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Distinct patterns of brain activity in young carriers of the APOE -ε4 allele
Open accessAbstract
The APOE ε4 allele is a risk factor for late-life pathological changes that is also associated with anatomical and functional brain changes in middle-aged and elderly healthy subjects. We investigated structural and functional effects of the APOE polymorphism in 18 young healthy APOE ε4-carriers and 18 matched noncarriers (age range: 20–35 years). Brain activity was studied both at rest and during an encoding memory paradigm using blood oxygen level-dependent fMRI. Resting fMRI revealed increased “default mode network” (involving retrosplenial, medial temporal, and medial-prefrontal cortical areas) coactivation in ε4-carriers relative to noncarriers. The encoding task produced greater hippocampal activation in ε4-carriers relative to noncarriers. Neither result could be explained by differences in memory performance, brain morphology, or resting cerebral blood flow. The APOE ε4 allele modulates brain function decades before any clinical or neurophysiological expression of neurodegenerative processes.
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“However, previous studies have already linked APOE4 to increased (hyper-)metabolism in young individuals.”
From APOE4 Increases Energy Metabolism in APOE-Isogenic iPSC-Derived Neurons (2024) · cites this paper as [45]
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“Studies in young adults, before the onset of a pathology, showed that APOE4 carriers display hypermetabolism and hyperactivity in distinct brain regions, such as the hippocampus, entorhinal cortex, and cortical regions [44,45,46].”
From APOE4 Increases Energy Metabolism in APOE-Isogenic iPSC-Derived Neurons (2024) · cites this paper as [45]
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In the citing paper
“Young ApoE4 carriers showed increased brain activity in default network regions, as well as in the hippocampus and the temporal lobe, possibly due to increased aerobic glycolysis.34”
From ApoE4-dependent lysosomal cholesterol accumulation impairs mitochondrial homeostasis and oxidative phosphorylation in human astrocytes (2023) · cites this paper as [35]
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“Interestingly, several studies in young APOE4 carriers or in APOE4-knock-in mice with no apparent neurodegenerative pathology, revealed increased brain metabolism and activity (Filippini et al., 2009; Evans et al., 2017; Nuriel et al., 2017; Venzi et al., 2017), indicating that the APOE4 effect on brain energy metabolism may differ depending on the degree of pathology.”
From APOE genotype-dependent differences in human astrocytic energy metabolism (2025) · cites this paper as Filippini et al., 2009
In the citing paper
“Dual regression is a reliable technique which allows for the identification of group differences in the spatial and temporal features of ICNs common to the entire sample (Filippini et al., 2009; Zuo et al., 2010).”
From Investigating functional brain network integrity using a traditional and novel categorical scheme for neurodevelopmental disorders (2019) · cites this paper as Filippini et al., 2009
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“Healthy young and middle-aged adult apoE4 carriers show increased DMN activation at rest [179]”
From Apolipoprotein E4, inhibitory network dysfunction, and Alzheimer’s disease (2019) · cites this paper as [179]
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“and increased hippocampal activation during encoding task performance [179–181]”
From Apolipoprotein E4, inhibitory network dysfunction, and Alzheimer’s disease (2019) · cites this paper as [179]
In the citing paper
“Network hyperactivity is an overarching symptom of AD and is evident in human apoE4 carriers.”
