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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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Li, C., & Tian, L. (2014) · American Journal of Neuroradiology · doi:10.3174/ajnr.a3850 · Cited by 34
Wang, X., Li, L., Xu, T., & Ding, Z. (2015) · PLoS ONE · doi:10.1371/journal.pone.0140300 · Cited by 34
Distinct Reward Properties are Encoded via Corticostriatal Interactions
Smith, D. V., Rigney, A. E., & Delgado, M. R. (2016) · Scientific Reports · doi:10.1038/srep20093 · Cited by 34
Trans-Synaptic Spread of Amyloid-βin Alzheimer’s Disease: Paths toβ-Amyloidosis
Pignataro, A., & Middei, S. (2017) · Neural Plasticity · doi:10.1155/2017/5281829 · Cited by 34
Foo, H., Mather, K. A., Jiang, J., Thalamuthu, A., Wen, W. X., & Sachdev, P. S. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2020.03.011 · Cited by 34
Köcher, M., Jockwitz, C., Caspers, S., Schreiber, J., Farrher, E., Stoffels, G., Filß, C., Lohmann, P., Tscherpel, C., Ruge, M. I., et al. (2020) · NeuroImage Clinical · doi:10.1016/j.nicl.2020.102287 · Cited by 34
van Eijndhoven, P., Collard, R. M., Vrijsen, J. N., Geurts, D. E. M., Vásquez, A. A., Schellekens, A., van den Munckhof, E., Brolsma, S. C. A., Duyser, F. A., Bergman, M. A., et al. (2021) · JMIRx Med · doi:10.2196/31269 · Cited by 34
Li, W., Han, T., Qin, W., Zhang, J., Liu, H., Li, Y., Meng, L., Ji, X., & Yu, C. (2013) · Neural Plasticity · doi:10.1155/2013/452439 · Cited by 34
Adamson, M. M., Hutchinson, J. B., Shelton, A. L., Wagner, A. D., & Taylor, J. L. (2011) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2011.04.022 · Cited by 34
Bott, J.-B., Héraud, C., Cosquer, B., Herbeaux, K., Aubert, J., Sartori, M., Goutagny, R., & Mathis, C. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.1174-16.2016 · Cited by 34
Cohen, A. D., Nencka, A. S., Lebel, R. M., & Wang, Y. (2017) · PLoS ONE · doi:10.1371/journal.pone.0169253 · Cited by 34
Modulation of resting-state network connectivity by verbal divergent thinking training
Fink, A., Benedek, M., Koschutnig, K., Papousek, I., Weiss, E. M., Bagga, D., & Schöpf, V. (2018) · Brain and Cognition · doi:10.1016/j.bandc.2018.10.008 · Cited by 34
Dajani, D. R., Burrows, C. A., Odriozola, P., Baez, A., Nebel, M. B., Mostofsky, S. H., & Uddin, L. Q. (2019) · NeuroImage: Clinical · doi:10.1016/j.nicl.2019.101678 · Cited by 33
“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).”
