Relationships between brain metabolism decrease in normal aging and changes in structural and functional connectivity
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Normal aging is characterized by brain glucose metabolism decline predominantly in the prefrontal cortex. The goal of the present study was to assess whether this change was associated with age-related alteration of white matter (WM) structural integrity and/or functional connectivity. FDG-PET data from 40 young and 57 elderly healthy participants from two research centers (n=49/48 in Center 1/2) were analyzed. WM volume from T1-weighted MRI (Center 1), fractional anisotropy from diffusion-tensor imaging (Center 2), and resting-state fMRI data (Center 1) were also obtained. Group comparisons were performed within each imaging modality. Then, positive correlations were assessed, within the elderly, between metabolism in the most affected region and the other neuroimaging modalities. Metabolism decline in the elderly predominated in the left inferior frontal junction (LIFJ). LIFJ hypometabolism was significantly associated with macrostructural and microstructural WM disturbances in long association fronto-temporo-occipital fibers, while no relationship was found with functional connectivity. The findings offer new perspectives to understand normal aging processes and open avenues for future studies to explore causality between age-related metabolism and connectivity changes.
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A default mode of brain function
Raichle, M. E., MacLeod, A. M., Snyder, A. Z., Powers, W. J., Gusnard, D. A., & Shulman, G. L. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.98.2.676 · Cited by 12,190 · see citing works
Fast robust automated brain extraction
Smith, S. M. (2002) · Human Brain Mapping · doi:10.1002/hbm.10062 · Cited by 10,496 · see citing works
<i>The Brain's Default Network</i>: <i>Anatomy, Function, and Relevance to Disease</i>
Buckner, R. L., Andrews‐Hanna, J. R., & Schacter, D. L. (2008) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1440.011 · Cited by 9,761 · see citing works
Dissociable intrinsic connectivity networks for salience processing and executive control
Seeley, W. W., Menon, V., Schatzberg, A. F., Keller, J., Glover, G. H., Kenna, H., Reiss, A. L., & Greicius, M. D. (2007) · The Journal of Neuroscience · doi:10.1523/jneurosci.5587-06.2007 · Cited by 7,426 · see citing works
Sperling, R. A., Aisen, P. S., Beckett, L. A., Bennett, D. A., Craft, S., Fagan, A. M., Iwatsubo, T., Jack, C. R., Kaye, J., Montine, T. J., et al. (2011) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2011.03.003 · Cited by 7,155 · see citing works
A Voxel-Based Morphometric Study of Ageing in 465 Normal Adult Human Brains
Good, C. D., Johnsrude, I. S., Ashburner, J., Henson, R. N. A., Friston, K. J., & Frackowiak, R. S. J. (2001) · NeuroImage · doi:10.1006/nimg.2001.0786 · Cited by 4,561 · see citing works
Toward discovery science of human brain function
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., et al. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0911855107 · Cited by 2,970 · see citing works
Disruption of Large-Scale Brain Systems in Advanced Aging
Andrews-Hanna, J. R., Snyder, A. Z., Vincent, J. L., Lustig, C., Head, D., Raichle, M. E., & Buckner, R. L. (2007) · Neuron · doi:10.1016/j.neuron.2007.10.038 · Cited by 1,592 · see citing works
Looking into the functional architecture of the brain with diffusion MRI.
Le Bihan, D. (2003) · Nature Reviews Neuroscience · doi:10.1038/nrn1119 · Cited by 1,571 · see citing works
Differential aging of the brain: Patterns, cognitive correlates and modifiers
Raz, N., & Rodrigue, K. M. (2006) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2006.07.001 · Cited by 1,195 · see citing works
Age-related myelin breakdown: a developmental model of cognitive decline and Alzheimer’s disease
Bartzokis, G. (2004) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2003.03.001 · Cited by 968 · see citing works
Diffusion tensor imaging and beyond
Tournier, J., Mori, S., & Leemans, A. (2011) · Magnetic Resonance in Medicine · doi:10.1002/mrm.22924 · Cited by 921 · see citing works
Age-related alterations in white matter microstructure measured by diffusion tensor imaging
Salat, D. H., Tuch, D. S., Greve, D. N., van der Kouwe, A. J. W., Hevelone, N. D., Zaleta, A. K., Rosen, B. R., Fischl, B. R., Corkin, S., Rosas, H. D., et al. (2004) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2004.09.017 · Cited by 832 · see citing works
Discrimination between Alzheimer dementia and controls by automated analysis of multicenter FDG PET
Herholz, K., Salmon, E., Perani, D., Baron, J.-C., Holthoff, V., Frölich, L., Schönknecht, P., Ito, K., Mielke, R., & Kalbe, E. (2002) · NeuroImage · doi:10.1006/nimg.2002.1208 · Cited by 832 · see citing works
Life-Span Changes of the Human Brain White Matter: Diffusion Tensor Imaging (DTI) and Volumetry
Westlye, L. T., Walhovd, K. B., Dale, A. M., Bjornerud, A., Due-Tonnessen, P., Engvig, A., Grydeland, H., Tamnes, C. K., Ostby, Y., & Fjell, A. M. (2010) · Cerebral Cortex · doi:10.1093/cercor/bhp280 · Cited by 765 · see citing works
Age-related changes in modular organization of human brain functional networks
Meunier, D., Achard, S., Morcom, A., & Bullmore, E. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.09.062 · Cited by 756 · see citing works
Marked loss of myelinated nerve fibers in the human brain with age
Marner, L., Nyengaard, J., Tang, Y., & Pakkenberg, B. (2003) · The Journal of comparative neurology · doi:10.1002/cne.10714 · Cited by 625 · see citing works
The effects of normal aging on myelin and nerve fibers: a review
Peters, A. (2002) · Journal of Neurocytology · doi:10.1023/a:1025731309829 · Cited by 577 · see citing works
Age-related changes in grey and white matter structure throughout adulthood
Giorgio, A., Santelli, L., Tomassini, V., Bosnell, R., Smith, S., De Stefano, N., & Johansen-Berg, H. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.03.004 · Cited by 532 · see citing works
The Human Brain: Surface, Three-Dimensional Sectional Anatomy with MRI, and Blood Supply
Duvernoy, H. M., Bourgouin, P. M., & Vannson, J. L. (1999) · Cited by 520 · see citing works
Assessing the effects of age on long white matter tracts using diffusion tensor tractography
Davis, S. W., Dennis, N. A., Buchler, N. G., White, L. E., Madden, D. J., & Cabeza, R. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.01.068 · Cited by 458 · see citing works
The role of the inferior frontal junction area in cognitive control.
