The DOI matches its Crossref record; 60 of the 60 references it cites were found in a registry or an index.
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source doesn’t support the claim as written.
In the citing paper
“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]
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
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]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“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
In the citing paper
“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]
In the citing paper
“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]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
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
Self-citation
Cited by
Sorted by citations
Items 301–400 of 1,003
Khalili‐Mahani, N., Zoethout, R. M. W., Beckmann, C. F., Baerends, E., de Kam, M. L., Soeter, R. P., Dahan, A., van Buchem, M. A., van Gerven, J. M. A., & Rombouts, S. A. R. B. (2012) · Human Brain Mapping · doi:10.1002/hbm.21265 · Cited by 114
Self-citationIbrahim, G. M., Cassel, D. B., Morgan, B. R., Smith, M. L., Otsubo, H., Ochi, A., Taylor, M. J., Rutka, J. T., Snead, O. C., & Doesburg, S. M. (2014) · Brain · doi:10.1093/brain/awu214 · Cited by 114
Shpaner, M., Kelly, C. A. M., Lieberman, G., Perelman, H., Davis, M., Keefe, F. J., & Naylor, M. R. (2014) · NeuroImage Clinical · doi:10.1016/j.nicl.2014.07.008 · Cited by 113
Differential effect of APOE genotype on amyloid load and glucose metabolism in AD dementia
Ossenkoppele, R., van der Flier, W. M., Zwan, M. D., Adriaanse, S. F., Boellaard, R., Windhorst, A. D., Barkhof, F., Lammertsma, A. A., Scheltens, P., & van Berckel, B. N. M. (2013) · Neurology · doi:10.1212/wnl.0b013e31827f0889 · Cited by 112
Wang, X., Foryt, P., Ochs, R., Chung, J.-H., Wu, Y. G., Parrish, T. B., & Ragin, A. B. (2011) · Brain Connectivity · doi:10.1089/brain.2011.0016 · Cited by 112
Network basis of suicidal ideation in depressed adolescents
Ordaz, S. J., Goyer, M. S., Ho, T. C., Singh, M. K., & Gotlib, I. H. (2018) · Journal of Affective Disorders · doi:10.1016/j.jad.2017.09.021 · Cited by 111
Neuronal Network Oscillations in Neurodegenerative Diseases
Nimmrich, V., Draguhn, A., & Axmacher, N. (2015) · NeuroMolecular Medicine · doi:10.1007/s12017-015-8355-9 · Cited by 110
Apolipoprotein E4 genotype compromises brain exosome production
Peng, K. Y., Pérez-González, R., Alldred, M. J., Goulbourne, C. N., Morales-Corraliza, J., Saito, M., Saito, M., Ginsberg, S. D., Mathews, P. M., & Levy, E. (2019) · Brain · doi:10.1093/brain/awy289 · Cited by 109
APOE-related biomarker profiles in non-pathological aging and early phases of Alzheimer's disease
Reinvang, I., Espeseth, T., & Westlye, L. T. (2013) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2013.05.006 · Cited by 109
Rusted, J. M., Evans, S., King, S. L., Dowell, N. G., Tabet, N., & Tofts, P. S. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.10.010 · Cited by 109
Mental time travel and default-mode network functional connectivity in the developing brain
Østby, Y., Walhovd, K. B., Tamnes, C. K., Grydeland, H., Westlye, L. T., & Fjell, A. M. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1210627109 · Cited by 109
Machine learning prediction of cognition from functional connectivity: Are feature weights reliable?