MethodThe search for neuroimaging biomarkers of Alzheimer's disease with advanced MRI techniques
Li, T., & Wahlund, L. (2011) · Acta Radiologica · doi:10.1258/ar.2010.100053 · Cited by 33
Disrupted Resting-State Functional Connectivity in Hippocampal Subregions After Sleep Deprivation
Zhao, R., Zhang, X., Zhu, Y., Fei, N., Sun, J., Liu, P., Yang, X., & Qin, W. (2018) · Neuroscience · doi:10.1016/j.neuroscience.2018.11.049 · Cited by 33
Bathelt, J., Koolschijn, P. C. M. P., & Geurts, H. M. (2020) · Molecular Autism · doi:10.1186/s13229-020-0316-y · Cited by 33
Anatürk, M., Suri, S., Zsoldos, E., Filippini, N., Mahmood, A., Singh‐Manoux, A., Mika Kivimaki, B., Mackay, C. E., Ebmeier, K. P., & Sexton, C. E. (2020) · JAMA Network Open · doi:10.1001/jamanetworkopen.2020.13793 · Cited by 33
Self-citationHori, Y., Schaeffer, D. J., Yoshida, A., Cléry, J. C., Hayrynen, L. K., Gati, J. S., Menon, R. S., & Everling, S. (2020) · Journal of Neuroscience · doi:10.1523/jneurosci.1984-20.2020 · Cited by 33
Kalafatakis, K., Russell, G. M., Ferguson, S. G., Grabski, M., Harmer, C. J., Munafo, M. R., Marchant, N., Wilson, A., Brooks, J. C. W., Thakrar, J., et al. (2020) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2020.105096 · Cited by 33
Brainnetome-wide association studies in schizophrenia: The advances and future
Jiang, T., Zhou, Y., Liu, B., Liu, Y., & Song, M. (2013) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2013.10.004 · Cited by 33
Structurofunctional resting-state networks correlate with motor function in chronic stroke
Kalinosky, B. T., Barillas, R. B., & Schmit, B. D. (2017) · NeuroImage Clinical · doi:10.1016/j.nicl.2017.07.002 · Cited by 33
Barnes, J. J., Woolrich, M. W., Baker, K., Colclough, G. L., & Astle, D. E. (2016) · Developmental Science · doi:10.1111/desc.12297 · Cited by 32
Initiative, A. D. N., McKenna, F., Koo, B., & Killiany, R. (2015) · Brain Imaging and Behavior · doi:10.1007/s11682-015-9451-z · Cited by 32
Moody, T. D., Morfini, F., Cheng, G., Sheen, C. L., Kerr, W. T., Strober, M. A., & Feusner, J. D. (2020) · Brain Imaging and Behavior · doi:10.1007/s11682-020-00323-5 · Cited by 32
Brown, J., Camporesi, E., Lantero‐Rodriguez, J., Olsson, M., Wang, A., Medem, B., Zetterberg, H., Blennow, K., Karikari, T. K., Wall, M. J., et al. (2023) · Acta Neuropathologica Communications · doi:10.1186/s40478-023-01562-5 · Cited by 32
Evaluation and management of patients with symptoms after anti-reflux surgery
Lin, D. C., Chun, C. L., & Triadafilopoulos, G. (2013) · Diseases of the Esophagus · doi:10.1111/dote.12103 · Cited by 32
Neuroimaging biomarkers for Alzheimer's disease in asymptomatic APOE4 carriers
Chételat, G., & Fouquet, M. (2013) · Revue Neurologique · doi:10.1016/j.neurol.2013.07.025 · Cited by 32
Matura, S., Prvulovic, D., Butz, M., Hartmann, D., Sepanski, B., Linnemann, K., Oertel‐Knöchel, V., Karakaya, T., Fußer, F., Pantel, J., et al. (2014) · European Journal of Neuroscience · doi:10.1111/ejn.12659 · Cited by 32
Altered motor network activation and functional connectivity in adult tourette's syndrome
Werner, C. J., Stöcker, T., Kellermann, T., Bath, J. E., Beldoch, M., Schneider, F. W., Wegener, H. P., Shah, J. N., & Neuner, I. (2011) · Human Brain Mapping · doi:10.1002/hbm.21175 · Cited by 32
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Horwitz, B., & Rowe, J. B. (2011) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2011.07.005 · Cited by 32
Dowell, N. G., Ruest, T., Evans, S., King, S. L., Tabet, N., Tofts, P. S., & Rusted, J. M. (2013) · NMR in Biomedicine · doi:10.1002/nbm.2912 · Cited by 32
Green, A. E., Gray, J. R., DeYoung, C. G., Mhyre, T. R., Padilla, R. M., DiBattista, A. M., & Rebeck, G. W. (2014) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2013.12.020 · Cited by 32