BRASS, M., DERRFUSS, J., FORSTMANN, B., & CRAMON, D. (2005) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2005.05.001 · Cited by 437 · see citing works
Normal aging in the central nervous system: Quantitative MR diffusion-tensor analysis
Abe, O., Aoki, S., Hayashi, N., Yamada, H., Kunimatsu, A., Mori, H., Yoshikawa, T., Okubo, T., & Ohtomo, K. (2002) · Neurobiology of Aging · doi:10.1016/s0197-4580(01)00318-9 · Cited by 420 · see citing works
White Matter Structural Integrity in Healthy Aging Adults and Patients With Alzheimer Disease
Bartzokis, G., Cummings, J. L., Sultzer, D. L., Henderson, V. W., Nuechterlein, K. H., & Mintz, J. (2003) · Archives of Neurology · doi:10.1001/archneur.60.3.393 · Cited by 415 · see citing works
Voxel-based mapping of brain gray matter volume and glucose metabolism profiles in normal aging
Kalpouzos, G., Chételat, G., Baron, J.-C., Landeau, B., Mevel, K., Godeau, C., Barré, L., Constans, J.-M., Viader, F., Eustache, F., et al. (2009) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2007.05.019 · Cited by 392 · cited 4× · see citing works
“In vivo cross-sectional 18 FDG-PET studies in normal healthy individuals have consistently shown decreased cerebral glucose metabolism with age, with a differential effect across brain regions, the frontal cortex showing the greatest effects (Moeller et al., 1996; Petit-Taboué et al., 1998; Garraux et al., 1999; Herho…”
BackgroundInfluentialRelationship between atrophy and β‐amyloid deposition in Alzheimer disease
Chételat, G., Villemagne, V. L., Bourgeat, P., Pike, K. E., Jones, G., Ames, D., Ellis, K. A., Szoeke, C., Martins, R. N., O'Keefe, G. J., et al. (2010) · Annals of Neurology · doi:10.1002/ana.21955 · Cited by 373 · see citing works
Age-related changes in the default mode network are more advanced in Alzheimer disease
Jones, D. T., Machulda, M. M., Vemuri, P., McDade, E. M., Zeng, G., Senjem, M. L., Gunter, J. L., Przybelski, S. A., Avula, R. T., Knopman, D. S., et al. (2011) · Neurology · doi:10.1212/wnl.0b013e318233b33d · Cited by 370 · see citing works
Villain, N., Desgranges, B., Viader, F., de la Sayette, V., Mezenge, F., Landeau, B., Baron, J.-C., Eustache, F., & Chetelat, G. (2008) · Journal of Neuroscience · doi:10.1523/jneurosci.1392-08.2008 · Cited by 366 · see citing works
Self-citationBartzokis, G., Sultzer, D., Lu, P. H., Nuechterlein, K. H., Mintz, J., & Cummings, J. L. (2004) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2003.09.005 · Cited by 363 · see citing works
Fractional anisotropy of water diffusion in cerebral white matter across the lifespan
Kochunov, P., Williamson, D. E., Lancaster, J., Fox, P. T., Cornell, J. E., Blangero, J., & Glahn, D. C. (2010) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2010.01.014 · Cited by 363 · see citing works
Frontal circuitry degradation marks healthy adult aging: Evidence from diffusion tensor imaging
Pfefferbaum, A., Elfar Adalsteinsson, A., & Sullivan, E. V. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.02.034 · Cited by 350 · see citing works
Age-induced white matter changes in the human brain: a stereological investigation.
