The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.
Impaired default network functional connectivity in autosomal dominant Alzheimer disease
Open accessAbstract
OBJECTIVE: To investigate default mode network (DMN) functional connectivity MRI (fcMRI) in a large cross-sectional cohort of subjects from families harboring pathogenic presenilin-1 (PSEN1), presenilin-2 (PSEN2), and amyloid precursor protein (APP) mutations participating in the Dominantly Inherited Alzheimer Network. METHODS: Eighty-three mutation carriers and 37 asymptomatic noncarriers from the same families underwent fMRI during resting state at 8 centers in the United States, United Kingdom, and Australia. Using group-independent component analysis, fcMRI was compared using mutation status and Clinical Dementia Rating to stratify groups, and related to each participant's estimated years from expected symptom onset (eYO). RESULTS: We observed significantly decreased DMN fcMRI in mutation carriers with increasing Clinical Dementia Rating, most evident in the precuneus/posterior cingulate and parietal cortices (p < 0.001). Comparison of asymptomatic mutation carriers with noncarriers demonstrated decreased fcMRI in the precuneus/posterior cingulate (p = 0.014) and right parietal cortex (p = 0.0016). We observed a significant interaction between mutation carrier status and eYO, with decreases in DMN fcMRI observed as mutation carriers approached and surpassed their eYO. CONCLUSION: Functional disruption of the DMN occurs early in the course of autosomal dominant Alzheimer disease, beginning before clinically evident symptoms, and worsening with increased impairment. These findings suggest that DMN fcMRI may prove useful as a biomarker across a wide spectrum of disease, and support the feasibility of DMN fcMRI as a secondary endpoint in upcoming multicenter clinical trials in Alzheimer disease.
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 source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“our findings support the possibility that callosal white matter degeneration contribute to functional disruption of functional networks such as the default mode network (Chhatwal et al., 2013; Mueller and Weiner, 2017; Taylor et al., 2017)”
From White matter diffusion alterations precede symptom onset in autosomal dominant Alzheimer’s disease (2018) · cites this paper as Chhatwal et al., 2013
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“a functional network showing reduced connectivity in early-stage Alzheimer’s disease (Sorg et al., 2007; Chhatwal et al., 2013)”
From White matter diffusion alterations precede symptom onset in autosomal dominant Alzheimer’s disease (2018) · cites this paper as Chhatwal et al., 2013
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
Lecture Notes in Computer Science 1205
(1999) · Industrial Robot the international journal of robotics research and application · doi:10.1108/ir.1999.04926fae.001 · Cited by 39,228
The Amyloid Hypothesis of Alzheimer’s Disease: Progress and Problems on the Road to Therapeutics
Hardy, J., & Selkoe, D. J. (2002) · Science · doi:10.1126/science.1072994 · Cited by 13,864
Amyloid oligomers exacerbate tau pathology in a mouse model of tauopathy
Selenica, M.-L. B., Brownlow, M., Jimenez, J. P., Lee, D. C., Pena, G., Dickey, C. A., Gordon, M. N., & Morgan, D. (2013) · Neurodegenerative Diseases · doi:10.1159/000337230 · Cited by 10,359
The organization of the human cerebral cortex estimated by intrinsic functional connectivity
Thomas Yeo, B. T., Krienen, F. M., Sepulcre, J., Sabuncu, M. R., Lashkari, D., Hollinshead, M., Roffman, J. L., Smoller, J. W., Zöllei, L., Polimeni, J. R., et al. (2011) · Journal of Neurophysiology · doi:10.1152/jn.00338.2011 · Cited by 9,182
The human brain is intrinsically organized into dynamic, anticorrelated functional networks
Fox, M. D., Snyder, A. Z., Vincent, J. L., Corbetta, M., Van Essen, D. C., & Raichle, M. E. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0504136102 · Cited by 8,553
The organization of the human cerebellum estimated by intrinsic functional connectivity
Buckner, R. L., Krienen, F. M., Castellanos, A., Diaz, J. C., & Yeo, B. T. T. (2011) · Journal of Neurophysiology · doi:10.1152/jn.00339.2011 · Cited by 7,304
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
Self-citationFunctional connectivity in the resting brain: a network analysis of the default mode hypothesis
Greicius, M. D., Krasnow, B., Reiss, A. L., & Menon, V. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0135058100 · Cited by 6,358
Gauthier, S. G., Reisberg, ., Zaudig, M., Petersen, R. C., Ritchie, K. A., Broich, K., Belleville, S., Brodaty, H., Bennett, D. A., Chertkow, H. M., et al. (2006) · The Lancet · doi:10.1016/s0140-6736(06)68542-5 · Cited by 4,094
Clinical and biomarker changes in dominantly inherited Alzheimer's disease
Bateman, R. J., Xiong, C., Benzinger, T. L. S., Fagan, A. M., Goate, A., Fox, N. C., Marcus, D. S., Cairns, N. J., Xie, X., Blazey, T. M., et al. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1202753 · Cited by 3,814
Self-citation
Research works printed but not linked: 1
- Thomas JB Brier MR Bateman RJ et al.. Functional connectivity in autosomal dominant and sporadic Alzheimer disease. Presented at the Alzheimer's Association International Conference; July 13–18 2013; Boston.