From Apolipoprotein E4, inhibitory network dysfunction, and Alzheimer’s disease (2019) · cites this paper as [179]
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Cites
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
A synaptic model of memory: long-term potentiation in the hippocampus
Bliss, T. V. P., & Collingridge, G. L. (1993) · Nature · doi:10.1038/361031a0 · Cited by 11,566
Nonparametric permutation tests for functional neuroimaging: A primer with examples
Nichols, T. E., & Holmes, A. P. (2002) · Human Brain Mapping · doi:10.1002/hbm.1058 · Cited by 6,256
Apolipoprotein E: Cholesterol Transport Protein with Expanding Role in Cell Biology
Mahley, R. W. (1988) · Science · doi:10.1126/science.3283935 · Cited by 4,028
Greicius, M. D., Srivastava, G., Reiss, A. L., & Menon, V. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0308627101 · Cited by 3,684
Investigations into resting-state connectivity using independent component analysis
Beckmann, C. F., DeLuca, M., Devlin, J. T., & Smith, S. M. (2005) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2005.1634 · Cited by 3,398
Self-citationThe Medial Temporal Lobe Memory System
Squire, L. R., & Zola-Morgan, S. (1991) · Science · doi:10.1126/science.1896849 · Cited by 3,282
Buckner, R. L., Snyder, A. Z., Shannon, B. J., LaRossa, G., Sachs, R., Fotenos, A. F., Sheline, Y. I., Klunk, W. E., Mathis, C. A., Morris, J. C., et al. (2005) · The Journal of Neuroscience · doi:10.1523/jneurosci.2177-05.2005 · Cited by 2,140
Apolipoprotein E: Far More Than a Lipid Transport Protein
Mahley, R. W., & Rall, S. C. (2000) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev.genom.1.1.507 · Cited by 1,836
Multilevel linear modelling for FMRI group analysis using Bayesian inference
Woolrich, M. W., Behrens, T. E. J., Beckmann, C. F., Jenkinson, M., & Smith, S. M. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2003.12.023 · Cited by 1,719
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Ovadia‐Caro, S., Villringer, K., Fiebach, J. B., Jungehulsing, G. J., van der Meer, E. E., Margulies, D. S., & Villringer, A. (2013) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1038/jcbfm.2013.80 · Cited by 83
Clinical Concepts Emerging from fMRI Functional Connectomics
Matthews, P. M., & Hampshire, A. (2016) · Neuron · doi:10.1016/j.neuron.2016.07.031 · Cited by 83
Self-citationQureshi, M. N. I., Oh, J., Cho, D., Jo, H. J., & Lee, B. (2017) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2017.00059 · Cited by 83
Gray matter atrophy patterns in multiple sclerosis: A 10-year source-based morphometry study
Bergsland, N., Horáková, D., Dwyer, M. G., Uher, T., Vaněčková, M., Týblová, M., Seidl, Z., Krásenský, J., Havrdová, E., & Zivadinov, R. (2017) · NeuroImage Clinical · doi:10.1016/j.nicl.2017.11.002 · Cited by 83
Resting state activity in patients with disorders of consciousness.
Soddu, A., Vanhaudenhuyse, A., Athena Demertzi, A., Bruno, M., Tshibanda, L., Di, H., Mélanie, B., Papa, M., Laureys, S., & Noirhomme, Q. (2011) · Europe PMC (PubMed Central) · Cited by 82
Xu, Y., & Lindquist, M. A. (2015) · Frontiers in Neuroscience · doi:10.3389/fnins.2015.00285 · Cited by 82
Resting-State Functional Connectivity Changes in Aging apoE4 and apoE-KO Mice
Zerbi, V., Wiesmann, M., Emmerzaal, T. L., Jansen, D., Beek, M. V., Mutsaers, M. P. C., Beckmann, C. F., Heerschap, A., & Kiliaan, A. J. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.0684-14.2014 · Cited by 82
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Filippini, N., Zsoldos, E., Haapakoski, R., Sexton, C. E., Mahmood, A., Allan, C. L., Topiwala, A., Valkanova, V., Brunner, E. J., Shipley, M. J., et al. (2014) · BMC Psychiatry · doi:10.1186/1471-244x-14-159 · Cited by 82
Self-citationZerbi, V., Ielacqua, G. D., Markicevic, M., Haberl, M. G., Ellisman, M. H., A-Bhaskaran, A., Frick, A., Rudin, M., & Wenderoth, N. (2018) · Cerebral Cortex · doi:10.1093/cercor/bhy046 · Cited by 81
