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Coupling of cerebral blood flow and functional connectivity is decreased in healthy aging

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Abstract

Aging leads to cerebral perfusion and functional connectivity changes that have been assessed using various neuroimaging techniques. In addition, a link between these two parameters has been demonstrated in healthy young adults. In this work, we employed arterial spin labeling (ASL) fMRI to measure global and voxel-wise differences in cerebral blood flow (CBF) and intrinsic connectivity contrast (ICC) in the resting state in a group of cognitively normal elderly subjects and a group of cognitively normal young subjects, in order to assess the effects of aging on CBF-ICC coupling, which had not been previously evaluated. Our results showed age-related global and regional CBF decreases in prefrontal mesial areas, lateral frontal regions, insular cortex, lateral parietal areas, precuneus and occipital regions. Subcortically, perfusion was reduced in the medial thalamus and caudate nucleus. ICC was also found reduced with age in prefrontal cortical areas and insular cortex, affecting key nodes of the default mode and salience networks. Areas of ICC and CBF decrease partially overlapped, however, the CBF reduction was more extensive and encompassed more areas. This dissociation was accompanied by a decrease in CBF-ICC coupling. These results suggest that aging leads to a disruption in the relationship between CBF and intrinsic functional connectivity that could be due to neurovascular dysregulation.

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References

  • Aguirre, G. K., & Detre, J. A. (2012). The development and future of perfusion fMRI for dynamic imaging of human brain activity. Neuroimage, 62, 1279–1285. https://doi.org/10.1016/j.neuroimage.2012.04.039 S1053-8119(12)00435-1 [pii].

    Article  PubMed  Google Scholar 

  • Aguirre, G. K., Detre, J. A., Zarahn, E., & Alsop, D. C. (2002). Experimental design and the relative sensitivity of BOLD and perfusion fMRI. Neuroimage, 15, 488–500.

    Article  CAS  Google Scholar 

  • Ances, B. M., Liang, C. L., Leontiev, O., Perthen, J. E., Fleisher, A. S., Lansing, A. E., & Buxton, R. B. (2009). Effects of aging on cerebral blood flow, oxygen metabolism, and blood oxygenation level dependent responses to visual stimulation. Human Brain Mapping, 30, 1120–1132. https://doi.org/10.1002/hbm.20574.

    Article  PubMed  PubMed Central  Google Scholar 

  • Andrews-Hanna, J. R., Snyder, A. Z., Vincent, J. L., Lustig, C., Head, D., Raichle, M. E., & Buckner, R. L. (2007). Disruption of large-scale brain systems in advanced aging. Neuron, 56, 924–935. https://doi.org/10.1016/j.neuron.2007.10.038.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Ashburner, J. (2007). A fast diffeomorphic image registration algorithm. Neuroimage, 38, 95–113.

    Article  Google Scholar 

  • Ashburner, J., & Friston, K. J. (2005). Unified segmentation. Neuroimage, 26, 839–851.

    Article  Google Scholar 

  • Asllani, I., Habeck, C., Borogovac, A., Brown, T. R., Brickman, A. M., & Stern, Y. (2009). Separating function from structure in perfusion imaging of the aging brain. Human Brain Mapping, 30, 2927–2935. https://doi.org/10.1002/hbm.20719.

    Article  PubMed  PubMed Central  Google Scholar 

  • Bentourkia, M., Bol, A., Ivanoiu, A., Labar, D., Sibomana, M., Coppens, A., Michel, C., Cosnard, G., & De Volder, A. G. (2000). Comparison of regional cerebral blood flow and glucose metabolism in the normal brain: effect of aging. Journal of the Neurological Sciences, 181, 19–28. https://doi.org/10.1016/S0022-510X(00)00396-8.

    Article  CAS  PubMed  Google Scholar 

  • Bertsch, K., Hagemann, D., Hermes, M., Walter, C., Khan, R., & Naumann, E. (2009). Resting cerebral blood flow, attention, and aging. Brain Research, 1267, 77–88. https://doi.org/10.1016/j.brainres.2009.02.053.

    Article  CAS  PubMed  Google Scholar 

  • Biagi, L., Abbruzzese, A., Bianchi, M. C., Alsop, D. C., Del Guerra, A., & Tosetti, M. (2007). Age dependence of cerebral perfusion assessed by magnetic resonance continuous arterial spin labeling. Journal of Magnetic Resonance Imaging, 25, 696–702.