Tian, Y., & Zalesky, A. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118648 · Cited by 109
Alterations in Resting-State Brain Networks in Concussed Adolescent Athletes
Borich, M. R., Babul, A., Yuan, P. H., Boyd, L. A., & Virji‐Babul, N. (2014) · Journal of Neurotrauma · doi:10.1089/neu.2013.3269 · Cited by 109
Bagarinao, E., Watanabe, H., Maesawa, S., Mori, D., Hara, K., Kawabata, K., Yoneyama, N., Ohdake, R., Imai, K., Masuda, M., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-47922-x · Cited by 108
Language networks in anophthalmia: maintained hierarchy of processing in ‘visual’ cortex
Watkins, K. E., Cowey, A., Alexander, I. H., Filippini, N., Kennedy, J. M., Smith, S. M., Ragge, N., & Bridge, H. (2012) · Brain · doi:10.1093/brain/aws067 · Cited by 108
Self-citationLi, W., Lai, T. M., Bohon, C., Loo, S. K., McCurdy, D., Strober, M. A., Bookheimer, S. Y., & Feusner, J. D. (2015) · Psychological Medicine · doi:10.1017/s0033291715000045 · Cited by 108
The goal priority network as a neural substrate of Conscientiousness
Rueter, A., Abram, S. V., MacDonald, A. W., Rustichini, A., & DeYoung, C. G. (2018) · Human Brain Mapping · doi:10.1002/hbm.24195 · Cited by 108
Relationships between cortical myeloarchitecture and electrophysiological networks
Hunt, B. A. E., Tewarie, P. K. B., Mougin, O. E., Geades, N., Jones, D. K., Singh, K. D., Morris, P. G., Gowland, P. A., & Brookes, M. J. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1608587113 · Cited by 107
Capillary Dysfunction: Its Detection and Causative Role in Dementias and Stroke
Østergaard, L., Jespersen, S. N., Engedahl, T., Jiménez, E. G., Ashkanian, M., Hansen, M. B., Eskildsen, S. F., & Mouridsen, K. (2015) · Current Neurology and Neuroscience Reports · doi:10.1007/s11910-015-0557-x · Cited by 106
Stonehouse, W. (2014) · Nutrients · doi:10.3390/nu6072730 · Cited by 105
APOE alters glucose flux through central carbon pathways in astrocytes
Williams, H. C., Farmer, B. C., Piron, M. A., Walsh, A. E., Bruntz, R. C., Gentry, M. S., Sun, R. C., & Johnson, L. A. (2020) · Neurobiology of Disease · doi:10.1016/j.nbd.2020.104742 · Cited by 105
Altered resting‐state connectivity in Huntington's Disease
Werner, C. J., Dogan, I., Saß, C., Mirzazade, S., Schiefer, J., Shah, N. J., Schulz, J. B., & Reetz, K. (2013) · Human Brain Mapping · doi:10.1002/hbm.22351 · Cited by 105
Mapping white-matter functional organization at rest and during naturalistic visual perception
Lynch, L. K., Lu, K., Wen, H., & Liu, Z. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.10.005 · Cited by 104
Intrinsically organized resting state networks in the human spinal cord
Kong, Y., Eippert, F., Beckmann, C. F., Andersson, J., Finsterbusch, J., Büchel, C., Tracey, I., & Brooks, J. C. W. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1414293111 · Cited by 104
Self-citationBrainnetome: A new -ome to understand the brain and its disorders
Jiang, T. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.002 · Cited by 104
Functional connectivity in the developing brain: a longitudinal study from 4 to 9months of age
Damaraju, E., Caprihan, A., Lowe, J. R., Allen, E. A., Calhoun, V. D., & Phillips, J. P. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.08.038 · Cited by 103
“Similar model orders have been used by a number of labs (Allen et al., 2012; Damoiseaux et al., 2006; Filippini et al., 2009).”
BackgroundMethodEvaluation of Multiband EPI Acquisitions for Resting State fMRI
Preibisch, C., Castrillón, G., Buehrer, M., & Riedl, V. (2015) · PLoS ONE · doi:10.1371/journal.pone.0136961 · Cited by 103
The effects of methylphenidate on whole brain intrinsic functional connectivity
Mueller, S., Costa, A. C. L., Keeser, D., Pogarell, O. M., Berman, A., Coates, U., Reiser, M. F., Riedel, M. J., Möller, H., Ettinger, U., et al. (2014) · Human Brain Mapping · doi:10.1002/hbm.22557 · Cited by 103