Johnen, V. M., Neubert, F.-X., Buch, E. R., Verhagen, L., O’Reilly, J. X., Mars, R. B., & Rushworth, M. F. S. (2015) · eLife · doi:10.7554/elife.04585 · Cited by 82
Castellazzi, G., Palesi, F., Casali, S., Vitali, P., Sinforiani, E., Wheeler‐Kingshott, C. A. M. G., & D'Angelo, E. U. (2014) · Frontiers in Neuroscience · doi:10.3389/fnins.2014.00223 · Cited by 81
Staging Alzheimer's disease progression with multimodality neuroimaging
Ewers, M., Frisoni, G. B., Teipel, S. J., Grinberg, L. T., Amaro, E., Heinsen, H., Thompson, P. M., & Hampel, H. J. (2011) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2011.06.004 · Cited by 81
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Hunt, L. T., Behrens, T. E. J., Hosokawa, T., Wallis, J. D., & Kennerley, S. W. (2015) · eLife · doi:10.7554/elife.11945 · Cited by 81
Shetty, A. K., & Bates, A. A. (2015) · Brain Research · doi:10.1016/j.brainres.2015.09.019 · Cited by 80
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Serra, L., Cercignani, M., Mastropasqua, C., Torso, M., Spanò, B., Makovac, E., Viola, V., Giulietti, G., Marra, C., Caltagirone, C., et al. (2016) · Journal of Alzheimer s Disease · doi:10.3233/jad-150961 · Cited by 80
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Verstraete, E., Turner, M. R., Großkreutz, J., Filippi, M., Benatar, M. G., & meeting, O. B. O. T. A. O. T. 4. N. (2015) · Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration · doi:10.3109/21678421.2015.1051989 · Cited by 80
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Yassine, H. N., Croteau, É., Rawat, V., Hibbeln, J. R., Rapoport, S. I., Cunnane, S. C., & Umhau, J. C. (2017) · Alzheimer s Research & Therapy · doi:10.1186/s13195-017-0250-1 · Cited by 80
Klaassens, B. L., van Gerven, J., van der Grond, J., de Vos, F., Möller, C., & Rombouts, S. A. R. B. (2017) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2017.00097 · Cited by 80
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Honea, R. A., Initiative, F. T. A. D. N., Vidoni, E. D., Swerdlow, R. H., & Burns, J. M. (2012) · Journal of Alzheimer s Disease · doi:10.3233/jad-2012-120676 · Cited by 79
Tong, Y., Hocke, L. M., Nickerson, L. D. H., Licata, S. C., Lindsey, K. P., & Frederick, B. B. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.03.019 · Cited by 79
Parkinson's disease-related network topographies characterized with resting state functional MRI
Vo, A., Sako, W., Fujita, K., Peng, S., Mattis, P. J., Skidmore, F. M., Ma, Y., Uluğ, A. M., & Eidelberg, D. (2016) · Human Brain Mapping · doi:10.1002/hbm.23260 · Cited by 79
Islet amyloid polypeptide: Another key molecule in Alzheimer’s pathogenesis?
Zhang, Y., & Song, W. (2017) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2017.03.001 · Cited by 79
Tavazzi, E., Bergsland, N., Cattaneo, D., Gervasoni, E., Laganà, M. M., Dipasquale, O., Grosso, C., Saibene, F. L., Baglio, F., & Rovaris, M. (2018) · Journal of Neurology · doi:10.1007/s00415-018-8859-y · Cited by 79
APOE ε4 carriers share immune-related proteomic changes across neurodegenerative diseases
Shvetcov, A., Johnson, E. C. B., Winchester, L. M., Walker, K. A., Wilkins, H. M., Thompson, T. G., Rothstein, J. D., Krish, V., Imam, F. B., The Global Neurodegeneration Proteomics Consortium (GNPC), et al. (2025) · Nature Medicine · doi:10.1038/s41591-025-03835-z · Cited by 78
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Li, R., Utevsky, A. V., Huettel, S. A., Braams, B. R., Peters, S., Crone, E. A., & van Duijvenvoorde, A. C. K. (2019) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01426 · Cited by 78
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Donix, M., Small, G. W., & Bookheimer, S. Y. (2012) · Neuropsychology Review · doi:10.1007/s11065-012-9193-2 · Cited by 78
Zhan, Y., Initiative, A. D. N., Ma, J., Alexander‐Bloch, A. F., Xu, K., Cui, Y. J., Feng, Q., Jiang, T., & Liu, Y. (2016) · Journal of Alzheimer s Disease · doi:10.3233/jad-160008 · Cited by 78