Cited by
Sorted by citations
Cerebral blood flow regulation and neurovascular dysfunction in Alzheimer disease
Kisler, K., Nelson, A. R., Montagne, A., & Zlokovic, B. V. (2017) · Nature Reviews Neuroscience · doi:10.1038/nrn.2017.48 · Cited by 1,243
The Evolution of Preclinical Alzheimer’s Disease: Implications for Prevention Trials
Sperling, R., Mormino, E., & Johnson, K. (2014) · Neuron · doi:10.1016/j.neuron.2014.10.038 · Cited by 725
Self-citationImaging the evolution and pathophysiology of Alzheimer disease
Jagust, W. (2018) · Nature Reviews Neuroscience · doi:10.1038/s41583-018-0067-3 · Cited by 604
Resting‐state network dysfunction in Alzheimer's disease: A systematic review and meta‐analysis
Badhwar, A., Tam, A., Dansereau, C. L., Orban, P., Hoffstaedter, F., & Bellec, P. (2017) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1016/j.dadm.2017.03.007 · Cited by 453
Resting-State Functional MR Imaging: A New Window to the Brain
Barkhof, F., Haller, S., & Rombouts, S. A. R. B. (2014) · Radiology · doi:10.1148/radiol.14132388 · Cited by 397
Schultz, A. P., Chhatwal, J. P., Hedden, T., Mormino, E. C., Hanseeuw, B. J., Sepulcre, J., Huijbers, W., LaPoint, M., Buckley, R. F., Johnson, K. A., et al. (2017) · The Journal of Neuroscience · doi:10.1523/jneurosci.3263-16.2017 · Cited by 330
Self-citationLongitudinal cognitive and biomarker changes in dominantly inherited Alzheimer disease
McDade, E., Wang, G., Gordon, B. A., Hassenstab, J., Benzinger, T. L. S., Buckles, V., Fagan, A. M., Holtzman, D. M., Cairns, N. J., Goate, A. M., et al. (2018) · Neurology · doi:10.1212/wnl.0000000000006277 · Cited by 314
Self-citationBrain connectivity in neurodegenerative diseases—from phenotype to proteinopathy
Pievani, M., Filippini, N., van den Heuvel, M. P., Cappa, S. F., & Frisoni, G. B. (2014) · Nature Reviews Neurology · doi:10.1038/nrneurol.2014.178 · Cited by 320
The human connectome in Alzheimer disease — relationship to biomarkers and genetics
Yu, M., Sporns, O., & Saykin, A. J. (2021) · Nature Reviews Neurology · doi:10.1038/s41582-021-00529-1 · Cited by 265
Self-citationHyperconnectivity is a fundamental response to neurological disruption.
Hillary, F. G., Román, C. A. F., Venkatesan, U. M., Rajtmajer, S. M., Bajo, R., & Castellanos, N. P. (2014) · Neuropsychology · doi:10.1037/neu0000110 · Cited by 265
Sex differences in normal age trajectories of functional brain networks
Scheinost, D., Finn, E. S., Tokoglu, F., Shen, X., Papademetris, X., Hampson, M., & Constable, R. T. (2014) · Human Brain Mapping · doi:10.1002/hbm.22720 · Cited by 240
Hohenfeld, C., Werner, C. J., & Reetz, K. (2018) · NeuroImage: Clinical · doi:10.1016/j.nicl.2018.03.013 · Cited by 232
What Happens with the Circuit in Alzheimer's Disease in Mice and Humans?