    Article  Google Scholar 

  • Biswal, B. B., Mennes, M., Zuo, X. N., Gohel, S., Kelly, C., Smith, S. M., Beckmann, C. F., Adelstein, J. S., Buckner, R. L., Colcombe, S., Dogonowski, A. M., Ernst, M., Fair, D., Hampson, M., Hoptman, M. J., Hyde, J. S., Kiviniemi, V. J., Kotter, R., Li, S. J., Lin, C. P., Lowe, M. J., Mackay, C., Madden, D. J., Madsen, K. H., Margulies, D. S., Mayberg, H. S., McMahon, K., Monk, C. S., Mostofsky, S. H., Nagel, B. J., Pekar, J. J., Peltier, S. J., Petersen, S. E., Riedl, V., Rombouts, S. A., Rypma, B., Schlaggar, B. L., Schmidt, S., Seidler, R. D., Siegle, G. J., Sorg, C., Teng, G. J., Veijola, J., Villringer, A., Walter, M., Wang, L., Weng, X. C., Whitfield-Gabrieli, S., Williamson, P., Windischberger, C., Zang, Y. F., Zhang, H. Y., Castellanos, F. X., & Milham, M. P. (2010). Toward discovery science of human brain function. Proceedings of the National Academy of Sciences of the United States of America, 107, 4734–4739.

    Article  CAS  Google Scholar 

  • Biswal, B. B., Van Kylen, J., & Hyde, J. S. (1997). Simultaneous assessment of flow and BOLD signals in resting-state functional connectivity maps. NMR in Biomedicine, 10, 165–170.

    Article  CAS  Google Scholar 

  • Bressler, S. L., & Menon, V. (2010). Large-scale brain networks in cognition: emerging methods and principles. Trends in Cognitive Sciences, 14, 277–290. https://doi.org/10.1016/j.tics.2010.04.004.

    Article  PubMed  Google Scholar 

  • Brown, W. R., & Thore, C. R. (2011). Review: cerebral microvascular pathology in ageing and neurodegeneration. Neuropathology and Applied Neurobiology, 37, 56–74. https://doi.org/10.1111/j.1365-2990.2010.01139.x.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Buckner, R. L. (2004). Memory and executive function in aging and ad: multiple factors that cause decline and reserve factors that compensate. Neuron, 44, 195–208. https://doi.org/10.1016/j.neuron.2004.09.006.

    Article  CAS  PubMed  Google Scholar 

  • Buckner, R. L., Andrews-Hanna, J. R., Schacter, D. L. (2008). The brain's default network: anatomy, function, and relevance to disease. Annals of the New York Academy of Sciences, 1124, 1–38.

  • Cheitlin, M. D. (2003). Cardiovascular physiology — changes with aging. The American Journal of Geriatric Cardiology, 12, 9–13. https://doi.org/10.1111/j.1076-7460.2003.01751.x.

    Article  PubMed  Google Scholar 

  • Chen, J. J., Jann, K., & Wang, D. J. J. (2015). Characterizing resting-state brain function using arterial spin labeling. Brain Connectivity, 5, 527–542. https://doi.org/10.1089/brain.2015.0344.

    Article  PubMed  PubMed Central  Google Scholar 

  • Chen, J. J., Rosas, H. D., & Salat, D. H. (2011). Age-associated reductions in cerebral blood flow are independent from regional atrophy. Neuroimage, 55, 468–478. https://doi.org/10.1016/j.neuroimage.2010.12.032.

    Article  PubMed  Google Scholar 

  • Chuang, K. H., van Gelderen, P., Merkle, H., Bodurka, J., Ikonomidou, V. N., Koretsky, A. P., Duyn, J. H., & Talagala, S. L. (2008). Mapping resting-state functional connectivity using perfusion MRI. Neuroimage, 40, 1595–1605.

    Article  Google Scholar 

  • Dai, W., Garcia, D., de Bazelaire, C., & Alsop, D. C. (2008). Continuous flow-driven inversion for arterial spin labeling using pulsed radio frequency and gradient fields. Magnetic Resonance in Medicine, 60, 1488–1497.