Ghrelin modulates encoding-related brain function without enhancing memory formation in humans
Kunath, N., Müller, N. C. J., Tonon, M., Konrad, B. N., Pawlowski, M. A., Kopczak, A., Elbau, I., Uhr, M., Kühn, S., Repantis, D., et al. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.07.016 · Cited by 32
Boerwinkle, V. L., Wilfong, A. A., & Curry, D. J. (2016) · Brain Connectivity · doi:10.1089/brain.2015.0404 · Cited by 32
Impact of automated ICA-based denoising of fMRI data in acute stroke patients
Carone, D., Licenik, R., Suri, S., Griffanti, L., Filippini, N., & Kennedy, J. M. (2017) · NeuroImage Clinical · doi:10.1016/j.nicl.2017.06.033 · Cited by 32
Self-citationReward enhances connectivity between the ventral striatum and the default mode network
Dobryakova, E., & Smith, D. V. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119398 · Cited by 31
Somatostatin and the pathophysiology of Alzheimer’s disease
Almeida, V. N. (2024) · Ageing Research Reviews · doi:10.1016/j.arr.2024.102270 · Cited by 31
Ringman, J. M., Medina, L. D., Braskie, M. N., Rodríguez‐Agudelo, Y., Geschwind, D. H., Macías-Islas, M. Á., Cummings, J. L., & Bookheimer, S. Y. (2010) · Cerebral Cortex · doi:10.1093/cercor/bhq158 · Cited by 31
Extracting functional networks with spatial independent component analysis
Esposito, F., & Goebel, R. (2011) · Current Opinion in Neurology · doi:10.1097/wco.0b013e32834897a5 · Cited by 31
Pruim, R. H. R., Beckmann, C. F., Oldehinkel, M., Oosterlaan, J., Heslenfeld, D. J., Hartman, C. A., Hoekstra, P. J., Faraone, S. V., Franke, B., Buitelaar, J. K., et al. (2018) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2018.11.014 · Cited by 31
Self-citationRace modifies default mode connectivity in Alzheimer’s disease
Misiura, M. B., Wu, J., Qiu, D., Howell, J. C., Parker, M. W., Turner, J. A., & Hu, W. T. (2020) · Translational Neurodegeneration · doi:10.1186/s40035-020-0186-4 · Cited by 31
Relating Cognition to both Brain Structure and Function: A Systematic Review of Methods
Litwińczuk, M. C., Trujillo‐Barreto, N. J., Muhlert, N., Cloutman, L. L., & Woollams, A. M. (2022) · Brain Connectivity · doi:10.1089/brain.2022.0036 · Cited by 31
Beyond the amyloid cascade: An update of Alzheimer's disease pathophysiology
Gouilly, D., Rafiq, M., Nogueira, L., Salabert, A., Payoux, P., Péran, P., & Pariente, J. (2023) · Revue Neurologique · doi:10.1016/j.neurol.2022.12.006 · Cited by 31
Ogonowski, N. S., García‐Marín, L. M., Fernando, A. S., Flores‐Ocampo, V., & Rentería, M. E. (2024) · Translational Psychiatry · doi:10.1038/s41398-024-02898-9 · Cited by 31
Altered amygdala functional connectivity in adult Tourette’s syndrome
Werner, C. J., Stöcker, T., Kellermann, T., Wegener, H. P., Schneider, F. W., Shah, N. J., & Neuner, I. (2010) · European Archives of Psychiatry and Clinical Neuroscience · doi:10.1007/s00406-010-0161-7 · Cited by 31
Tian, L., Kong, Y., Ren, J., Varoquaux, G. P., Zang, Y., & Smith, S. M. (2013) · PLoS ONE · doi:10.1371/journal.pone.0066572 · Cited by 31
Self-citationKepinska, O., de Rover, M., Caspers, J., & Schiller, N. O. (2016) · Behavioural Brain Research · doi:10.1016/j.bbr.2016.12.015 · Cited by 31
Altered resting-state connectivity within default mode network associated with late chronotype
Horne, C. M., & Norbury, R. (2018) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2018.04.013 · Cited by 31
Chandler, H. L., Wise, R. G., Murphy, K., Tansey, K. E., Linden, D. E. J., & Lancaster, T. M. (2019) · Scientific Reports · doi:10.1038/s41598-018-36820-3 · Cited by 31
Wang, X., Jiao, Y., Tang, T., Wang, H., & Lu, Z. (2013) · Neuroscience · doi:10.1016/j.neuroscience.2013.09.009 · Cited by 30
Imaging as a biomarker in drug discovery for Alzheimer’s disease: is MRI a suitable technology?