Zott, B., Busche, M. A., Sperling, R. A., & Konnerth, A. (2018) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-080317-061725 · Cited by 221
Self-citationSex and gender differences in cognitive resilience to aging and Alzheimer's disease
Arenaza‐Urquijo, E. M., Boyle, R., Casaletto, K., Anstey, K. J., Vila‐Castelar, C., Colverson, A., Palpatzis, E., Eissman, J. M., Kheng Siang Ng, T., Raghavan, S., et al. (2024) · Alzheimer's & Dementia · doi:10.1002/alz.13844 · Cited by 223
Halko, M. A., Farzan, F., Eldaief, M. C., Schmahmann, J. D., & Pascual‐Leone, Á. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.1776-14.2014 · Cited by 206
Network Dysfunction in Alzheimer's Disease: Refining the Disconnection Hypothesis
Brier, M. R., Thomas, J., & Ances, B. M. (2014) · Brain Connectivity · doi:10.1089/brain.2014.0236 · Cited by 203
Self-citationWhite matter diffusion alterations precede symptom onset in autosomal dominant Alzheimer’s disease
Araque Caballero, M. Á., Suárez-Calvet, M., Duering, M., Franzmeier, N., Benzinger, T., Fagan, A. M., Bateman, R. J., Jack, C. R., Levin, J., Dichgans, M., et al. (2018) · Brain · doi:10.1093/brain/awy229 · Cited by 184
“, 2009), a functional network showing reduced connectivity in early-stage Alzheimer’s disease (Sorg et al., 2007; Chhatwal et al., 2013).”
BackgroundSelf-citationFunctional Connectivity in Autosomal Dominant and Late-Onset Alzheimer Disease
Thomas, J. B., Brier, M. R., Bateman, R. J., Snyder, A. Z., Benzinger, T. L., Xiong, C., Raichle, M., Holtzman, D. M., Sperling, R. A., Mayeux, R., et al. (2014) · JAMA Neurology · doi:10.1001/jamaneurol.2014.1654 · Cited by 129
Self-citationQuiroz, Y. T., Schultz, A. P., Chen, K., Protas, H. D., Brickhouse, M. J., Fleisher, A., Langbaum, J. B. S., Thiyyagura, P., Fagan, A. M., Shah, A. R., et al. (2015) · JAMA Neurology · doi:10.1001/jamaneurol.2015.1099 · Cited by 124
Self-citationFranzmeier, N., Düzel, E., Jessen, F., Büerger, K., Levin, J., Duering, M., Dichgans, M., Haass, C., Suárez‐Calvet, M., Fagan, A. M., et al. (2018) · Brain · doi:10.1093/brain/awy008 · Cited by 117
Self-citationAccelerated functional brain aging in pre-clinical familial Alzheimer’s disease
Gonneaud, J., Baria, A. T., Binette, A. P., Gordon, B. A., Chhatwal, J. P., Cruchaga, C., Jucker, M., Levin, J., Salloway, S., Farlow, M. R., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-25492-9 · Cited by 109
Self-citationPreferential degradation of cognitive networks differentiates Alzheimer’s disease from ageing
Chhatwal, J. P., Schultz, A. P., Johnson, K. A., Hedden, T., Jaimes, S., Benzinger, T. L. S., Jack, C., Ances, B. M., Ringman, J. M., Marcus, D. S., et al. (2018) · Brain · doi:10.1093/brain/awy053 · Cited by 101
Self-citationCognitive Science: An Introduction to the Science of the Mind
Bermúdez, J. L. (2020) · Cited by 98
Genetic 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
Guzmán‐Vélez, E., Diez, I. P., Schoemaker, D., Pardilla‐Delgado, E., Vila‐Castelar, C., Fox‐Fuller, J. T., Baena, A. Y., Sperling, R. A., Johnson, K. A., Lopera, F. J., et al. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2113641119 · Cited by 95
Self-citationJoo, S. H., Lim, H. K., & Lee, C. U. (2016) · Psychiatry Investigation · doi:10.4306/pi.2016.13.1.1 · Cited by 94