    Article  Google Scholar 

  • Damoiseaux, J. S. (2017). Effects of aging on functional and structural brain connectivity. Neuroimage, 160, 32–40. https://doi.org/10.1016/j.neuroimage.2017.01.077.

    Article  PubMed  Google Scholar 

  • Damoiseaux, J. S., Beckmann, C. F., Arigita, E. J., Barkhof, F., Scheltens, P., Stam, C. J., Smith, S. M., & Rombouts, S. A. (2008). Reduced resting-state brain activity in the “default network” in normal aging. Cerebral Cortex, 18, 1856–1864. https://doi.org/10.1093/cercor/bhm207.

    Article  CAS  PubMed  Google Scholar 

  • De Luca, M., Beckmann, C. F., De Stefano, N., Matthews, P. M., & Smith, S. M. (2006). fMRI resting state networks define distinct modes of long-distance interactions in the human brain. Neuroimage, 29, 1359–1367.

    Article  Google Scholar 

  • Eickhoff, S. B., Stephan, K. E., Mohlberg, H., Grefkes, C., Fink, G. R., Amunts, K., & Zilles, K. (2005). A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data. Neuroimage, 25, 1325–1335.

    Article  Google Scholar 

  • Esposito, F., Aragri, A., Pesaresi, I., Cirillo, S., Tedeschi, G., Marciano, E., Goebel, R., & Di Salle, F. (2008). Independent component model of the default-mode brain function: combining individual-level and population-level analyses in resting-state fMRI. Magnetic Resonance Imaging, 26, 905–913. https://doi.org/10.1016/j.mri.2008.01.045.

    Article  PubMed  Google Scholar 

  • Fabiani, M., Gordon, B. A., Maclin, E. L., Pearson, M. A., Brumback-Peltz, C. R., Low, K. A., McAuley, E., Sutton, B. P., Kramer, A. F., & Gratton, G. (2014). Neurovascular coupling in normal aging: a combined optical, ERP and fMRI study. Neuroimage, 85, 592–607. https://doi.org/10.1016/j.neuroimage.2013.04.113.

    Article  PubMed  Google Scholar 

  • Fazekas, F., Chawluk, J. B., Alavi, A., Hurtig, H. I., & Zimmerman, R. A. (1987). MR signal abnormalities at 1.5 T in Alzheimer’s dementia and normal aging. AJR. American Journal of Roentgenology, 149, 351–356. https://doi.org/10.2214/ajr.149.2.351.

    Article  CAS  PubMed  Google Scholar 

  • Fernandez-Seara, M. A., Aznarez-Sanado, M., Mengual, E., Irigoyen, J., Heukamp, F., & Pastor, M. A. (2011). Effects on resting cerebral blood flow and functional connectivity induced by metoclopramide: a perfusion MRI study in healthy volunteers. British Journal of Pharmacology, 163, 1639–1652.

    Article  Google Scholar 

  • Fernandez-Seara, M. A., Aznarez-Sanado, M., Mengual, E., Loayza, F. R., & Pastor, M. A. (2009). Continuous performance of a novel motor sequence leads to highly correlated striatal and hippocampal perfusion increases. Neuroimage, 47, 1797–1808.

    Article  Google Scholar 

  • Fernandez-Seara, M. A., Mengual, E., Vidorreta, M., Castellanos, G., Irigoyen, J., Erro, E., & Pastor, M. A. (2015). Resting state functional connectivity of the subthalamic nucleus in Parkinson’s disease assessed using arterial spin-labeled perfusion fMRI. Human Brain Mapping, 36, 1937–1950.

    Article  Google Scholar 

  • Fernandez-Seara, M. A., Wang, J., Wang, Z., Korczykowski, M., Guenther, M., Feinberg, D. A., & Detre, J. A. (2007). Imaging mesial temporal lobe activation during scene encoding: comparison of fMRI using BOLD and arterial spin labeling. Human Brain Mapping, 28, 1391–1400.

    Article  Google Scholar 

  • Ferreira, L. K., & Busatto, G. F. (2013). Resting-state functional connectivity in normal brain aging. Neuroscience and Biobehavioral Reviews, 37, 384–400. https://doi.org/10.1016/j.neubiorev.2013.01.017.

    Article  PubMed  Google Scholar 

  • Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12, 189–198.