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de Haan, W., van Straaten, E. C. W., Gouw, A. A., & Stam, C. J. (2017) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005707 · Cited by 78
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Sohn, W. S., Yoo, K., Lee, Y., Seo, S. W., Na, D. L., & Jeong, Y. (2015) · Frontiers in Neuroscience · doi:10.3389/fnins.2015.00280 · Cited by 77
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Blautzik, J., Vetter, C., Peres, I., Gutyrchik, E., Keeser, D., Berman, A., Kirsch, V., Mueller, S., Pöppel, E., Reiser, M. F., et al. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.08.010 · Cited by 77
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Single-dose serotonergic stimulation shows widespread effects on functional brain connectivity
Klaassens, B. L., van Gorsel, H. C., Khalili-Mahani, N., van der Grond, J., Wyman, B. T., Whitcher, B., Rombouts, S. A. R. B., & van Gerven, J. M. A. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.08.012 · Cited by 76
Krafft, C. E., Pierce, J. E., Schwarz, N. F., Chi, L., Weinberger, A. L., Schaeffer, D. J., Rodrigue, A., Camchong, J., Allison, J., Yanasak, N. E., et al. (2013) · Neuroscience · doi:10.1016/j.neuroscience.2013.09.052 · Cited by 77
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Monroe, T. B., Gore, J. C., Chen, L. M., Mion, L. C., & Cowan, R. L. (2012) · Journal of Geriatric Psychiatry and Neurology · doi:10.1177/0891988712466457 · Cited by 76
Verfaillie, S. C. J., Binette, A. P., Vachon‐Presseau, É., Tabrizi, S., Savard, M., Bellec, P., Ossenkoppele, R., Scheltens, P., van der Flier, W. M., Breitner, J. C. S., et al. (2017) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2017.11.012 · Cited by 76
Iwabuchi, S. J., Auer, D. P., Lankappa, S. T., & Palaniyappan, L. K. (2019) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2019.02.012 · Cited by 76
Starck, T., Nikkinen, J., Rahko, J., Remes, J., Hurtig, T., Haapsamo, H., Jussila, K., Kuusikko-Gauffin, S., Mattila, M.-L., Jansson-Verkasalo, E., et al. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00802 · Cited by 75
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Acevedo, S. F., Piper, B. J., Craytor, M. J., Benice, T. S., & Raber, J. (2010) · Pediatric Research · doi:10.1203/pdr.0b013e3181cb8e68 · Cited by 75
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O’Neill, G. C., Bauer, M., Woolrich, M. W., Morris, P. G., Barnes, G. R., & Brookes, M. J. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.04.030 · Cited by 75
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Korgaonkar, M. S., Ram, K., Williams, L. M., Gatt, J. M., & Grieve, S. M. (2014) · Human Brain Mapping · doi:10.1002/hbm.22446 · Cited by 74
Rytty, R., Nikkinen, J., Paavola, L. E., Elseoud, A. A., Moilanen, V., Visuri, A., Tervonen, O. A., Renton, A. E., Traynor, B. J., Kiviniemi, V. J., et al. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00461 · Cited by 74
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Bijsterbosch, J. D., Beckmann, C. F., Woolrich, M. W., Smith, S. M., & Harrison, S. J. (2019) · eLife · doi:10.7554/elife.44890 · Cited by 72
Self-citationDipasquale, O., Selvaggi, P., Veronese, M., Gabay, A. S., Turkheimer, F., & Mehta, M. A. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.04.007 · Cited by 71
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Mowinckel, A. M., Alnæs, D., Pedersen, M. L., Ziegler, S., Fredriksen, M., Kaufmann, T., Sonuga-Barke, E. J. S., Endestad, T., Westlye, L. T., & Biele, G. (2017) · NeuroImage Clinical · doi:10.1016/j.nicl.2017.03.008 · Cited by 71
Dacosta‐Aguayo, R., Graña, M., Savio, A. M., Fernández‐Andújar, M., Millán, M., Elena López-Cancio, M., Cáceres, C. M., Bargalló, N., Garrido, C., Barrios, M., et al. (2014) · Human Brain Mapping · doi:10.1002/hbm.22439 · Cited by 70
Kariv-Inbal, Z., Yacobson, S., Berkecz, R., Péter, M., Janáky, T., Lütjohann, D., Broersen, L. M., Hartmann, T., & Michaelson, D. M. (2012) · Journal of Alzheimer s Disease · doi:10.3233/jad-2011-111265 · Cited by 70