Amyloid Deposition Is Linked to Aberrant Entorhinal Activity among Cognitively Normal Older Adults
Huijbers, W., Mormino, E. C., Wigman, S. E., Ward, A. M., Vannini, P., McLaren, D. G., Becker, J. A., Schultz, A. P., Hedden, T., Johnson, K. A., et al. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.3579-13.2014 · Cited by 91
Self-citationProudfoot, M., Rohenkohl, G., Quinn, A. J., Colclough, G. L., Wuu, J., Talbot, K., Woolrich, M. W., Benatar, M. G., Nobre, A. C., & Turner, M. R. (2016) · Human Brain Mapping · doi:10.1002/hbm.23357 · Cited by 87
Burks, J. D., Bonney, P. A., Conner, A. K., Glenn, C. A., Briggs, R. G., Battiste, J. D., McCoy, T. M., OʼDonoghue, D. L., Wu, D. H., & Sughrue, M. E. (2016) · Journal of neurosurgery · doi:10.3171/2016.5.jns153006 · Cited by 85
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
Liang, P., Wang, Z., Qian, T., & Li, K. (2014) · American Journal of Alzheimer s Disease & Other Dementias® · doi:10.1177/1533317514536600 · Cited by 85
Network-Based Biomarkers in Alzheimer’s Disease: Review and Future Directions
Gómez‐Ramírez, J., & Wu, J. (2014) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2014.00012 · Cited by 82
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
Early Failure of the Default‐Mode Network and the Pathogenesis of Alzheimer's Disease
Šimić, G., Leko, M. B., Borovečki, F., & Hof, P. R. (2014) · CNS Neuroscience & Therapeutics · doi:10.1111/cns.12260 · Cited by 75
Early detection of dementia with default-mode network effective connectivity
Ereira, S., Waters, S., Razi, A., & Marshall, C. R. (2024) · Nature Mental Health · doi:10.1038/s44220-024-00259-5 · Cited by 82
Ding, X., Li, C.-Y., Wang, Q.-S., Du, F.-Z., Ke, Z.-W., Peng, F., Wang, J., & Chen, L. (2014) · Neuroscience · doi:10.1016/j.neuroscience.2014.07.060 · Cited by 69
The INTUIT Study: Investigating Neuroinflammation Underlying Postoperative Cognitive Dysfunction
Berger, M., Oyeyemi, D. M., Olurinde, M. O., Whitson, H. E., Weinhold, K. J., Woldorff, M. G., Lipsitz, L. A., Moretti, E., Giattino, C., Roberts, K., et al. (2019) · Journal of the American Geriatrics Society · doi:10.1111/jgs.15770 · Cited by 66
Gene expression parallels synaptic excitability and plasticity changes in Alzheimer’s disease
Saura, C. A., Parra‐Damas, A., & Enríquez-Barreto, L. (2015) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2015.00318 · Cited by 65
de Florès, R., Mutlu, J., Bejanin, A., Gonneaud, J., Landeau, B., Tomadesso, C., Mézenge, F., Sayette, V. D. L., Eustache, F., & Chételat, G. (2017) · Human Brain Mapping · doi:10.1002/hbm.23704 · Cited by 67
Premi, E., Cauda, F., Gasparotti, R., Diano, M., Archetti, S., Padovani, A., & Borroni, B. (2014) · PLoS ONE · doi:10.1371/journal.pone.0106500 · Cited by 73
Kayed, R., Dettmer, U., & Lesné, S. (2020) · Journal of Parkinson s Disease · doi:10.3233/jpd-201965 · Cited by 63
Imaging endpoints for clinical trials in Alzheimer’s disease
Cash, D. M., Rohrer, J. D., Ryan, N. S., Sebastien Ourselin, A., & Fox, N. C. (2014) · Alzheimer s Research & Therapy · doi:10.1186/s13195-014-0087-9 · Cited by 62