Klumpers, L. E., Cole, D. M., Khalili‐Mahani, N., Soeter, R. P., Beek, E. T. T., Rombouts, S. A. R. B., & van Gerven, J. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.07.051 · Cited by 103
Klingbeil, J., Wawrzyniak, M., Stockert, A., & Saur, D. (2017) · Brain and Cognition · doi:10.1016/j.bandc.2017.08.005 · Cited by 102
Linguistic immersion and structural effects on the bilingual brain: a longitudinal study
DeLuca, V., Rothman, J., & Pliatsikas, C. (2018) · Bilingualism Language and Cognition · doi:10.1017/s1366728918000883 · Cited by 102
Salience and Default Mode Network Coupling Predicts Cognition in Aging and Parkinson’s Disease
Putcha, D., Ross, R. S., Cronin‐Golomb, A., Janes, A. C., & Stern, C. E. (2016) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617715000892 · Cited by 101
Alzheimer's disease disrupts alpha and beta-band resting-state oscillatory network connectivity
Koelewijn, L., Bompas, A., Tales, A., Brookes, M. J., Muthukumaraswamy, S. D., Bayer, A. J., & Singh, K. D. (2017) · Clinical Neurophysiology · doi:10.1016/j.clinph.2017.04.018 · Cited by 101
Magnetic Resonance Imaging in Late-Life Depression
Sexton, C. E., Allan, C. L., Masurier, M. L., McDermott, L. M., Kalu, U. G., Herrmann, L. L., Mäurer, M. A., Bradley, K. M., Mackay, C. E., & Ebmeier, K. P. (2012) · Archives of General Psychiatry · doi:10.1001/archgenpsychiatry.2011.1862 · Cited by 101
Self-citationHigh-Density Lipoproteins and Cerebrovascular Integrity in Alzheimer’s Disease
Stukas, S. K., Robert, J., & Wellington, C. L. (2014) · Cell Metabolism · doi:10.1016/j.cmet.2014.01.003 · Cited by 101
Large-scale Probabilistic Functional Modes from resting state fMRI
Harrison, S. J., Woolrich, M. W., Robinson, E. C., Glasser, M. F., Beckmann, C. F., Jenkinson, M., & Smith, S. M. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.01.013 · Cited by 100
Self-citationMultiparametric MRI changes persist beyond recovery in concussed adolescent hockey players
Manning, K. Y., Schranz, A. L., Bartha, R., Dekaban, G. A., Barreira, C., Brown, A. M., Fischer, L. K., Asem, K., Doherty, T. J., Fraser, D. D., et al. (2017) · Neurology · doi:10.1212/wnl.0000000000004669 · Cited by 99
Dynamic Connectivity at Rest Predicts Attention Task Performance
Madhyastha, T. M., Askren, M. K., Boord, P., & Grabowski, T. J. (2014) · Brain Connectivity · doi:10.1089/brain.2014.0248 · Cited by 99
Alzheimer's disease: The forgetting gene
Spinney, L. (2014) · Nature · doi:10.1038/510026a · Cited by 98
Vaessen, M. J., Braakman, H. M. H., Heerink, J. S., Jansen, J. F. A., Hall, M. H. J. A. D.-V., Hofman, P. A. M., Aldenkamp, A. P., & Backes, W. H. (2012) · Cerebral Cortex · doi:10.1093/cercor/bhs186 · Cited by 98
Foley, S. F., Tansey, K. E., Caseras, X., Lancaster, T. M., Bracht, T., Parker, G. D., Hall, J., Williams, J. H., & Linden, D. E. J. (2016) · Biological Psychiatry · doi:10.1016/j.biopsych.2016.02.033 · Cited by 98
Bagga, D., Aigner, C. S., Reichert, J. L., Cecchetto, C., Fischmeister, F. P. S., Holzer, P. D., Moissl‐Eichinger, C., & Schöpf, V. (2018) · European Journal of Nutrition · doi:10.1007/s00394-018-1732-z · Cited by 98
Ren, F., Wei, J., Chen, Q., Hu, M., Yu, L., Mi, J., Zhou, X., Qin, D., Wu, J., & Wu, A. (2025) · Acta Pharmaceutica Sinica B · doi:10.1016/j.apsb.2025.07.030 · Cited by 97
The effects of APOE-ε4 on the BOLD response
Trachtenberg, A. J., Filippini, N., & Mackay, C. E. (2010) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2010.03.009 · Cited by 97
Self-citationGenetic variants in Alzheimer disease — molecular and brain network approaches
Gaiteri, C., Mostafavi, S., Honey, C. J., Jager, P. L. D., & Bennett, D. A. (2016) · Nature Reviews Neurology · doi:10.1038/nrneurol.2016.84 · Cited by 97