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Wang, L. Y., Roe, C. M., Snyder, A. Z., Brier, M. R., Thomas, J., Xiong, C., Benzinger, T. L. S., Morris, J. C., & Ances, B. M. (2012) · Annals of Neurology · doi:10.1002/ana.23643 · Cited by 70
Dídac Vidal-piñeiro, A., Martín-Trias, P., Arenaza‐Urquijo, E. M., Sala‐Llonch, R., Clemente, I. C., Mena-Sánchez, I., Bargalló, N., Falcón, C., Pascual‐Leone, Á., & Bartrés‐Faz, D. (2014) · Brain stimulation · doi:10.1016/j.brs.2013.12.016 · Cited by 70
Executive control network connectivity strength protects against relapse to cocaine use
McHugh, M. J., Gu, H., Yang, Y., Adinoff, B. H., & Stein, E. A. (2016) · Addiction Biology · doi:10.1111/adb.12448 · Cited by 70
Alerted default mode: functional connectivity changes in the aftermath of social stress
Clemens, B., Wagels, L., Bauchmüller, M., Bergs, R., Habel, U., & Kohn, N. (2017) · Scientific Reports · doi:10.1038/srep40180 · Cited by 70
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Jimenez, A. M., Riedel, P., Lee, J., Reavis, E. A., & Green, M. F. (2019) · Human Brain Mapping · doi:10.1002/hbm.24731 · Cited by 70
Exploring connectivity with large-scale Granger causality on resting-state functional MRI
DSouza, A. M., Abidin, A. Z., Leistritz, L., & Wismüller, A. (2017) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2017.06.007 · Cited by 69
Fasting plasma insulin and the default mode network in women at risk for Alzheimer's disease
Kenna, H. A., Hoeft, F., Kelley, R. G., Wroolie, T., DeMuth, B. N., Reiss, A. L., & Rasgon, N. (2012) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2012.06.006 · Cited by 69
Resting‐State Functional Brain Networks in Parkinson's Disease
Baggio, H. C., Segura, B., & Junqué, C. (2015) · CNS Neuroscience & Therapeutics · doi:10.1111/cns.12417 · Cited by 69
Novel MRI Approaches for Assessing Cerebral Hemodynamics in Ischemic Cerebrovascular Disease
Donahue, M. J., Strother, M. K., & Hendrikse, J. (2012) · Stroke · doi:10.1161/strokeaha.111.635995 · Cited by 69
Resting connectivity predicts task activation in pre-surgical populations
Jones, Ō. P., Voets, N., Adcock, J., Stacey, R. J., & Jbabdi, S. (2016) · NeuroImage Clinical · doi:10.1016/j.nicl.2016.12.028 · Cited by 69
Modulation of Long-Range Connectivity Patterns via Frequency-Specific Stimulation of Human Cortex
Weinrich, C. A., Brittain, J., Nowak, M., Salimi-Khorshidi, R., Brown, P., & Stagg, C. J. (2017) · Current Biology · doi:10.1016/j.cub.2017.08.075 · Cited by 69
Cole, D. M., Beckmann, C. F., Searle, G. E., Plisson, C., Tziortzi, A. C., Nichols, T. E., Gunn, R. N., Matthews, P. M., Rabiner, E. A., & Beaver, J. D. (2011) · Cerebral Cortex · doi:10.1093/cercor/bhr354 · Cited by 68
Self-citationRokicki, J., Li, L. M., Imabayashi, E., Kaneko, J., Hisatsune, T., & Matsuda, H. (2015) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2015.00219 · Cited by 68
Nashiro, K., Sakaki, M., Braskie, M. N., & Mather, M. (2017) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2017.03.003 · Cited by 68
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de Schipper, L. J., Hafkemeijer, A., van der Grond, J., Marinus, J., Henselmans, J. M. L., & van Hilten, J. J. (2018) · Frontiers in Neurology · doi:10.3389/fneur.2018.00419 · Cited by 68
Changes in resting‐state functionally connected parietofrontal networks after videogame practice
Martínez, K., Solana, A. B., Burgaleta, M., Hernandez-Tamames, J. A., Álvarez‐Linera, J., Román, F. J., Alfayate, E., Privado, J., Escorial, S., Quiroga, M. Á., et al. (2012) · Human Brain Mapping · doi:10.1002/hbm.22129 · Cited by 68
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Zamboni, G., Wilcock, G. K., Douaud, G., Drazich, E., McCulloch, E., Filippini, N., Tracey, I., Brooks, J. C. W., Smith, S. M., Jenkinson, M., et al. (2013) · Biological Psychiatry · doi:10.1016/j.biopsych.2013.04.015 · Cited by 67
Self-citationGordon, E. M., Stollstorff, M., & Vaidya, C. J. (2011) · Human Brain Mapping · doi:10.1002/hbm.21306 · Cited by 67