Pich, E. M., Jeromin, A., Frisoni, G. B., Hill, D., Lockhart, A., Schmidt, M. E., Turner, M. R., Mondello, S., & Potter, W. Z. (2014) · Alzheimer s Research & Therapy · doi:10.1186/alzrt276 · Cited by 30
Self-citationShine, J. P., Hodgetts, C. J., Postans, M., Lawrence, A. D., & Graham, K. S. (2015) · Scientific Reports · doi:10.1038/srep16322 · Cited by 30
Keinänen, T., Rytky, S., Korhonen, V. O., Huotari, N., Nikkinen, J., Tervonen, O. A., Palva, J. M., & Kiviniemi, V. J. (2018) · Journal of Neuroscience Research · doi:10.1002/jnr.24257 · Cited by 30
Functional disconnection between the visual cortex and right fusiform face area in schizophrenia
Maher, S. M., Ekstrom, T., Öngür, D., Levy, D. L., Norton, D. J., Nickerson, L. D. H., & Chen, Y. (2019) · Schizophrenia Research · doi:10.1016/j.schres.2019.05.016 · Cited by 30
Alnæs, D., Sneve, M. H., Richard, G., Skåtun, K. C., Kaufmann, T., Nordvik, J. E., Andreassen, O. A., Endestad, T., Laeng, B., & Westlye, L. T. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.08.029 · Cited by 30
Remes, J. J., Starck, T., Nikkinen, J., Ollila, E., Beckmann, C. F., Tervonen, O. A., Kiviniemi, V. J., & Sílven, O. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.04.268 · Cited by 30
Self-citationReproducibility of Resting State Connectivity in Patients with Stable Multiple Sclerosis
Pinter, D., Beckmann, C. F., Koini, M., Pirker, E., Filippini, N., Pichler, A., Fuchs, S., Fazekas, F., & Enzinger, C. (2016) · PLoS ONE · doi:10.1371/journal.pone.0152158 · Cited by 30
Self-citationOh, H., Steffener, J., Razlighi, Q. R., Habeck, C. G., & Stern, Y. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.3266-15.2016 · Cited by 30
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Su, Y. Y., Liang, X., Schoepf, U. J., Varga‐Szemes, Á., West, H. C., Qi, R., Kong, X., Chen, H., Lu, G., & Zhang, L. J. (2015) · Medicine · doi:10.1097/md.0000000000001734 · Cited by 31
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Seixas, D., Palace, J. A., & Tracey, I. (2016) · European Journal of Neuroscience · doi:10.1111/ejn.13272 · Cited by 30
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von Rhein, D. T., Beckmann, C. F., Franke, B., Oosterlaan, J., Heslenfeld, D. J., Hoekstra, P. J., Hartman, C. A., Luman, M., Faraone, S. V., Cools, R., et al. (2017) · Human Brain Mapping · doi:10.1002/hbm.23522 · Cited by 30
Self-citationWang, Z., Dai, Z., Shu, H., Liao, X., Yue, C., Liu, D., Guo, Q., Yong He, A., & Zhang, Z. (2017) · Scientific Reports · doi:10.1038/s41598-017-00432-0 · Cited by 30
Jiang, P., Vuontela, V., Tokariev, M., Lin, H., Aronen, E. T., Ma, Y., & Carlson, S. (2018) · PLoS ONE · doi:10.1371/journal.pone.0205690 · Cited by 30
„Default-mode“-Netzwerk des Gehirns
Otti, A., Gündel, H., Wohlschläger, A., Zimmer, C., Sorg, C., & Noll‐Hussong, M. (2011) · Der Nervenarzt · doi:10.1007/s00115-011-3307-6 · Cited by 30
Combining fMRI during resting state and an attention bias task in children
Harrewijn, A., Abend, R., Linke, J. O., Brotman, M. A., Fox, N. A., Leibenluft, E., Winkler, A. M., & Pine, D. S. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116301 · Cited by 29
Sánchez‐Pérez, N., Inuggi, A., Castillo, A., Campoy, G., García‐Santos, J. M., González-Salinas, C., & Fuentes, L. J. (2019) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2019.00247 · Cited by 29