Hyperactivity Induced by Soluble Amyloid-β Oligomers in the Early Stages of Alzheimer's Disease
Hector, A., & Brouillette, J. (2021) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2020.600084 · Cited by 97
Idiosyncratic responding during movie-watching predicted by age differences in attentional control
Campbell, K. L., Shafto, M. A., Wright, P. K., Tsvetanov, K. A., Geerligs, L., Cusack, R., TYLER, L. K., Tyler, L. K., Brayne, C., Bullmore, E. T., et al. (2015) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2015.07.028 · Cited by 97
Mash, L. E., Linke, A. C., Olson, L. A., Fishman, I., Liu, T. T., & Müller, R. (2019) · Human Brain Mapping · doi:10.1002/hbm.24529 · Cited by 96
Functional connectivity and cognitive impairment in migraine with and without aura
Buono, V. L., Bonanno, L., Corallo, F., Pisani, L. R., Presti, R. L., Grugno, R., Lorenzo, G. D., Bramanti, P., & Marino, S. (2017) · The Journal of Headache and Pain · doi:10.1186/s10194-017-0782-6 · Cited by 96
Schmitt, A. G., Upadhyay, N., Martin, J. A., Rojas, S., Strüder, H. K., & Boecker, H. (2019) · Brain Plasticity · doi:10.3233/bpl-190081 · Cited by 97
Maesawa, S., Bagarinao, E., Fujii, M., Futamura, M., Motomura, K., Watanabe, H., Mori, D., Sobue, G., & Wakabayashi, T. (2015) · PLoS ONE · doi:10.1371/journal.pone.0118072 · Cited by 96
Liu, B., Song, M., Li, J., Liu, Y., Li, K., Yu, C., & Jiang, T. (2010) · Journal of Neuroscience · doi:10.1523/jneurosci.3941-09.2010 · Cited by 95
Filippi, M., & Agosta, F. (2011) · Journal of Alzheimer s Disease · doi:10.3233/jad-2011-101854 · Cited by 95
Link between hippocampus' raised local and eased global intrinsic connectivity in AD
Pasquini, L., Scherr, M., Tahmasian, M., Meng, C., Myers, N. E., Ortner, M., Mühlau, M., Kurz, A., Förstl, H., Zimmer, C., et al. (2014) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2014.02.007 · Cited by 95
Apolipoprotein E genotype, gender and age modulate connectivity of the hippocampus in healthy adults
Heise, V., Filippini, N., Trachtenberg, A. J., Suri, S., Ebmeier, K. P., & Mackay, C. E. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.04.081 · Cited by 94
Self-citationRittman, T., Rubinov, M., Vértes, P. E., Patel, A. X., Ginestet, C. E., Ghosh, B. C. P., Barker, R. A., Spillantini, M. G., Bullmore, E. T., & Rowe, J. B. (2016) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2016.09.001 · Cited by 94
A computational model of shared fine-scale structure in the human connectome
Guntupalli, J. S., Feilong, M., & Haxby, J. V. (2018) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006120 · Cited by 94
Reduced default mode network connectivity in treatment‐resistant idiopathic generalized epilepsy
Kay, B. P., DiFrancesco, M. W., Privitera, M., Gotman, J., Holland, S. K., & Szaflarski, J. P. (2013) · Epilepsia · doi:10.1111/epi.12057 · Cited by 94
Igelström, K. M., Webb, T. W., & Graziano, M. S. A. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw079 · Cited by 93
Lee, H., Cho, S., Kim, M.-J., Park, Y. J., Cho, E., Jo, Y. S., Kim, Y.-S., Lee, J. Y., Thoudam, T., Woo, S.-H., et al. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.113183 · Cited by 93
Wines-Samuelson, M., Schulte, E. C., Smith, M. J., Aoki, C. J., Liu, X., Kelleher, R. J., & Shen, J. (2010) · PLoS ONE · doi:10.1371/journal.pone.0010195 · Cited by 93
Neuroimaging in pre-motor Parkinson's disease
Barber, T. R., Klein, J. C., Mackay, C. E., & Hu, M. T. M. (2017) · NeuroImage Clinical · doi:10.1016/j.nicl.2017.04.011 · Cited by 92
Self-citationWang, J., Khosrowabadi, R., Ng, K. K., Hong, Z., Chong, J. S. X., Wang, Y., Chen, C.-Y., Hilal, S., Venketasubramanian, N., Wong, T. Y., et al. (2018) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2018.00404 · Cited by 92
Rajab, A. S., Crane, D., Middleton, L. E., Robertson, A. D., Hampson, M., & MacIntosh, B. J. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00625 · Cited by 92