Tang, Y., Nyengaard, J., Pakkenberg, B., & Gundersen, H. (1997) · Neurobiology of Aging · doi:10.1016/s0197-4580(97)00155-3 · Cited by 345 · see citing works
Direct voxel-based comparison between grey matter hypometabolism and atrophy in Alzheimer's disease
Chételat, G., Desgranges, B., Landeau, B., Mézenge, F., Poline, J.-B., Sayette, V. D. L., Viader, F., Eustache, F., & Baron, J. (2007) · Brain · doi:10.1093/brain/awm288 · Cited by 340 · see citing works
White Matter Microstructural Integrity and Cognitive Function in a General Elderly Population
Vernooij, M. W., Ikram, M. A., Vrooman, H. A., Wielopolski, P. A., Krestin, G. P., Hofman, A., Niessen, W. J., Van der Lugt, A., & Breteler, M. M. B. (2009) · Archives of General Psychiatry · doi:10.1001/archgenpsychiatry.2009.5 · Cited by 335 · see citing works
Grady, C. L., Protzner, A. B., Kovacevic, N., Strother, S. C., Afshin‐Pour, B., Wojtowicz, M., Anderson, J. A. E., Churchill, N. W., & McIntosh, A. R. (2009) · Cerebral Cortex · doi:10.1093/cercor/bhp207 · Cited by 327 · see citing works
Preservation of limbic and paralimbic structures in aging
Grieve, S. M., Clark, C. R., Williams, L. M., Peduto, A. J., & Gordon, E. (2005) · Human Brain Mapping · doi:10.1002/hbm.20115 · Cited by 293 · see citing works
Sullivan, E. V., Adalsteinsson, E., & Pfefferbaum, A. (2006) · Cerebral Cortex · doi:10.1093/cercor/bhj045 · Cited by 280 · see citing works
MRI atlas of human white matter
Oishi, K., & Crain, B. J. (2010) · Cited by 272 · see citing works
The metabolic topography of normal aging
Moeller, J. R., Ishikawa, T., Dhawan, V., Spetsieris, P., Mandel, F., Alexander, G. E., Grady, C., Pietrini, P., & Eidelberg, D. (1996) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1097/00004647-199605000-00005 · Cited by 254 · see citing works
Kochunov, P., Thompson, P. M., Lancaster, J. L., Bartzokis, G., Smith, S., Coyle, T., Royall, D. R., Laird, A., & Fox, P. T. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2006.12.021 · Cited by 250 · see citing works
Villain, N., Fouquet, M., Baron, J.-C., Mezenge, F., Landeau, B., de La Sayette, V., Viader, F., Eustache, F., Desgranges, B., & Chetelat, G. (2010) · Brain · doi:10.1093/brain/awq203 · Cited by 237 · see citing works
Petit-Taboué, M. C., Landeau, B., Desson, J. F., Desgranges, B., & Baron, J. C. (1998) · NeuroImage · doi:10.1006/nimg.1997.0318 · Cited by 221 · see citing works
Default Network Modulation and Large-Scale Network Interactivity in Healthy Young and Old Adults
Spreng, R. N., & Schacter, D. L. (2012) · Cerebral Cortex · doi:10.1093/cercor/bhr339 · Cited by 214 · see citing works
Age-related degeneration of corpus callosum measured with diffusion tensor imaging
Ota, M., Obata, T., Akine, Y., Ito, H., Ikehira, H., Asada, T., & Suhara, T. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.02.008 · Cited by 210 · see citing works
Sex differences in corpus callosum size: relationship to age and intracranial size
Sullivan, E. V., Rosenbloom, M. J., Desmond, J. E., & Pfefferbaum, A. (2001) · Neurobiology of Aging · doi:10.1016/s0197-4580(01)00232-9 · Cited by 200 · see citing works
Sperling, R. A., Aisen, P. S. S., Beckett, L. A., Bennett, D. A., Craft, S., Fagan, A. M., Iwatsubo, T., Jack, C. R., Kaye, J. A., Montine, T. J., et al. (2011) · Cited by 197 · see citing works
Coevolution of white matter hyperintensities and cognition in the elderly
Maillard, P., Carmichael, O., Fletcher, E., Reed, B., Mungas, D., & DeCarli, C. (2012) · Neurology · doi:10.1212/wnl.0b013e3182617136 · Cited by 172 · see citing works
Bartzokis, G., Lu, P. H., Heydari, P., Couvrette, A., Lee, G. J., Kalashyan, G., Freeman, F., Grinstead, J. W., Villablanca, P., Finn, J. P., et al. (2012) · Biological Psychiatry · doi:10.1016/j.biopsych.2012.07.010 · Cited by 152 · see citing works
Fjell, A. M., Westlye, L. T., Greve, D. N., Fischl, B. R., Benner, T., van der Kouwe, A. J. W., Salat, D. H., Bjørnerud, A., Due‐Tønnessen, P., & Walhovd, K. B. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.06.005 · Cited by 151 · see citing works
Estimating Smoothness in Statistical Parametric Maps
Poline, J., Worsley, K. J., Holmes, A. P., Frackowiak, R. S. J., & Friston, K. J. (1995) · Journal of Computer Assisted Tomography · doi:10.1097/00004728-199509000-00017 · Cited by 143 · see citing works
Rovaris, M., Iannucci, G., Cercignani, M., Sormani, M. P., Stefano, N. D., Gerevini, S., Comi, G., & Filippi, M. (2003) · Radiology · doi:10.1148/radiol.2273020721 · Cited by 137 · see citing works
Age effect on the default mode network, inner thoughts, and cognitive abilities
Mevel, K., Landeau, B., Fouquet, M., Joie, R. L., Villain, N., Mézenge, F., Perrotin, A., Eustache, F., Desgranges, B., & Chételat, G. (2012) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2012.08.018 · Cited by 136 · see citing works