    Article  CAS  Google Scholar 

  • Gjedde, A., Johannsen, P., Cold, G. E., & Østergaard, L. (2005). Cerebral metabolic response to Low blood flow: possible role of cytochrome oxidase inhibition. Journal of Cerebral Blood Flow and Metabolism, 25, 1183–1196. https://doi.org/10.1038/sj.jcbfm.9600113.

    Article  CAS  PubMed  Google Scholar 

  • Grady, C. L., Protzner, A. B., Kovacevic, N., Strother, S. C., Afshin-Pour, B., Wojtowicz, M., Anderson, J. A. E., Churchill, N., & McIntosh, A. R. (2010). A multivariate analysis of age-related differences in default mode and task-positive networks across multiple cognitive domains. Cerebral Cortex, 20, 1432–1447. https://doi.org/10.1093/cercor/bhp207.

    Article  PubMed  Google Scholar 

  • Grieve, S. M., Clark, C. R., Williams, L. M., Peduto, A. J., & Gordon, E. (2005). Preservation of limbic and paralimbic structures in aging. Human Brain Mapping, 25, 391–401. https://doi.org/10.1002/hbm.20115.

    Article  PubMed  Google Scholar 

  • Gunther, M., Oshio, K., & Feinberg, D. A. (2005). Single-shot 3D imaging techniques improve arterial spin labeling perfusion measurements. Magnetic Resonance in Medicine, 54, 491–498.

    Article  Google Scholar 

  • Hedden, T. (2007). Imaging cognition in the aging human brain. In D. Riddle (Ed.), Brain aging: Models, methods, and mechanisms (pp. 1–11). CRC Press/Taylor & Francis.

  • Hedden, T., & Gabrieli, J. D. E. (2004). Insights into the ageing mind: A view from cognitive neuroscience. Nature Reviews. Neuroscience, 5, 87–96. https://doi.org/10.1038/nrn1323.

    Article  CAS  PubMed  Google Scholar 

  • Kaplan, E. F., Goodglass, H., & Weintraub, S. (1983). The Boston naming test (2nd ed.). Philadelphia: Lea & Febiger.

    Google Scholar 

  • Lancaster, J. L., Woldorff, M. G., Parsons, L. M., Liotti, M., Freitas, C. S., Rainey, L., Kochunov, P. V., Nickerson, D., Mikiten, S. A., & Fox, P. T. (2000). Automated Talairach atlas labels for functional brain mapping. Human Brain Mapping, 10, 120–131.

    Article  CAS  Google Scholar 

  • Leenders, K., Perani, D., Lammertsma, A., Heather, J., Buckingham, P., Jones, T., Healy, M., Gibbs, J., Wise, R., Hatazawa, J., Herold, S., Beaney, R., Brooks, D., Spinks, T., Rhodes, C., & Frackowiak, R. (1990). Cerebral blood flow, blood volume and oxygen utilization: normal values and effect of age. Brain, 113, 27–47.

    Article  Google Scholar 

  • Lemaitre, H., Goldman, A. L., Sambataro, F., Verchinski, B. A., Meyer-Lindenberg, A., Weinberger, D. R., & Mattay, V. S. (2012). Normal age-related brain morphometric changes: nonuniformity across cortical thickness, surface area and gray matter volume? Neurobiology of Aging, 33, 617.e1–617.e9. https://doi.org/10.1016/j.neurobiolaging.2010.07.013.

    Article  Google Scholar 

  • Liang, X., Connelly, A., & Calamante, F. (2015). Voxel-Wise functional Connectomics using arterial spin labeling functional magnetic resonance imaging: the role of Denoising. Brain Connectivity, 5, 543–553. https://doi.org/10.1089/brain.2014.0290.

    Article  PubMed  Google Scholar 

  • Liang, X., Tournier, J. D., Masterton, R., Connelly, A., & Calamante, F. (2012). A k-space sharing 3D GRASE pseudocontinuous ASL method for whole-brain resting-state functional connectivity. International Journal of Imaging Systems and Technology, 22, 37–43. https://doi.org/10.1002/ima.22006.

    Article  Google Scholar 

  • Liang, X., Zou, Q., He, Y., & Yang, Y. (2013). Coupling of functional connectivity and regional cerebral blood flow reveals a physiological basis for network hubs of the human brain. Proceedings of the National Academy of Sciences, 110, 1929–1934. https://doi.org/10.1073/pnas.1214900110.