Self-citationErpelding, N., & Davis, K. D. (2013) · Pain · doi:10.1016/j.pain.2013.06.030 · Cited by 91
Gray matter network associated with risk for Alzheimer's disease in young to middle-aged adults
Alexander, G. E., Bergfield, K. L., Chen, K., Reiman, E. M., Hanson, K. D., Lin, L., Bandy, D. J., Caselli, R. J., & Moeller, J. R. (2012) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2012.01.014 · Cited by 91
Executive Dysfunction in MCI: Subtype or Early Symptom
Reinvang, I., Grambaitė, R., & Espeseth, T. (2012) · International Journal of Alzheimer s Disease · doi:10.1155/2012/936272 · Cited by 91
Labrenz, F., Wrede, K. H., Forsting, M., Engler, H., Schedlowski, M., Elsenbruch, S., & Benson, S. (2015) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2015.11.010 · Cited by 91
Panda, R., Bharath, R. D., Upadhyay, N., Mangalore, S., Chennu, S., & Rao, S. L. (2016) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2016.00372 · Cited by 91
Bukhari, Q., Schroeter, A., Cole, D. M., & Rudin, M. (2017) · Frontiers in Neural Circuits · doi:10.3389/fncir.2017.00005 · Cited by 90
Functional network integration and attention skills in young children
Rohr, C. S., Arora, A. K., Cho, I. Y. K., Katlariwala, P., Dimond, D., Dewey, D., & Bray, S. (2018) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2018.03.007 · Cited by 90
Heine, J., Prüß, H., Kopp, U. A., Wegner, F., Bergh, F. T., Münte, T. F., Wandinger, K., Paul, F., Bartsch, T., & Finke, C. (2018) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp-2017-317780 · Cited by 90
Within- and across-network alterations of the sensorimotor network in Parkinson’s disease
Caspers, J., Rubbert, C., Eickhoff, S. B., Hoffstaedter, F., Südmeyer, M., Hartmann, C. J., Sigl, B., Teichert, N., Aissa, J., Turowski, B., et al. (2021) · Neuroradiology · doi:10.1007/s00234-021-02731-w · Cited by 90
Zilberter, M. Y., Ivanov, A., Ziyatdinova, S., Mukhtarov, M. R., Malkov, A., Alpár, A., Tortoriello, G., Botting, C. H., Fülöp, L., Osypov, A. A., et al. (2012) · Journal of Neurochemistry · doi:10.1111/jnc.12127 · Cited by 90
Poudel, G. R., Egan, G. F., Churchyard, A., Chua, P. M.-L., Stout, J. C., & Georgiou‐Karistianis, N. (2014) · Journal of Psychiatry and Neuroscience · doi:10.1503/jpn.120226 · Cited by 90
Eskildsen, S. F., Gyldensted, L., Nagenthiraja, K., Nielsen, R. B., Hansen, M. B., Dalby, R. B., Frandsen, J. R., Rodell, A. B., Gyldensted, C., Jespersen, S. N., et al. (2016) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2016.11.004 · Cited by 90
Functional parcellation of the default mode network: a large-scale meta-analysis
Wang, S., Tepfer, L. J., Taren, A. A., & Smith, D. V. (2020) · Scientific Reports · doi:10.1038/s41598-020-72317-8 · Cited by 89
Apolipoprotein E ε4 modulates functional brain connectome in A lzheimer's disease
Wang, J., Wang, X., He, Y., Yu, X., Wang, H., & He, Y. (2015) · Human Brain Mapping · doi:10.1002/hbm.22740 · Cited by 87
Imaging Brain Effects of APOE4 in Cognitively Normal Individuals Across the Lifespan
Fouquet, M., Besson, F. L., Gonneaud, J., Joie, R. L., & Chételat, G. (2014) · Neuropsychology Review · doi:10.1007/s11065-014-9263-8 · Cited by 89
Network-wide reorganization of procedural memory during NREM sleep revealed by fMRI
Vahdat, S., Fogel, S. M., Benali, H., & Doyon, J. (2017) · eLife · doi:10.7554/elife.24987 · Cited by 88
P301L tau expression affects glutamate release and clearance in the hippocampal trisynaptic pathway
Hunsberger, H. C., Rudy, C. C., Batten, S. R., Gerhardt, G. A., & Reed, M. N. (2014) · Journal of Neurochemistry · doi:10.1111/jnc.12967 · Cited by 87
Modulating spontaneous brain activity using repetitive transcranial magnetic stimulation