Wu, J., Wu, H.-Z., Yan, C., Chen, W., Zhang, H., Yong He, A., & Yang, H. (2011) · Neuroscience Letters · doi:10.1016/j.neulet.2011.08.059 · Cited by 122 · see citing works
Predominant ventromedial frontopolar metabolic impairment in frontotemporal dementia
Salmon, É., Garraux, G., Delbeuck, X., Collette, F., Kalbe, E., Zuendorf, G., Perani, D., Fazio, F., & Herholz, K. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00346-x · Cited by 122 · see citing works
Zuendorf, G., Kerrouche, N., Herholz, K., & Baron, J. (2002) · Human Brain Mapping · doi:10.1002/hbm.10069 · Cited by 119 · see citing works
Executive deficits are related to the inferior frontal junction in early dementia
Schroeter, M. L., Vogt, B., Frisch, S., Becker, G., Barthel, H., Mueller, K., Villringer, A., & Sabri, O. (2011) · Brain · doi:10.1093/brain/awr311 · Cited by 116 · see citing works
Mulkern, R. V., Zengingönül, H. P., Robertson, R. L., Bogner, P., Zou, K. H., Guðbjartsson, H., Guttmann, C. R. G., Holtzman, D. H., Kyriakos, W. E., Jolesz, F. A., et al. (2000) · Magnetic Resonance in Medicine · doi:10.1002/1522-2594(200008)44:2 · Cited by 109 · see citing works
Garraux, G., Salmon, E., Degueldre, C., Lemaire, C., Laureys, S., & Franck, G. (1999) · NeuroImage · doi:10.1006/nimg.1999.0463 · Cited by 109 · cited 2× · see citing works
“In vivo cross-sectional 18 FDG-PET studies in normal healthy individuals have consistently shown decreased cerebral glucose metabolism with age, with a differential effect across brain regions, the frontal cortex showing the greatest effects (Moeller et al., 1996; Petit-Taboué et al., 1998; Garraux et al., 1999; Herho…”
BackgroundBastin, C., Yakushev, I. Y., Bahri, M. A., Fellgiebel, A., Eustache, F., Landeau, B., Scheurich, A., Feyers, D., Collette, F., Chételat, G., et al. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.06.074 · Cited by 98 · see citing works
Sundermann, B., & Pfleiderer, B. (2012) · BMC Neuroscience · doi:10.1186/1471-2202-13-119 · Cited by 98 · see citing works
Kochunov, P. V., Ramage, A. E., Lancaster, J. L., Robin, D. A., Narayana, S., Coyle, T. R., Royall, D. R., & Fox, P. T. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.11.010 · Cited by 82 · see citing works
Derrfuß, J., Vogt, V. L., Fiebach, C. J., von Cramon, D. Y., & Tittgemeyer, M. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.11.051 · Cited by 56 · see citing works
White matter integrity and cortical metabolic associations in aging and dementia
Kuczynski, B., Targan, E., Madison, C. M., Weiner, M. W., Zhang, Y., Reed, B., Chui, H. C., & Jagust, W. J. (2010) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2009.04.1228 · Cited by 56 · see citing works
Sex‐ and Age‐Related Differences in Brain FDG Metabolism of Healthy Adults: An SPM Analysis
Hsieh, T., Lin, W., Ding, H., Sun, S., Wu, Y., Yen, K., & Kao, C. (2011) · Journal of Neuroimaging · doi:10.1111/j.1552-6569.2010.00543.x · Cited by 56 · see citing works
A Simple Way to Improve Anatomical Mapping of Functional Brain Imaging
Villain, N., Landeau, B., Groussard, M., Mevel, K., Fouquet, M., Dayan, J., Eustache, F., Desgranges, B., & Chételat, G. (2010) · Journal of Neuroimaging · doi:10.1111/j.1552-6569.2010.00470.x · Cited by 48 · see citing works
Inoue, K., Ito, H., Uchida, S., Taki, Y., Kinomura, S., Tsuji, I., Sato, S., Horie, K., Kawashima, R., Ito, M., et al. (2007) · Human Brain Mapping · doi:10.1002/hbm.20394 · Cited by 21 · see citing works
Age-Related Changes in Frontal and Temporal Lobe Volumes in Men: A Magnetic Resonance Imaging Study
Bartzokis, G., Beckson, M., Lu, P. H., Nuechterlein, K. H., Edwards, N., & Mintz, J. (2001) · Archives of General Psychiatry · doi:10.1001/archpsyc.58.5.461 · Cited by 14 · see citing works
Flagged first, then by citations
1 of the 68 references couldn’t be matched to a known paper.
Research works printed but not linked: 1
- Pfefferbaum A., Sullivan E.V., Hedehus M., Lim K.O., Adalsteinsson E., Moseley M. Age-related decline in brain white matter anisotropy measured with spatially corrected echo-planar diffusion tensor imaging. Magn. Reson. Med. 2000, 44:259-268.
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Swerdlow, R. H., Burns, J. M., & Khan, S. M. (2014) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2013.09.010 · Cited by 786 · see citing works
Estrogen: A master regulator of bioenergetic systems in the brain and body
Rettberg, J. R., Yao, J., & Brinton, R. D. (2014) · Frontiers in Neuroendocrinology · doi:10.1016/j.yfrne.2013.08.001 · Cited by 534 · see citing works
Perez Ortiz, J. M., & Swerdlow, R. H. (2019) · British Journal of Pharmacology · doi:10.1111/bph.14585 · Cited by 426 · see citing works
Gray matter asymmetries in aging and neurodegeneration: a review and meta-analysis.