Self-citationMulticenter stability of resting state fMRI in the detection of Alzheimer’s disease and amnestic MCI
Teipel, S. J., Wohlert, A., Metzger, C., Grimmer, T., Sorg, C., Ewers, M., Meisenzahl, E., Klöppel, S., Borchardt, V., Grothe, M. J., et al. (2017) · NeuroImage: Clinical · doi:10.1016/j.nicl.2017.01.018 · Cited by 62
Algarín, C. R., Karunakaran, K. D., Reyes, S., Morales, C., Lozoff, B., Peirano, P. D., & Biswal, B. B. (2017) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2017.00054 · Cited by 70
The Molecular and Neuropathological Consequences of Genetic Risk for Alzheimer's Dementia
Tasaki, S., Gaiteri, C., Mostafavi, S., Jager, P. L. D., & Bennett, D. A. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00699 · Cited by 61
Predicting brain age from functional connectivity in symptomatic and preclinical Alzheimer disease
Millar, P. R., Luckett, P. H., Gordon, B. A., Benzinger, T. L. S., Schindler, S. E., Fagan, A. M., Cruchaga, C., Bateman, R. J., Allegri, R., Jucker, M., et al. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119228 · Cited by 60
Self-citationJalilianhasanpour, R., Beheshtian, E., Sherbaf, G., Sahraian, S., & Sair, H. I. (2019) · Topics in Magnetic Resonance Imaging · doi:10.1097/rmr.0000000000000223 · Cited by 57
Brain properties predict proximity to symptom onset in sporadic Alzheimer’s disease
Vogel, J. W., Vachon‐Presseau, É., Binette, A. P., Tam, A., Orban, P., Joie, R. L., Savard, M., Picard, C., Poirier, J., Bellec, P., et al. (2018) · Brain · doi:10.1093/brain/awy093 · Cited by 52
Functional neuroimaging findings in healthy middle-aged adults at risk of Alzheimer’s disease
Habib, M., Mak, E., Gabel, S., Su, L., Williams, G., Waldman, A., Wells, K., Ritchie, K., Ritchie, C., & O’Brien, J. T. (2017) · Ageing Research Reviews · doi:10.1016/j.arr.2017.03.004 · Cited by 53
Noradrenergic Dysfunction in Alzheimer's and Parkinson's Diseases—An Overview of Imaging Studies
Peterson, A. C., & Li, C. R. (2018) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2018.00127 · Cited by 58
Neuroimaging in aging and neurologic diseases
Risacher, S. L., & Saykin, A. J. (2019) · Handbook of clinical neurology · doi:10.1016/b978-0-12-804766-8.00012-1 · Cited by 56
Self-citationDisruption of Resting Functional Connectivity in Alzheimer’s Patients and At-Risk Subjects
Krajčovičová, L., Mareček, R., Mikl, M., & Rektorová, I. (2014) · Current Neurology and Neuroscience Reports · doi:10.1007/s11910-014-0491-3 · Cited by 51
Pievani, M., Pini, L., Ferrari, C., Pizzini, F. B., Galazzo, I. B., Cobelli, C., Cotelli, M., Manenti, R., & Frisoni, G. B. (2017) · Journal of Alzheimer s Disease · doi:10.3233/jad-161105 · Cited by 52
Breakdown of specific functional brain networks in clinical variants of Alzheimer’s disease
Pini, L., Wennberg, A. M. V., Salvalaggio, A., Vallesi, A., Pievani, M., & Corbetta, M. (2021) · Ageing Research Reviews · doi:10.1016/j.arr.2021.101482 · Cited by 48
Clinical, biological, and imaging features of monogenic Alzheimer’s disease
Pilotto, A., Padovani, A., & Borroni, B. (2013) · BioMed Research International · doi:10.1155/2013/689591 · Cited by 47
McKay, N. S., Gordon, B. A., Hornbeck, R. C., Dincer, A., Flores, S. E., Keefe, S., Joseph‐Mathurin, N., Jack, C. R., Koeppe, R. A., Millar, P. R., et al. (2023) · Nature Neuroscience · doi:10.1038/s41593-023-01359-8 · Cited by 44