Hong, W., Lin, Q., Cui, Z., Liu, F., Xu, R. H., & Tang, C. (2019) · NeuroImage Clinical · doi:10.1016/j.nicl.2019.102065 · Cited by 29
Li, Q., Marcu, D.-C., Palazzo, O., Turner, F. S., King, D., Spires‐Jones, T. L., Stefan, M. I., & Busch, K. E. (2020) · eLife · doi:10.7554/elife.59711 · Cited by 29
Smith, D. V., Sip, K. E., & Delgado, M. R. (2015) · Human Brain Mapping · doi:10.1002/hbm.22804 · Cited by 29
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Anhøj, S. J., Nielsen, M. Ø., Jensen, M. H., Ford, K., Fagerlund, B., Williamson, P., Glenthoj, B. Y., & Rostrup, E. (2017) · Schizophrenia Bulletin · doi:10.1093/schbul/sbx171 · Cited by 29
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Canu, E., Agosta, F., Tomić, A., Sarasso, E., Petrović, I. N., Piramide, N., Svetel, M. V., Inuggi, A., Mišković, N., Kostić, V., et al. (2020) · Human Brain Mapping · doi:10.1002/hbm.24997 · Cited by 29
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Shanahan, M. J., & Hofer, S. M. (2010) · Elsevier eBooks · doi:10.1016/b978-0-12-380880-6.00010-1 · Cited by 28
Parker, A. F., Smart, C. M., Scarapicchia, V., Gawryluk, J. R., & Initiative, A. D. N. (2020) · Journal of Alzheimer s Disease · doi:10.3233/jad-200299 · Cited by 29
Sabia, S., Mika Kivimaki, B., Meena Kumari, B., Shipley, M. J., & Singh‐Manoux, A. (2010) · Molecular Neurodegeneration · doi:10.1186/1750-1326-5-23 · Cited by 28
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DiBattista, A. M., Dumanis, S. B., Newman, J., & Rebeck, G. W. (2016) · Experimental Neurology · doi:10.1016/j.expneurol.2016.04.014 · Cited by 28
Tuovinen, T., Rytty, R., Moilanen, V., Elseoud, A. A., Veijola, J. M., Remes, A. M., & Kiviniemi, V. J. (2017) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2016.00680 · Cited by 28
Hobkirk, A. L., Nichols, T. T., Foulds, J., Yingst, J. M., Veldheer, S., Hrabovsky, S., Richie, J. P., Eissenberg, T., & Wilson, S. J. (2017) · Brain Research Bulletin · doi:10.1016/j.brainresbull.2017.05.010 · Cited by 28
Krajčovičová, L., Bartoň, M., Elfmarková, N., Mikl, M., Mareček, R., & Rektorová, I. (2017) · Journal of Neural Transmission · doi:10.1007/s00702-017-1789-5 · Cited by 28
Schluter, R. S., Jansen, J. M., van Holst, R. J., van den Brink, W., & Goudriaan, A. E. (2017) · Brain Connectivity · doi:10.1089/brain.2017.0542 · Cited by 28
Raitamaa, L., Korhonen, V. O., Huotari, N., Raatikainen, V., Hautaniemi, T., Kananen, J., Rasila, A., Helakari, H., Zienkiewicz, A., Myllylä, T., et al. (2018) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x18798441 · Cited by 28
Hegarty, A. K., Yani, M. S., Albishi, A. M., Michener, L. A., & Kutch, J. J. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117177 · Cited by 28
Faragó, P., Szabó, N., Tóth, E. M., Tuka, B., Király, A., Csete, G., Párdutz, Á., Szok, D., Tajti, J., Ertsey, C., et al. (2016) · Brain Topography · doi:10.1007/s10548-016-0535-x · Cited by 27
Alcauter, S., García-Mondragón, L., Gracia-Tabuenca, Z., Moreno, M. B., Ortiz, J. J., & Barrios, F. A. (2017) · Brain and Language · doi:10.1016/j.bandl.2017.07.007 · Cited by 27
Lee, P., Chou, K., Lu, C.-H., Chen, H.-L., Tsai, N., Hsu, A., Chen, M., Lin, W., & Lin, C. (2018) · European Radiology · doi:10.1007/s00330-018-5342-1 · Cited by 27