Minkova, L., Habich, A., Peter, J., Kaller, C. P., Eickhoff, S. B., & Klöppel, S. (2017) · Human Brain Mapping · doi:10.1002/hbm.23772 · Cited by 194 · see citing works
Deery, H. A., Paolo, R. D., Moran, C., Egan, G. F., & Jamadar, S. D. (2022) · Psychophysiology · doi:10.1111/psyp.14159 · Cited by 167 · see citing works
Dídac Vidal-piñeiro, A., eValls-Pedret, C., Fernández‐Cabello, S., Arenaza‐Urquijo, E. M., Sala-Llonch, R., Solana, E., Bargalló, N., Junqué, C., Ros, E., & David Bartrés-faz, A. (2014) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2014.00256 · Cited by 126 · see citing works
Malpetti, M., Ballarini, T., Presotto, L., Garibotto, V., Tettamanti, M., Perani, D., Initiative, A. D. N., & Network for Efficiency and Standardization of Dementia Diagnosis (NEST‐DD) database (2017) · Human Brain Mapping · doi:10.1002/hbm.23659 · Cited by 119 · see citing works
Teipel, S. J., Grothe, M. J., Zhou, J. H., Sepulcre, J., Dyrba, M., Sorg, C., & Babiloni, C. (2016) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617715000995 · Cited by 115 · see citing works
Brain glucose and acetoacetate metabolism: a comparison of young and older adults
Nugent, S., Tremblay, S., Chen, K. W., Ayutyanont, N., Roontiva, A., Castellano, C., Fortier, M., Roy, M., Courchesne‐Loyer, A., Bocti, C., et al. (2013) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2013.11.027 · Cited by 113 · see citing works
Sundermann, B., Beverborg, M. O. L., & Pfleiderer, B. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00692 · Cited by 109 · see citing works
Feng, X., Lipton, Z. C., Yang, J., Small, S. A., & Provenzano, F. A. (2020) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2020.02.009 · Cited by 96 · see citing works
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Grashorn, W., Sprenger, C., Forkmann, K., Wrobel, N., & Bingel, U. (2013) · PLoS ONE · doi:10.1371/journal.pone.0075629 · Cited by 79 · see citing works
Storsve, A. B., Fjell, A. M., Yendiki, A., & Walhovd, K. B. (2016) · PLoS ONE · doi:10.1371/journal.pone.0156770 · Cited by 71 · see citing works
Danka Mohammed, C. P., Park, J. S., Nam, H. G., & Kim, K. (2017) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2017.01.007 · Cited by 68 · see citing works
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Chételat, G., Mézenge, F., Tomadesso, C., Landeau, B., Arenaza‐Urquijo, E. M., Rauchs, G., André, C., de Florès, R., Egret, S., Gonneaud, J., et al. (2017) · Scientific Reports · doi:10.1038/s41598-017-07764-x · Cited by 70 · see citing works
Wang, Y., Mishra, A., & Brinton, R. D. (2020) · F1000Research · doi:10.12688/f1000research.21599.1 · Cited by 63 · see citing works
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Sprecher, K. E., Riedner, B. A., Smith, R., Tononi, G., Davidson, R. J., & Benca, R. M. (2016) · PLoS ONE · doi:10.1371/journal.pone.0149770 · Cited by 57 · see citing works
miR‐204 downregulates EphB2 in aging mouse hippocampal neurons
Mohammed, C. P. D., Rhee, H., Phee, B., Kim, K., Kim, H., Lee, H., Park, J. H., Jung, J. H., Kim, J. Y., Kim, H., et al. (2016) · Aging Cell · doi:10.1111/acel.12444 · Cited by 57 · see citing works
PET imaging of neural activity, β-amyloid, and tau in normal brain aging
Zhang, K., Mizuma, H., Zhang, X., Takahashi, K., Jin, C., Song, F., Gao, Y., Kanayama, Y., Wu, Y., Li, Y., et al. (2021) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-021-05230-5 · Cited by 50 · see citing works
Bioenergetic Dysfunction and Inflammation in Alzheimer’s Disease: A Possible Connection
Wilkins, H., Carl, S. M., Greenlief, A. C. S., Festoff, B. W., & Swerdlow, R. H. (2014) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2014.00311 · Cited by 48 · see citing works
Swerdlow, R. H. (2013) · British Journal of Pharmacology · doi:10.1111/bph.12394 · Cited by 50 · see citing works
Brain regions vulnerable and resistant to aging without Alzheimer’s disease
Feng, X., Guo, J., Sigmon, H. C., Sloan, R. P., Brickman, A. M., Provenzano, F. A., Small, S. A., & Initiative, A. D. N. (2020) · PLoS ONE · doi:10.1371/journal.pone.0234255 · Cited by 48 · see citing works
Buoli, M., Serati, M., Caldiroli, A., Cremaschi, L., & Altamura, A. C. (2017) · Psychiatria Danubina · doi:10.24869/psyd.2017.24 · Cited by 44 · see citing works
Bonte, S., Vandemaele, P., Verleden, S. E., Audenaert, K., Deblaere, K., Goethals, I., & Holen, R. V. (2016) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-016-3569-0 · Cited by 42 · see citing works
Metabolic brain networks in aging and preclinical Alzheimer's disease
Arnemann, K. L., Stöber, F., Narayan, S., Rabinovici, G. D., & Jagust, W. J. (2017) · NeuroImage Clinical · doi:10.1016/j.nicl.2017.12.037 · Cited by 36 · see citing works
Kordestani-Moghadam, P., Assari, S., Nouriyengejeh, S., Mohammadipour, F., & Pourabbasi, A. (2020) · Journal of Obesity & Metabolic Syndrome · doi:10.7570/jomes20021 · Cited by 36 · see citing works
Hshieh, T. T., Dai, W., Cavallari, M., Guttmann, C. R. G., Meier, D., Schmitt, E. M., Dickerson, B. C., Press, D. Z., Marcantonio, E. R., Jones, R. N., et al. (2016) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x16656014 · Cited by 34 · see citing works
Fletcher, E. M., Villeneuve, S., Maillard, P., Harvey, D. J., Reed, B., Jagust, W. J., & DeCarli, C. S. (2016) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2016.01.133 · Cited by 32 · see citing works
Disrupted topology of the resting state structural connectome in middle-aged APOE ε4 carriers
Korthauer, L. E., Zhan, L., Ajilore, O., Leow, A., & Driscoll, I. F. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.05.052 · Cited by 32 · see citing works
Castellano, C., Hudon, C., Croteau, É., Fortier, M., St‐Pierre, V., Vandenberghe, C., Nugent, S., Tremblay, S., Paquet, N., Lepage, M., et al. (2019) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2019.00015 · Cited by 32 · see citing works
Alteration of Copper Fluxes in Brain Aging: A Longitudinal Study in Rodent Using 64CuCl2-PET/CT
Peng, F., Xie, F., & Muzik, O. (2018) · Aging and Disease · doi:10.14336/ad.2017.1025 · Cited by 30 · see citing works
Visser, M., O’Brien, J. T., & Mak, E. (2024) · Ageing Research Reviews · doi:10.1016/j.arr.2024.102197 · Cited by 28 · see citing works
Age and Vascular Burden Determinants of Cortical Hemodynamics Underlying Verbal Fluency
Heinzel, S., Metzger, F. G., Ehlis, A., Korell, R., Alboji, A., Haeussinger, F. B., Wurster, I., Brockmann, K., Suenkel, U., Eschweiler, G. W., et al. (2015) · PLoS ONE · doi:10.1371/journal.pone.0138863 · Cited by 29 · see citing works
Saccadic eye movements: what do they tell us about aging cognition?