Self-citationGoing round in circles—The Papez circuit in Alzheimer's disease
Forno, G., Lladó, A., & Hornberger, M. (2021) · European Journal of Neuroscience · doi:10.1111/ejn.15494 · Cited by 47
Functional Connectivity in Patients With Sensorineural Hearing Loss Using Resting-State MRI
Liu, B., Feng, Y., Yang, M., Chen, J.-Y., Li, J., Huang, Z.-C., & Zhang, L. (2015) · American Journal of Audiology · doi:10.1044/2015_aja-13-0068 · Cited by 43
Brain Activity: Connectivity, Sparsity, and Mutual Information
Cassidy, B., Rae, C. D., & Solo, V. (2014) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2014.2358681 · Cited by 42
Differential effects of Down's syndrome and Alzheimer's neuropathology on default mode connectivity
Wilson, L. R., Vatansever, D., Annus, T., Williams, G. B., Hong, Y. T., Fryer, T. D., Nestor, P. J., Holland, A. J., & Zaman, S. H. (2019) · Human Brain Mapping · doi:10.1002/hbm.24720 · Cited by 43
Testing the amyloid cascade hypothesis: Prevention trials in autosomal dominant Alzheimer disease
Levin, J., Vöglein, J., Quiroz, Y. T., Bateman, R. J., Ghisays, V., Lopera, F., McDade, E., Reiman, E., Tariot, P. N., & Morris, J. C. (2022) · Alzheimer's & Dementia · doi:10.1002/alz.12624 · Cited by 40
Self-citationRujeedawa, T., Félez, E. C., Clare, I. C. H., Fortea, J., Strydom, A., Rebillat, A., Coppus, A. M. W., Levin, J., & Zaman, S. H. (2021) · Journal of Clinical Medicine · doi:10.3390/jcm10194582 · Cited by 43
Epicentral Disruption of Structural Connectivity in Alzheimer's Disease
Mallio, C. A., Schmidt, R., de Reus, M. A., Vernieri, F., Quintiliani, L., Curcio, G., Beomonte Zobel, B., Quattrocchi, C. C., & van den Heuvel, M. P. (2015) · CNS Neuroscience & Therapeutics · doi:10.1111/cns.12397 · Cited by 39
Harrison, T. M., Burggren, A. C., Small, G. W., & Bookheimer, S. Y. (2015) · Human Brain Mapping · doi:10.1002/hbm.23036 · Cited by 38
Revolution of Resting-State Functional Neuroimaging Genetics in Alzheimer’s Disease
Chiesa, P. A., Cavedo, E., Lista, S., Thompson, P. M., & Hampel, H. J. (2017) · Trends in Neurosciences · doi:10.1016/j.tins.2017.06.002 · Cited by 35
Self-citationAltered functional connectivity in patients with post-stroke memory impairment: A resting fMRI study
Liu, J., Wang, Q., Liu, F.-W., Song, H.-Y., Liang, X.-F., Lin, Z., Hong, W.-J., Yang, S.-L., Huang, J., Zheng, G.-H., et al. (2017) · Experimental and Therapeutic Medicine · doi:10.3892/etm.2017.4751 · Cited by 32
Kucikova, L., Goerdten, J., Dounavi, M., Mak, E., Su, L., Waldman, A. D., Danso, S., Terrera, G. M., & Ritchie, C. W. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.07.024 · Cited by 42
Zhurakovskaya, E., Ishchenko, I., Gureviciene, I., Алиев, Р. Р., Gröhn, O. H. J., & Tanila, H. (2019) · Scientific Reports · doi:10.1038/s41598-019-41851-5 · Cited by 37
Quevenco, F. C., Bergen, J. M. G. V., Treyer, V., Studer, S. T., Kagerer, S. M., Meyer, R., Gietl, A. F., Kaufmann, P. A., Nitsch, R. M., Höck, C., et al. (2020) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2020.00046 · Cited by 34
Kim, J., & Kim, Y. (2021) · Biomedicines · doi:10.3390/biomedicines9010082 · Cited by 36