Wandschneider, B., Centeno, M., Vollmar, C., Symms, M. R., Thompson, P. J., Duncan, J. S., & Koepp, M. J. (2014) · Brain · doi:10.1093/brain/awu175 · Cited by 67
Li, Z., Lan, L., Zeng, F., Makris, N., Hwang, J., Guo, T., Wu, F., Gao, Y., Dong, M., Liu, M., et al. (2016) · Cephalalgia · doi:10.1177/0333102416641665 · Cited by 67
Cui, L., Liu, L., Guo, F., Chen, Y., Chen, G., Xi, M., Qin, W., Sun, J., Li, C., Xi, Y., et al. (2017) · Radiology · doi:10.1148/radiol.2016160938 · Cited by 67
Wisner, K. M., Atluri, G., Lim, K. O., & MacDonald, A. W. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.02.066 · Cited by 66
Chiesa, P. A., Cavedo, E., Vergallo, A., Lista, S., Potier, M., Habert, M., Dubois, B., Thiebaut de Schotten, M., Hampel, H., and the INSIGHT‐preAD study group, et al. (2019) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2019.03.006 · Cited by 66
Widespread Disruption of Functional Brain Organization in Early-Onset Alzheimer’s Disease
Adriaanse, S. M., Binnewijzend, M. A. A., Ossenkoppele, R., Tijms, B. M., van der Flier, W. M., Koene, T., Smits, L. L., Wink, A. M., Scheltens, P., van Berckel, B. N. M., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0102995 · Cited by 66
Influence of APOE Genotype on Hippocampal Atrophy over Time - An N=1925 Surface-Based ADNI Study
Li, B., Shi, J., Gutman, B. A., Baxter, L. C., Thompson, P. M., Caselli, R. J., Wang, Y., & Initiative, A. D. N. (2016) · PLoS ONE · doi:10.1371/journal.pone.0152901 · Cited by 67
Cognitive benefit and cost of acute stress is differentially modulated by individual brain state
Kohn, N., Hermans, E. J., & Fernández, G. (2017) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsx043 · Cited by 66
Impact of literacy on the functional connectivity of vision and language related networks
López-Barroso, D., de Schotten, M. T., Morais, J., Kolinsky, R., Braga, L. W., Guerreiro-Tauil, A., Dehaene, S., & Cohen, L. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116722 · Cited by 66
EEG microstates are correlated with brain functional networks during slow-wave sleep
Xu, J., Pan, Y., Zhou, S., Zou, G., Liu, J., Su, Z., Zou, Q., & Gao, J. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116786 · Cited by 65
Amyloid-driven disruption of default mode network connectivity in cognitively healthy individuals
Ingala, S., Tomassen, J., Collij, L. E., Prent, N., Ent, D. V. ‘., ten Kate, M., Konijnenberg, E., Yaqub, M. M., Scheltens, P., de Geus, E. J. C., et al. (2021) · Brain Communications · doi:10.1093/braincomms/fcab201 · Cited by 65
Saggar, M., Shine, J. M., Liégeois, R., Dosenbach, N. U. F., & Fair, D. A. (2022) · Nature Communications · doi:10.1038/s41467-022-32381-2 · Cited by 65
Metadata
- Authors
- Filippini, N., MacIntosh, B. J., Hough, M. G., Goodwin, G. M., Frisoni, G. B., Smith, S. M., Matthews, P. M., Beckmann, C. F., & Mackay, C. E.
- Affiliations
- University of Oxford (GB)
- University Department of Psychiatry and
- Centro San Giovanni di Dio Fatebenefratelli (IT)
- GlaxoSmithKline (United Kingdom) (GB)
- ORCID
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2009-04-28
- Volume
- 106
- Issue
- 17
- Pages
- 7209-7214
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC2678478
- OpenAlex
- W2041325253
- Cited by
- 1,613
- References
- 60
- Citations by year
- 2026: 41 · 2025: 60 · 2024: 48 · 2023: 53 · 2022: 61 · 2021: 82 · 2020: 99 · 2019: 104 · 2018: 110 · 2017: 142 · 2016: 136 · 2015: 160 · 2014: 140 · 2013: 125 · 2012: 110
- FWCI
- 50.83
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- GlaxoSmithKline
- Wellcome Trust
- Engineering and Physical Sciences Research Council (EP/D001935/1)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- APOE ε4, APOE polymorphism, default mode network, resting-state brain activity, hippocampal activation, memory encoding, neurodegeneration risk
- MeSH terms
- Adult, Alleles, Brain, Female, Humans, Magnetic Resonance Imaging, Male, Memory, Apolipoprotein E4
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