    Article  Google Scholar 

  • Liu, Y., Zhu, X., Feinberg, D., Guenther, M., Gregori, J., Weiner, M. W., & Schuff, N. (2012). Arterial spin labeling MRI study of age and gender effects on brain perfusion hemodynamics. Magnetic Resonance in Medicine, 68, 912–922. https://doi.org/10.1002/mrm.23286.

    Article  PubMed  Google Scholar 

  • Martin, A. J., Friston, K. J., Colebatch, J. G., Frackowiak, R. S. (1991). Decreases in regional cerebral blood flow with normal aging. Journal of Cerebral Blood Flow and Metabolism, 11, 684–689.

  • Martuzzi, R., Ramani, R., Qiu, M. L., Shen, X. L., Papademetris, X., & Constable, R. T. (2011). A whole-brain voxel based measure of intrinsic connectivity contrast reveals local changes in tissue connectivity with anesthetic without a priori assumptions on thresholds or regions of interest. Neuroimage, 58, 1044–1050. https://doi.org/10.1016/j.neuroimage.2011.06.075.

    Article  PubMed  PubMed Central  Google Scholar 

  • Matsuda, H., Ohnishi, T., Asada, T., Li, Z., & Kanetaka, H. (2003). Correction for partial-volume effects on brain perfusion SPECT in healthy men. Journal of Nuclear Medicine, 44, 1243–1253.

    PubMed  Google Scholar 

  • Mevel, K., Landeau, B., Fouquet, M., La Joie, R., Villain, N., Mézenge, F., Perrotin, A., Eustache, F., Desgranges, B., & Chételat, G. (2013). Age effect on the default mode network, inner thoughts, and cognitive abilities. Neurobiology of Aging, 34, 1292–1301. https://doi.org/10.1016/j.neurobiolaging.2012.08.018.

    Article  PubMed  Google Scholar 

  • Morris, J. C., Heyman, A., Mohs, R. C., Hughes, J. P., van Belle, G., Fillenbaum, G., Mellits, E. D., & Clark, C. (1989). The consortium to establish a registry for Alzheimer’s disease (CERAD). Part I. Clinical and neuropsychological assessment of Alzheimer’s disease. Neurology, 39, 1159–1165.

    Article  CAS  Google Scholar 

  • Moscovitch, M., & Winocur, G. (1995). Frontal lobes, memory and aging. Annals of the New York Academy of Sciences, 769, 119–150.

    Article  CAS  Google Scholar 

  • Muller, A. M., Mérillat, S., & Jäncke, L. (2016a). Older but still fluent? Insights from the intrinsically active baseline configuration of the aging brain using a data driven graph-theoretical approach. Neuroimage, 127, 346–362. https://doi.org/10.1016/j.neuroimage.2015.12.027.

    Article  PubMed  Google Scholar 

  • Muller, A. M., Mérillat, S., & Jäncke, L. (2016b). Small changes, but huge impact? The right anterior insula’s loss of connection strength during the transition of old to very old age. Frontiers in Aging Neuroscience, 8, 1–20. https://doi.org/10.3389/fnagi.2016.00086.

    Article  Google Scholar 

  • Onoda, K., Ishihara, M., & Yamaguchi, S. (2012). Decreased functional connectivity by aging is associated with cognitive decline. Journal of Cognitive Neuroscience, 24, 2186–2198. https://doi.org/10.1162/jocn_a_00269.

    Article  PubMed  Google Scholar 

  • Parkes, L. M., Rashid, W., Chard, D. T., & Tofts, P. S. (2004). Normal cerebral perfusion measurements using arterial spin labeling: reproducibility, stability, and age and gender effects. Magnetic Resonance in Medicine, 51, 736–743. https://doi.org/10.1002/mrm.20023.

    Article  PubMed  Google Scholar 

  • Pfefferbaum, A., Adalsteinsson, E., & Sullivan, E. V. (2005). Frontal circuitry degradation marks healthy adult aging: evidence from diffusion tensor imaging. Neuroimage, 26, 891–899. https://doi.org/10.1016/j.neuroimage.2005.02.034.

    Article  PubMed  Google Scholar 

  • Poppelreuter, W. (1990). Disturbances of lower and higher visual capacities caused by occipital damage. Oxford: Oxford Science Publications.