Yan, Y., Gao, M., Geng, Z., Wu, Y., Xiao, G., Wang, L., Pang, X., Yang, C., Zhou, S., Li, H., et al. (2024) · GeroScience · doi:10.1007/s11357-024-01181-5 · Cited by 37
Broestl, L., Worden, K., Moreno, A. J., Davis, E. J., Wang, D., Garay, B. I., Singh, T., Verret, L., Palop, J. J., & Dubal, D. B. (2018) · eNeuro · doi:10.1523/eneuro.0132-17.2018 · Cited by 35
Schultz, A. P., Buckley, R. F., Hampton, O. L., Scott, M. R., Properzi, M. J., Peña-Gómez, C., Pruzin, J. J., Yang, H., Johnson, K. A., Sperling, R. A., et al. (2019) · NeuroImage Clinical · doi:10.1016/j.nicl.2019.102052 · Cited by 34
Self-citationWheelock, M. D., Strain, J. F., Mansfield, P. K., Tu, J. C., Tanenbaum, A., Preische, O., Chhatwal, J. P., Cash, D. M., Cruchaga, C., Fagan, A. M., et al. (2023) · Brain · doi:10.1093/brain/awac498 · Cited by 31
Self-citationPreserved Modular Network Organization in the Sedated Rat Brain
D'Souza, D. V., Jonckers, E., Bruns, A., Künnecke, B., von Kienlin, M., der Linden, A. V., Mueggler, T., & Verhoye, M. (2014) · PLoS ONE · doi:10.1371/journal.pone.0106156 · Cited by 30
Tu, Y., Wei, Y., Sun, K., Zhao, W., & Yu, B. (2015) · PLoS ONE · doi:10.1371/journal.pone.0116849 · 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
Neumann, U., Machauer, R., & Shimshek, D. R. (2019) · British Journal of Pharmacology · doi:10.1111/bph.14582 · Cited by 27
Disrupted topological organization of structural brain networks in childhood absence epilepsy
Qiu, W., Yu, C., Gao, Y., Miao, A., Tang, L., Huang, S., Jiang, W., Sun, J., Xiang, J., & Wang, X. (2017) · Scientific Reports · doi:10.1038/s41598-017-10778-0 · Cited by 28
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
Alderson, T. H., Kehoe, E. G., Maguire, L., Farrell, D., LAWLOR, B. A., Kenny, R. A., Lyons, D., Bokde, A. L. W., & Coyle, D. (2017) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2017.00370 · Cited by 27
Su, Y. Y., Zhang, X. D., Schoepf, U. J., Varga‐Szemes, Á., Stubenrauch, A. C., Liang, X., Zheng, L. J., Zheng, G., Kong, X., Xu, Q., et al. (2016) · Brain Imaging and Behavior · doi:10.1007/s11682-016-9556-z · Cited by 25
Zheng, L. J., Su, Y. Y., Wang, Y. F., Schoepf, U. J., Varga‐Szemes, Á., Pannell, J. T., Liang, X., Zheng, G., Lu, G., Yang, G. F., et al. (2017) · Molecular Neurobiology · doi:10.1007/s12035-017-0540-4 · Cited by 26
Cingulate-centered large-scale networks: Normal functions, aging, and neurodegenerative disease
Touroutoglou, A., & Dickerson, B. C. (2019) · Handbook of clinical neurology · doi:10.1016/b978-0-444-64196-0.00008-x · Cited by 23
Wisch, J. K., Roe, C. M., Babulal, G. M., Schindler, S. E., Fagan, A. M., Benzinger, T. L. S., Morris, J. C., & Ances, B. M. (2020) · Journal of Alzheimer s Disease · doi:10.3233/jad-191039 · Cited by 25
Self-citationDistinct regional vulnerability to Aβ and iron accumulation in post mortem AD brains
Yao, J., Li, Z., Zhou, Z., Bao, A., Wang, Z., Wei, H., & He, H. (2024) · Alzheimer s & Dementia · doi:10.1002/alz.14188 · Cited by 27
Shang, Y., Hinkley, L. B. N., Cai, C., Mizuiri, D., Cheung, S. W., & Nagarajan, S. S. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116376 · Cited by 24