van der Werf, Y. D., Sanz‐Arigita, E., Menning, S., & van den Heuvel, O. A. (2010) · BMC Neuroscience · doi:10.1186/1471-2202-11-145 · Cited by 87
Brain connectivity aberrations in anabolic-androgenic steroid users
Westlye, L. T., Kaufmann, T., Alnæs, D., Hullstein, I. R., & Bjørnebekk, A. (2016) · NeuroImage Clinical · doi:10.1016/j.nicl.2016.11.014 · Cited by 87
Wolpe, N., Moore, J. W., Rae, C. L., Rittman, T., Altena, E., Haggard, P., & Rowe, J. B. (2014) · Brain · doi:10.1093/brain/awt302 · Cited by 86
Cognitive and neural signatures of the APOE E4 allele in mid-aged adults
Evans, S., Dowell, N. G., Tabet, N., Tofts, P. S., King, S. L., & Rusted, J. M. (2014) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2014.01.145 · Cited by 86
Hafkemeijer, A., Möller, C., Dopper, E. G. P., Jiskoot, L. C., Schouten, T. M., Swieten, J. C. V., van der Flier, W. M., Vrenken, H., Pijnenburg, Y. A. L., Barkhof, F., et al. (2015) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2015.00474 · Cited by 85
The anatomy of fear learning in the cerebellum: A systematic meta-analysis
Lange, I., Kasanova, Z., Goossens, L., Leibold, N. K., Zeeuw, C. I. D., van Amelsvoort, T., & Schruers, K. R. J. (2015) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2015.09.019 · Cited by 85
Tong, L. M., Fong, H., & Huang, Y. (2015) · Experimental & Molecular Medicine · doi:10.1038/emm.2014.124 · Cited by 85
Lee, T., Miernicki, M. E., & Telzer, E. H. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.02.078 · Cited by 85
Hunsberger, H. C., Weitzner, D. S., Rudy, C. C., Hickman, J. E., Libell, E. M., Speer, R. R., Gerhardt, G. A., & Reed, M. N. (2015) · Journal of Neurochemistry · doi:10.1111/jnc.13230 · Cited by 85
Aberrant functional connectivity of resting state networks associated with trait anxiety
Modi, S., Kumar, M., Kumar, P., & Khushu, S. (2015) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2015.07.006 · Cited by 85
Griffanti, L., Rolinski, M., Szewczyk‐Królikowski, K., Menke, R., Filippini, N., Zamboni, G., Jenkinson, M., Hu, M. T. M., & Mackay, C. E. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.09.021 · Cited by 84
Self-citationJamadar, S. D., Ward, P. G. D., Li, S., Sforazzini, F., Baran, J., Chen, Z., & Egan, G. F. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.01.003 · Cited by 84
Vascular physiology drives functional brain networks
Bright, M. G., Whittaker, J. R., Driver, I. D., & Murphy, K. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116907 · Cited by 84
Dacosta‐Aguayo, R., Graña, M., Iturria‐Medina, Y., Fernández‐Andújar, M., Elena López-Cancio, M., Cáceres, C. M., Bargalló, N., Barrios, M., Clemente, I. C., Toran, P., et al. (2014) · Human Brain Mapping · doi:10.1002/hbm.22648 · Cited by 84
APOE and neuroenergetics: an emerging paradigm in Alzheimer's disease
Wolf, A. B., Caselli, R. J., Reiman, E. M., & Valla, J. (2012) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2012.10.011 · Cited by 84
APOE ε4 and cognitive function in early life: A meta-analysis.
Ihle, A., Bunce, D. J., & Kliegel, M. (2012) · Neuropsychology · doi:10.1037/a0026769 · Cited by 84
Consistent Functional Connectivity Alterations in Schizophrenia Spectrum Disorder: A Multisite Study
Skåtun, K. C., Kaufmann, T., Doan, N. T., Alnæs, D., Córdova‐Palomera, A., Jönsson, E. G., Fatouros‐Bergman, H., Flyckt, L., Melle, I. S., Andreassen, O. A., et al. (2016) · Schizophrenia Bulletin · doi:10.1093/schbul/sbw145 · Cited by 84
Bos, D. J., Oranje, B., Achterberg, M., Vlaskamp, C., Ambrosino, S., de Reus, M. A., van den Heuvel, M. P., Rombouts, S. A. R. B., & Durston, S. (2017) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12712 · Cited by 84
Cai, W., Li, L., Sang, S., Pan, X., & Zhong, C. (2023) · Neuroscience Bulletin · doi:10.1007/s12264-022-00985-9 · Cited by 83
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review