    Google Scholar 

  • Power, J. D., Barnes, K. A., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2012). Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. Neuroimage, 59, 2142–2154. https://doi.org/10.1016/j.neuroimage.2011.10.018.

    Article  PubMed  Google Scholar 

  • Raichle, M. E., & Snyder, A. Z. (2007). A default mode of brain function: a brief history of an evolving idea. Neuroimage, 37, 1083–1090. https://doi.org/10.1016/j.neuroimage.2007.02.041.

    Article  PubMed  Google Scholar 

  • Raz, N., & Rodrigue, K. M. (2006). Differential aging of the brain: patterns, cognitive correlates and modifiers. Neuroscience and Biobehavioral Reviews, 30, 730–748. https://doi.org/10.1016/j.neubiorev.2006.07.001.

    Article  PubMed  PubMed Central  Google Scholar 

  • Reitan, R. M. (1955). The relation of the trail making test to organic brain damage. Journal of Consulting Psychology, 19, 393–394.

    Article  CAS  Google Scholar 

  • Satterthwaite, T. D., Wolf, D. H., Loughead, J., Ruparel, K., Elliott, M. A., Hakonarson, H., Gur, R. C., & Gur, R. E. (2012). Impact of in-scanner head motion on multiple measures of functional connectivity: relevance for studies of neurodevelopment in youth. Neuroimage, 60, 623–632. https://doi.org/10.1016/j.neuroimage.2011.12.063.

    Article  PubMed  PubMed Central  Google Scholar 

  • Seeley, W. W., Menon, V., Schatzberg, A. F., Keller, J., Glover, G. H., Kenna, H., Reiss, A. L., & Greicius, M. D. (2007). Dissociable intrinsic connectivity networks for salience processing and executive control. The Journal of Neuroscience, 27, 2349–2356.

    Article  CAS  Google Scholar 

  • Sigurdsson, S., Forsberg, L., Aspelund, T., Van Der Geest, R. J., Van Buchem, M. A., Launer, L. J., Gudnason, V., & Van Osch, M. J. (2015). Feasibility of using pseudo-continuous arterial spin labeling perfusion in a geriatric population at 1.5 tesla. PLoS One, 10, 1–15. https://doi.org/10.1371/journal.pone.0144743.

    Article  CAS  Google Scholar 

  • Storti, S. F., Boscolo Galazzo, I., Montemezzi, S., Menegaz, G., & Pizzini, F. B. (2017). Dual-echo ASL contributes to decrypting the link between functional connectivity and cerebral blow flow. Human Brain Mapping, 38, 5831–5844. https://doi.org/10.1002/hbm.23804.

    Article  PubMed  Google Scholar 

  • Stroop, J. R. (1935). Studies of interference in serial verbal reactions. Journal of Experimental Psychology, 18, 643–662. https://doi.org/10.1037/0096-3445.121.1.15.

    Article  Google Scholar 

  • Sullivan, E. V., & Pfefferbaum, A. (2006). Diffusion tensor imaging and aging. Neuroscience and Biobehavioral Reviews, 30, 749–761. https://doi.org/10.1016/j.neubiorev.2006.06.002.

    Article  PubMed  Google Scholar 

  • Tarantini, S., Tran, C. H. T., Gordon, G. R., Ungvari, Z., & Csiszar, A. (2017). Impaired neurovascular coupling in aging and Alzheimer’s disease: contribution of astrocyte dysfunction and endothelial impairment to cognitive decline. Experimental Gerontology, 94, 52–58. https://doi.org/10.1016/j.exger.2016.11.004.

    Article  CAS  PubMed  Google Scholar 

  • Van Den Heuvel, M. P., Mandl, R. C. W., Kahn, R. S., & Hulshoff Pol, H. E. (2009). Functionally linked resting-state networks reflect the underlying structural connectivity architecture of the human brain. Human Brain Mapping, 30, 3127–3141. https://doi.org/10.1002/hbm.20737.

    Article  PubMed  Google Scholar 

  • van Dijk, K. R. A., Sabuncu, M. R., & Buckner, R. L. (2012). The influence of head motion on intrinsic functional connectivity MRI. Neuroimage, 59, 431–438. https://doi.org/10.1016/j.neuroimage.2011.07.044.

