMRI was used to measure FC, and DWI to measure WM microstructure as an index of SC. TRACULA, part of FreeSurfer, was used for automated tractography of 18 major WM tracts. Cortical regions with tight structural couplings defined by tractography were only weakly related at the functional level. Certain regions of the DMN showed a modest relationship between change in FC and SC, but for the most part, the two measures changed independently. The main conclusions are that anatomical alignment of SC and FC seems restricted to specific networks and tracts, and that Additional Supporting Information may be found in the online specifically, grant number(s) S10RR023401, S10RR019307, S10RR version of this article. 019254, S10RR023043. This research was carried out in whole or in part at the Athinoula *Correspondence to: Anders M. Fjell, Department of Psychology, A. Martinos Center for Biomedical Imaging at the Massachusetts Pb. 1094 Blindern, 0317 Oslo, Norway. General Hospital, using resources provided by the Center for E-mail: [email protected] Functional Neuroimaging Technologies, P41EB015896, a P41 Bio- Received for publication 31 May 2016; Revised 17 August 2016; technology Resource Grant supported by the National Institute of Accepted 31 August 2016. Biomedical Imaging and Bioengineering (NIBIB), National Insti- tutes of Health. This work also involved the use of instrumenta- DOI: 10.1002/hbm.23403 tion supported by the NIH Shared Instrumentation Grant Published online 00 Month 2016 in Wiley Online Library Program and/or High-End Instrumentation Grant Program; (wileyonlinelibrary.com). VC 2016 Wiley Periodicals, Inc. r Fjell et al. r changes in SC and FC are not necessarily strongly correlated. Hum Brain Mapp 00:000–000, 2016. VC 2016 Wiley Periodicals, Inc. Key words: structural connectivity; functional connectivity; longitudinal; magnetic resonance imaging; aging; resting-state; tractography r r Davis et al., 2012; Lowe et al., 2008; Teipel et al., 2010; van INTRODUCTION den Heuvel et al., 2008; Wang et al., 2009]. However, strik- Understanding the brain by mapping its functional and ing differences in reported age-trajectories for microstruc- structural connections has sparked enormous interest. tural WM tract properties and FC indicate that the Functional (FC) and structural connectivity (SC) are closely relationship is unlikely to be simple. While age has a pro- related at a conceptual level, with FC being intrinsically found effect on WM microstructure, with negative age- dependent on SC for fast and efficient transfer of informa- relationship for fractional anisotropy (FA—degree of tion. However, it is not known to what degree FC is con- anisotropy of diffusion of water molecules) and positive strained by or related to characteristics of the major white for axial (AD—longitudinal, parallel or principal diffu- matter (WM) tracts of the brain, that is, their microstruc- sion), radial (RD—transverse diffusion, mean of the two tural properties as measured by diffusion weighted imag- minor axes of diffusion) and mean (MD—mean diffusion ing (DWI), and whether FC and the microstructural across all three axes) diffusivity [Bennett and Madden, properties of SC change together over time. The aim of the 2014; Lockhart and DeCarli, 2014; Salat et al., 2005a,b; Sex- present study was to use longitudinal data to test this in ton et al., in press; Westlye et al., 2010c], both positive and an adult lifespan sample where participants were scanned negative correlations between age and FC have been twice, separated by 3.3 years. Here, FC is measured by reported [Antonenko and Floel, 2014; Ferreira and Busatto, functional magnetic resonance imaging (fMRI), and 2013]. Different age-trajectories for FC and WM micro- indexed as degree of synchronicity in brain activity structure may not be surprising, since FC and SC usually between different regions when the participant is not per- are measured from tissue classes with different macro- forming any specific task in the scanner (resting-state structural age-trajectories, that is, gray vs. white matter fMRI). Resting-state functional connectivity then reflects [Walhovd et al., 2005, 2011]. Other lines of evidence indi- spontaneously occurring synchronization of brain activity cating a complex relationship between SC and FC are between distant brain areas in the absence of an externally reports of higher FC associated with lower WM integrity presented task, and is typically interpreted as indexing [Hawellek et al., 2011] and that major WM tracts are con- degree of communication between these areas. SC is used duits for smaller bundles that connect disparate functional to refer to diffusion characteristics of major WM tracts entities [Lehman et al., 2011]. Here, high FC has been identified by automated tractography, not to the actual interpreted as reflecting less-differentiated patterns of neu- existence or absence of fiber tracts. ral activity, reduced cognitive efficiency, or anatomical dis- Several lines of evidence support a relationship between connectivity leading to loss of functional diversity among FC and SC, for example, by convergence between FC and brain networks. For instance, lack of differentiation has SC of the default mode network (DMN) [Greicius et al., been proposed as a possible result of loss of flexibility in 2009; Horn et al., 2014; Zhu et al., 2014], and demonstra- the brain’s functional interactions, so that stronger appar- tions that both FC and properties of SC differ between ent functional connectivity could result from degradation groups of, for example, schizophrenic patients vs. controls of structural connections due to specific regions more fre- [Skudlarski et al., 2010; Zhou et al., 2008] and between quently participating in prevalent patterns of global activi- younger and older adults [Fling et al., 2012]. Still, the rela- ty seen, for example, in DMN [Hawellek et al., 2011]. tionship is complex, and regions with few or no direct Further, several cross-sectional developmental studies structural connections can show high FC, indicating pres- either did not observe strong relationships between micro- ence of indirect connections [Damoiseaux and Greicius, structural WM properties and FC, or found that the rela- 2009; Honey et al., 2009]. This means that tight connections tionships could change during development [Gordon can exist also between regions not connected by major et al., 2011; Uddin et al., 2011]. For instance, one study of WM tracts, possibly through smaller connections not easily the default mode network (DMN) found that FC in chil- captured by tractography or through common connections dren aged 7 to 9 years could reach adult-like levels despite with a third region. Nevertheless, changes in microstruc- weak SC [Supekar et al., 2010]. tural properties of major WM tracts are proposed to be a To examine the relationship between FC and microstruc- major causal factor for FC changes in aging [Ferreira and tural properties of major WM tracts at an individual level, Busatto, 2013], supported by cross-sectional FC-SC correla- we measured FC and WM diffusion characteristics at two tions where higher FC are related to higher FA or lower time points separated by 3.3 years on average in 120 par- MD or RD [Andrews-Hanna et al., 2007; Chen et al., 2009; ticipants, and tested whether they (a) related similarly to r 2 r r Connectivity Change Across the Adult Lifespan r age, and (b) to what extent change in one connectivity TABLE I. Sample descriptives measure was related to change in the other. We hypothe- sized partly different age-relationships for SC vs. FC, with Young & middle-aged Older adults Sig negative (FA) and positive (MD, RD, AD) relationships for SC, accelerating in the last part of the age-range, and a N6456 negative but weaker relationship for FC. Such changes Age 32.9 (23–52) 71.6 (63–86) * may be related to myelin disruption or loss, axonal injury Sex (females/males) 40/24 29/27 or other processes, but the exact neurobiological underpin- Education 15.9 (12–23) 16.5 (8–26) nings still are controversial [see Sexton et al., in press], for IQ 119 (101–133) 120 (90–146) a more thorough review, see [Bennett and Madden, 2014]. MMSE 29.6 (27–30) 29.0 (26–30) * Longitudinally, we hypothesized that changes in SC and Follow-up interval 3.4 (2.7–4.0) 3.1 (2.8–3.8) * FC would be moderately related, especially within the Age, IQ, and MMSE values from Tp2, education from Tp1.
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