Lee, J., Eun, S., Kim, J., Lee, J., & Park, K. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.01062 · Cited by 27
Rabipour, S., Rajagopal, S., Yu, E., Pasvanis, S., Lafaille‐Magnan, M., Breitner, J. C. S., & Rajah, M. N. (2020) · Journal of Alzheimer s Disease · doi:10.3233/jad-191292 · Cited by 27
Lee, H. L., Stirnberg, R., Wu, S., Wang, X., Stöcker, T., Jung, S., Montag, C., & Axmacher, N. (2020) · Current Biology · doi:10.1016/j.cub.2020.08.042 · Cited by 27
Saeed, U., Desmarais, P., & Masellis, M. (2021) · Expert Review of Neurotherapeutics · doi:10.1080/14737175.2021.1956904 · Cited by 27
Kato, S., Maesawa, S., Bagarinao, E., Nakatsubo, D., Tsugawa, T., Mizuno, S., Kawabata, K., Tsuboi, T., Suzuki, M., Shibata, M., et al. (2022) · Journal of neurosurgery · doi:10.3171/2022.5.jns22411 · Cited by 27
GABA Concentration in Posterior Cingulate Cortex Predicts Putamen Response during Resting State fMRI
Arrubla, J., Tse, D. H. Y., Amkreutz, C., Neuner, I., & Shah, N. J. (2014) · PLoS ONE · doi:10.1371/journal.pone.0106609 · Cited by 27
Starck, T., Nissilä, J., Aunio, A., Abou‐Elseoud, A., Remes, J. J., Nikkinen, J., Timonen, M., Takala, T., Tervonen, O. A., & Kiviniemi, V. J. (2012) · World Journal of Neuroscience · doi:10.4236/wjns.2012.22012 · Cited by 27
Intrinsic connectivity of neural networks in the awake rabbit
Schroeder, M. P., Weiss, C., Procissi, D., Disterhoft, J. F., & Wang, L. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.01.010 · Cited by 27
Functional integrity in children with anoxic brain injury from drowning
Ishaque, M., Manning, J. H., Woolsey, M. D., Franklin, C. G., Tullis, E. W., Beckmann, C. F., & Fox, P. T. (2017) · Human Brain Mapping · doi:10.1002/hbm.23745 · Cited by 27
Self-citationTollens, F., Gass, N., Becker, R., Schwarz, A. J., Risterucci, C., Künnecke, B., Lebhardt, P., Reinwald, J., Sack, M., Weber‐Fahr, W., et al. (2018) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2018.05.016 · Cited by 27
An active cognitive lifestyle as a potential neuroprotective factor in Huntington's disease
Garcia‐Gorro, C., Garau-Rolandi, M., Escrichs, A., Rodríguez‐Dechicha, N., Vaquer, I., Subirà, S., Calopa, M., Martínez‐Horta, S., Pérez‐Pérez, J., Kulisevsky, J., et al. (2018) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2018.10.017 · Cited by 27
Pignataro, A., Meli, G., Pagano, R., Fontebasso, V., Battistella, R., Conforto, G., Ammassari‐Teule, M., & Middei, S. (2018) · Biological Psychiatry · doi:10.1016/j.biopsych.2018.10.018 · Cited by 27
Bäuml, J., Baumann, N., Avram, M., Bratec, S. M., Breeman, L. D., Berndt, M. T., Bilgin, A., Jaekel, J., Dieter Wolke, C., & Sorg, C. (2018) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2018.11.005 · Cited by 27
Hilland, E., Landrø, N. I., Harmer, C. J., Maglanoc, L. A., & Jonassen, R. (2018) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2018.00508 · Cited by 27
Lu, M., Zhao, X., Xu, D.-E., Chen, J.-B., Ji, W., Huang, Z.-P., Pan, T.-T., Xue, L., Wang, F., Li, Q., et al. (2020) · Journal of Alzheimer s Disease · doi:10.3233/jad-200010 · Cited by 27
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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