    Article  PubMed  Google Scholar 

  • Vidorreta, M., Balteau, E., Wang, Z., De Vita, E., Pastor, M. A., Thomas, D. L., Detre, J. A., & Fernandez-Seara, M. A. (2014). Evaluation of segmented 3D acquisition schemes for whole-brain high-resolution arterial spin labeling at 3 T. NMR in Biomedicine, 27, 1387–1396.

    Article  Google Scholar 

  • Vidorreta, M., Wang, Z., Rodriguez, I., Pastor, M. A., Detre, J. A., & Fernandez-Seara, M. A. (2013). Comparison of 2D and 3D single-shot ASL perfusion fMRI sequences. Neuroimage, 66, 662–671.

    Article  Google Scholar 

  • Viviani, R., Messina, I., & Walter, M. (2011). Resting state functional connectivity in perfusion imaging: correlation maps with BOLD connectivity and resting state perfusion. PLoS One, 6, e27050.

    Article  CAS  Google Scholar 

  • Wang, Z., Aguirre, G. K., Rao, H., Wang, J., Fernandez-Seara, M. A., Childress, A. R., & Detre, J. A. (2008). Empirical optimization of ASL data analysis using an ASL data processing toolbox: ASLtbx. Magnetic Resonance Imaging, 26, 261–269.

    Article  Google Scholar 

  • Warrington, E.K., James, M., (1991). Visual object and space perception battery (VOSP). Thames Valley Test Company, Bury St. Edmunds, Suffolk.

  • Wechsler, D. (1997a). Wechsler memory scale - third edition. San Antonio: The Phychological Corporation.

    Google Scholar 

  • Wechsler, D. (1997b). Wechsler adult intelligence scale - third edition. San Antonio: The Phychological Corporation.

    Google Scholar 

  • West, R. (1996). An application of prefrontal cortex function theory to cognitive aging. Psychological Bulletin, 120, 272–292.

    Article  CAS  Google Scholar 

  • Whitfield-Gabrieli, S., & Nieto-Castanon, A. (2012). Conn: a functional connectivity toolbox for correlated and anticorrelated brain networks. Brain Connectivity, 2, 125–141.

    Article  Google Scholar 

  • Williams, D. S., Detre, J. A., Leigh, J. S., & Koretsky, A. P. (1992). Magnetic resonance imaging of perfusion using spin inversion of arterial water.[erratum appears in Proc Natl Acad Sci U S A 1992 May 1;89(9):4220]. Proceedings of the National Academy of Sciences of the United States of America, 89, 212–216.

    Article  CAS  Google Scholar 

  • Wu, J. T., Wu, H. Z., Yan, C. G., Chen, W. X., Zhang, H. Y., He, Y., & Yang, H. S. (2011). Aging-related changes in the default mode network and its anti-correlated networks: a resting-state fMRI study. Neuroscience Letters, 504, 62–67. https://doi.org/10.1016/j.neulet.2011.08.059.

    Article  CAS  PubMed  Google Scholar 

  • Wu, W. C., Fernandez-Seara, M., Detre, J. A., Wehrli, F. W., & Wang, J. (2007). A theoretical and experimental investigation of the tagging efficiency of pseudocontinuous arterial spin labeling. Magnetic Resonance in Medicine, 58, 1020–1027.

    Article  Google Scholar 

  • Yesavage, J. A., Brink, T. L., Rose, T. L., Lum, O., Huang, V., Adey, M., & Leirer, V. O. (1982). Development and validation of a geriatric depression screening scale: a preliminary report. Journal of Psychiatric Research, 17, 37–49.

    Article  Google Scholar 

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Acknowledgements

This work was supported by the Spanish Ministry of Economy and Competitiveness (grants SAF2014-56330-R and IEDI-2017-00826). This funding source did not have any role in study design, collection, analysis, interpretation of data, manuscript writing or decision to publish.

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This study was funded by the Spanish Ministry of Economy and Competitiveness (grants SAF2014–56330-R and IEDI-2017-00826).

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Correspondence to María A. Fernández-Seara.

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Galiano, A., Mengual, E., García de Eulate, R. et al. Coupling of cerebral blood flow and functional connectivity is decreased in healthy aging. Brain Imaging and Behavior 14, 436–450 (2020). https://doi.org/10.1007/s11682-019-00157-w

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