Noiret, N., Vigneron, B., Diogo, M., Vandel, P., & Laurent, É. (2016) · Aging Neuropsychology and Cognition · doi:10.1080/13825585.2016.1237613 · Cited by 27 · see citing works
Jiang, J., Sun, Y., Zhou, H., Li, S., Huang, Z., Wu, P., Shi, K., Zuo, C., & Initiative, A. D. N. (2018) · Contrast Media & Molecular Imaging · doi:10.1155/2018/3786083 · Cited by 27 · see citing works
Brain Networks Reorganization During Maturation and Healthy Aging-Emphases for Resilience
González‐Escamilla, G., Muthuraman, M., Chirumamilla, V. C., Vogt, J., & Groppa, S. (2018) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2018.00601 · Cited by 26 · see citing works
Healthy brain aging assessed with [18F]FDG and [11C]UCB-J PET
Andersen, K. B., Hansen, A. K., Knudsen, K., Schacht, A. C., Damholdt, M. F., Brooks, D. J., & Borghammer, P. (2022) · Nuclear Medicine and Biology · doi:10.1016/j.nucmedbio.2022.06.007 · Cited by 25 · see citing works
Bi, Q., Wang, W., Niu, N., Li, H., Wang, Y., Huang, W., Chen, K., Xu, K., Zhang, J., Chen, Y., et al. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117591 · Cited by 22 · see citing works
FDG PET and cognitive symptoms of dementia
Perani, D. (2013) · Clinical and Translational Imaging · doi:10.1007/s40336-013-0029-8 · Cited by 21 · see citing works
Nugent, S., Castellano, C., Bocti, C., Dionne, I. J., Fülöp, T., & Cunnane, S. C. (2015) · Biogerontology · doi:10.1007/s10522-015-9595-7 · Cited by 20 · see citing works
Metabolic Connectivity as Index of Verbal Working Memory
Zou, N., Chételat, G., Baydoğan, M. G., Li, J., Fischer, F. U., Titov, D., Dukart, J., Fellgiebel, A., Schreckenberger, M., & Yakushev, I. Y. (2015) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1038/jcbfm.2015.40 · Cited by 20 · see citing works
van Aalst, J., Devrome, M., Weehaeghe, D. V., Rezaei, A., Radwan, A., Schramm, G., Ceccarini, J., Sunaert, S. G., Koole, M. J. B., & Laere, K. V. (2021) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-021-05518-6 · Cited by 19 · see citing works
Meditation and the Brain in Health and Disease
Fox, K. C. R., & Cahn, B. R. (2020) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780198808640.013.23 · Cited by 16 · see citing works
Fortel, I., Butler, M. P., Korthauer, L. E., Zhan, L., Ajilore, O., Sidiropoulos, A., Wu, Y., Driscoll, I. F., Schonfeld, D., & Leow, A. (2021) · Network Neuroscience · doi:10.1162/netn_a_00220 · Cited by 16 · see citing works
Striatofrontal Deafferentiation in MSA-P: Evaluation with [18F]FDG Brain PET
Kim, H. W., Oh, M., Oh, J. S., Oh, S. J., Lee, S. J., Chung, S. J., & Kim, J. S. (2017) · PLoS ONE · doi:10.1371/journal.pone.0169928 · Cited by 16 · see citing works
Bakhtiari, A., Benedek, K., Law, I. G., Fagerlund, B., Mortensen, E. L., Osler, M., Lauritzen, M., Larsson, H. B. W., & Vestergaard, M. B. (2023) · GeroScience · doi:10.1007/s11357-023-01031-w · Cited by 15 · see citing works
Jiang, D., Lu, X., Li, Z., Rydberg, N., Zuo, C., Peng, F., Hua, F., Guan, Y., & Xie, F. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.01052 · Cited by 15 · see citing works
Firbank, M., Lloyd, J. J., Williams, D., Barber, R., Colloby, S. J., Barnett, N. A., Olsen, K., Davison, C. M., Donaldson, C., Herholz, K., et al. (2015) · The British Journal of Psychiatry · doi:10.1192/bjp.bp.114.160804 · Cited by 15 · see citing works
Oosterwijck, S. V., Meeus, M., van der Wekken, J., Dhondt, E., Billens, A., & Oosterwijck, J. V. (2024) · Journal of Pain · doi:10.1016/j.jpain.2024.104639 · Cited by 14 · see citing works
Kavroulakis, E., Simos, N. J., Maris, T. G., Zaganas, I. V., Panagiotakis, S., & Papadaki, E. Z. (2021) · Frontiers in Neurology · doi:10.3389/fneur.2021.633500 · Cited by 14 · see citing works
Jiang, J., Sheng, C., Chen, G., Liu, C., Jin, S., Li, L., Jiang, X., Han, Y., Initiative, A. D. N., Weiner, M. W., et al. (2022) · GeroScience · doi:10.1007/s11357-022-00588-2 · Cited by 14 · see citing works
Ferré, P., Benhajali, Y., Steffener, J., Stern, Y., Joanette, Y., & Bellec, P. (2019) · Language Cognition and Neuroscience · doi:10.1080/23273798.2019.1608072 · Cited by 14 · see citing works
Observation of Reduced Homeostatic Metabolic Activity and/or Coupling in White Matter Aging
Anderson, V. C., Tagge, I., Li, X., Quinn, J. F., Kaye, J. A., BOURDETTE, D. N., Spain, R., Riccelli, L. P., Sammi, M. K., SPRINGER, C. S. J., et al. (2020) · Journal of Neuroimaging · doi:10.1111/jon.12744 · Cited by 13 · see citing works
Meditation and the brain in health and diseasePreprint
Fox, K. C. R., & Cahn, B. R. (2018) · doi:10.31231/osf.io/m2sez · Cited by 13 · see citing works
García-San-Martín, N., Bethlehem, R. A. I., Segura, P., Mihalik, Á., Seidlitz, J., Sebenius, I., Alemán-Morillo, C., Dorfschmidt, L., Shafiei, G., Morgan, S. E., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-63792-6 · Cited by 12 · see citing works
Planning in amnestic mild cognitive impairment: an fMRI study
Lejko, N., Tumati, S., Opmeer, E. M., Marsman, J.-B. C., Reesink, F. E., Deyn, P. P. D., Aleman, A., & Ćurĉić‐Blake, B. (2021) · Experimental Gerontology · doi:10.1016/j.exger.2021.111673 · Cited by 12 · see citing works
Lao, Y., Nguyen, B., Tsao, S., Gajawelli, N., Law, M., Chui, H. C., Weiner, M. W., Wang, Y., & Leporé, N. (2016) · NeuroImage Clinical · doi:10.1016/j.nicl.2016.12.027 · Cited by 10 · see citing works
Effects of a Health Education program on cognition, mood and functional capacity
Dias, J. C., Rodrigues, I. A., Casemiro, F. G., Monteiro, D. Q., Luchesi, B. M., Chagas, M. H. N., Castro, P. C., Pavarini, S. C. I., & Gratão, A. C. M. (2017) · Revista Brasileira de Enfermagem · doi:10.1590/0034-7167-2016-0638 · Cited by 10 · see citing works
Xu, K., Niu, N., Li, X., Chen, Y., Wang, D., Zhang, J., Chen, Y., Li, H., Wei, D., Chen, K., et al. (2022) · Cerebral Cortex · doi:10.1093/cercor/bhac248 · Cited by 9 · see citing works
Heiss, W. (2014) · Springer eBooks · doi:10.1007/978-3-642-42014-6_3 · Cited by 9 · see citing works
Network Occlusion Sensitivity Analysis Identifies Regional Contributions to Brain Age Prediction
He, L., Wang, S., Chen, C., Wang, Y., Fan, Q., Chu, C., Fan, L., & Xu, J. (2025) · Human Brain Mapping · doi:10.1002/hbm.70239 · Cited by 8 · see citing works
Personality-Related Determinants of Subtle Cognitive Decline in Old Age: A Population-Based Study
Rodriguez, C. K., Albanese, E., Pegna, A. J., Toma, S., Ackermann, M., Tombeur, E., Herrmann, F. R., & Giannakopoulos, P. (2016) · Dementia and Geriatric Cognitive Disorders Extra · doi:10.1159/000441388 · Cited by 8 · see citing works
Bauckneht, M., Chincarini, A., Brendel, M., Rominger, A., Beyer, L., Bruffaerts, R., Vandenberghe, R. R., Kramberger, M. G., Trošt, M., Garibotto, V., et al. (2021) · Alzheimer s & Dementia · doi:10.1002/alz.12294 · Cited by 7 · see citing works
Aging-Related Modular Architectural Reorganization of the Metabolic Brain Network
Huang, Q., Ren, S., Zhang, T., Li, J., Jiang, D., Xiao, J., Hua, F., Xie, F., & Guan, Y. (2021) · Brain Connectivity · doi:10.1089/brain.2021.0054 · Cited by 7 · see citing works
Imaging Clinical Subtypes and Associated Brain Networks in Alzheimer’s Disease
Herholz, K. (2022) · Brain Sciences · doi:10.3390/brainsci12020146 · Cited by 7 · see citing works
Neuroactive Phytoconstituents of Glycyrrhiza glabra for the Treatment of Alzheimer’s Disease
Verma, M., Usman, M., & Singh, N. K. (2024) · Current Topics in Medicinal Chemistry · doi:10.2174/0115680266357793241223100307 · Cited by 7 · see citing works
Mayorga-Weber, G. A., Alarcón, P., Peña-Münzenmayer, G., Rojas, P., Burgos, R. A., Rivera, F. J., & Castro, M. A. (2025) · Free Radical Biology and Medicine · doi:10.1016/j.freeradbiomed.2025.06.044 · Cited by 6 · see citing works
A review of epigenetics in human consciousness
Liester, M. B., & Sullivan, E. E. (2019) · Cogent Psychology · doi:10.1080/23311908.2019.1668222 · Cited by 6 · see citing works
Sundermann, B., Beverborg, M. O. L., & Pfleiderer, B. (2014) · doi:10.7287/peerj.preprints.412v1 · Cited by 7 · see citing works
Tomadesso, C., de Lizarrondo, S. M., Ali, C., Landeau, B., Mézenge, F., Perrotin, A., Sayette, V. D. L., Vivien, D., & Chételat, G. (2022) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2022.871214 · Cited by 5 · see citing works
Zuo, Q., Lei, B., Qiu, W., Jing, C., Hong, J., & Wang, S. (2026) · IEEE Transactions on Consumer Electronics · doi:10.1109/tce.2026.3677325 · Cited by 5 · see citing works
Estimating brain age based on a healthy population with deep learning and structural MRIPreprint
Feng, X., Lipton, Z. C., Yang, J., Small, S. A., & Provenzano, F. A. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1907.00943 · Cited by 5 · see citing works
Tristão‐Pereira, C., Langella, S., Baena, A. Y., Londono, N., Sanchez, J. S., Martinez, L., Álvarez, S., Vidal, M., Aguillon, D. F., Su, Y., et al. (2025) · Brain Communications · doi:10.1093/braincomms/fcaf508 · Cited by 5 · see citing works
The microRNA-mediated gene regulatory network in the hippocampus and hypothalamus of the aging mouse
Munkhzul, C., Yi, S. S., Kim, J., Lee, S., Kim, H.-T., Moon, J., & Lee, M. (2023) · PLoS ONE · doi:10.1371/journal.pone.0291943 · Cited by 4 · see citing works
Bachmann, S., Beck, M., Tsai, D.-H., & Haupt, F. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.670539 · Cited by 4 · see citing works
Woyk, K., Hansen, N., Wiltfang, J., Lange, C., & Bouter, C. (2025) · Journal of Alzheimer s Disease Reports · doi:10.1177/25424823251314392 · Cited by 3 · see citing works
Structural and Functional Magnetic Resonance Imaging
Lockau, H., Jessen, F., Fellgiebel, A., & Drzezga, A. E. (2013) · PET Clinics · doi:10.1016/j.cpet.2013.08.004 · Cited by 2 · see citing works
Heiss, W., & Zaro‐Weber, O. (2020) · Springer eBooks · doi:10.1007/978-3-030-53176-8_4 · Cited by 2 · see citing works
Moezzi, B., Lavrencic, L. M., Goldsworthy, M. R., Coussens, S. W., & Keage, H. A. D. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/625608 · Cited by 2 · see citing works
Diet-mediated bioenergetic flux: a double-edged sword for health and diseases
Nasb, M., Luo, A., Dayoub, L., Wang, M., & Chen, N. (2025) · Food Science and Human Wellness · doi:10.26599/fshw.2025.9250724 · Cited by 2 · see citing works
Difference between Okinawan and Dutch older adults in prefrontal brain activation
Ćurĉić‐Blake, B., Futenma, Y., Willcox, D. C., Tazangi, P. E., Wardana, N. D., Ueda, Y., & Aleman, A. (2025) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2025.1454068 · Cited by 1 · see citing works
Brain functional connectivity in regions that exhibit age-related cortical thinning
Vieira, B. H. (2018) · doi:10.11606/d.59.2018.tde-17042018-130342 · Cited by 1 · see citing works
García-San-Martín, N., Bethlehem, R. A. I., Segura, P., Mihalik, Á., Seidlitz, J., Sebenius, I., Alemán-Morillo, C., Dorfschmidt, L., Shafiei, G., Morgan, S. E., et al. (2024) · medRxiv · doi:10.1101/2024.11.25.24317878 · Cited by 1 · see citing works
Deery, H. A., Paolo, R. D., Moran, C., Egan, G. F., & Jamadar, S. D. (2021) · doi:10.31234/osf.io/3n5td
Ferré, P., Benhajali, Y., Steffener, J., Stern, Y., Joanette, Y., & Bellec, P. (2019) · doi:10.31234/osf.io/n239v
Tomadesso, C. (2018) · theses.fr (ABES) · doi:10.70675/7fad6418zff81z49c7z984dz63aa2e44d7fc
Optical development to image brain activity at extreme depth
Suarez-Baquero, D. E. (2024) · theses.fr (ABES) · doi:10.70675/b2f8ef6ezf2b3z43edzb579z3f1b4da5b767
Chemoarchitectural influences on the cortical connectome confer resilience in agingPreprint
Flores-Alonso, S. I., Solomon, J. P., Dobri, S. G. J., McIntosh, A. R., & Wiesman, A. I. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.04.23.719924
- Authors
- Chételat, G., Landeau, B., Salmon, E., Yakushev, I., Bahri, M. A., Mézenge, F., Perrotin, A., Bastin, C., Manrique, A., Scheurich, A., Scheckenberger, M., Desgranges, B., Eustache, F., & Fellgiebel, A.
- Affiliations
- Inserm (FR)
- University Medical Center of the Johannes Gutenberg University Mainz (DE)
- University of Liège (BE)
- Centre Hospitalier Universitaire de Caen Normandie (FR)
- Corresponding author
- Chételat, Gaël
- ORCID
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2013-08
- Volume
- 76
- Pages
- 167-177
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2072418095
- Cited by
- 92
- References
- 68
- Citations by year
- 2026: 2 · 2025: 7 · 2024: 5 · 2023: 2 · 2022: 6 · 2021: 10 · 2020: 9 · 2019: 9 · 2018: 7 · 2017: 8 · 2016: 10 · 2015: 4 · 2014: 5 · 2013: 8
- FWCI
- 4.92
- Type
- journal article
- Language
- en
- Open access
- green
- inserm.hal.science
- Licence
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- HAL (submittedVersion, other-oa)
- mediaTUM (Technical University of Munich) (submittedVersion)
- ORBi (University of Liège) (submittedVersion, other-oa)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Keywords
- normal aging, brain glucose metabolism, white matter integrity, fractional anisotropy, functional connectivity, structural connectivity, inferior frontal junction, resting-state fMRI, FDG-PET, diffusion tensor imaging
- MeSH terms
- Adult, Aged, Aged, 80 and over, Aging, Brain, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Neural Pathways, Positron-Emission Tomography, Young Adult
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