Huang, C., Hsu, S., Tsai, S., Chen, N.-C., Liu, M., Lee, C., Huang, S., Chang, W.-N., Chang, Y., Tsai, W., et al. (2017) · Journal of Neuroinflammation · doi:10.1186/s12974-017-0791-z · Cited by 23
APOE ε 4 and resting‐state functional connectivity in racially/ethnically diverse older adults
Turney, I. C., Chesebro, A. G., Rentería, M. A., Lao, P. J., Beato, J. M., Schupf, N., Mayeux, R. P., Manly, J. J., & Brickman, A. M. (2020) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1002/dad2.12094 · Cited by 25
Self-citationSmith, R. X., Strain, J. F., Tanenbaum, A., Fagan, A. M., Hassenstab, J. J., McDade, E., Schindler, S. E., Gordon, B. A., Xiong, C., Chhatwal, J. P., et al. (2021) · Brain Connectivity · doi:10.1089/brain.2020.0808 · Cited by 25
Self-citationShi, Y., Wang, Z., Chen, P., Cheng, P., Zhao, K., Zhang, H., Shu, H., Gu, L., Gao, L., Wáng, Q., et al. (2020) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2020.12.007 · Cited by 22
Çelebi, Ö. Ö., Uzdoğan, A., Oğuz, K. K., Has, A. C., Dolgun, A., Çakmaklı, G. Y., Akbıyık, F., Elibol, B., & Saka, E. (2015) · Archives of Gerontology and Geriatrics · doi:10.1016/j.archger.2015.09.010 · Cited by 21
Promteangtrong, C., Kolber, M., Ramchandra, P., Moghbel, M. C., Houshmand, S., Schöll, M., Bai, H., Werner, T. J., Alavi, A. A., & Buchpiguel, C. A. (2015) · Dementia & Neuropsychologia · doi:10.1590/1980-57642015dn94000318 · Cited by 21
Falls Associate with Neurodegenerative Changes in ATN Framework of Alzheimer’s Disease
Keleman, A. A., Wisch, J. K., Bollinger, R. M., Grant, E., Benzinger, T. L. S., Morris, J. C., Ances, B. M., & Stark, S. L. (2020) · Journal of Alzheimer s Disease · doi:10.3233/jad-200192 · Cited by 23
Self-citationKulkarni, P., Grant, S. E., Morrison, T. R., Cai, X., Iriah, S. C., Kristal, B. S., Honeycutt, J. A., Brenhouse, H. C., Hartner, J. C., Madularu, D., et al. (2020) · Brain Research · doi:10.1016/j.brainres.2020.147030 · Cited by 19
Prescott, J. W., Doraiswamy, P. M., Gamberger, D., Benzinger, T. L. S., Petrella, J. R., & for the Dominantly Inherited Alzheimer Network (2021) · Radiology · doi:10.1148/radiol.2021210383 · Cited by 21
Self-citationMultivariate brain network graph identification in functional MRI
Aggarwal, P., Gupta, A., & Garg, A. K. (2017) · Medical Image Analysis · doi:10.1016/j.media.2017.08.007 · Cited by 20
Chang, C., Chang, Y., Huang, C., Tsai, S., Hsu, S., Huang, S., Lee, C., Chang, W., Lui, C., & Lien, C.-Y. (2018) · Alzheimer s Research & Therapy · doi:10.1186/s13195-018-0344-4 · Cited by 19
Lin, P., Tsai, S., Huang, C., Liu, M., Hsu, S., Lee, C., Chen, N.-C., Chang, Y., Lan, M., & Chang, C. (2016) · Oncotarget · doi:10.18632/oncotarget.11027 · Cited by 18
Effects of Homocysteine on white matter diffusion parameters in Alzheimer’s disease
Lee, C., Hsu, S., Huang, C., Chang, W., Chen, S.-F., Wu, M., Chang, C., Hwang, L.-C., & Chen, P.-C. (2017) · BMC Neurology · doi:10.1186/s12883-017-0970-7 · Cited by 18
Metadata
- Authors
- Chhatwal, J. P., Schultz, A. P., Johnson, K., Benzinger, T. L. S., Jack, C., Ances, B. M., Sullivan, C. A., Salloway, S. P., Ringman, J. M., Koeppe, R. A., Marcus, D. S., Thompson, P., Saykin, A. J., Correia, S., Schofield, P. R., Rowe, C. C., Fox, N. C., Brickman, A. M., Mayeux, R., McDade, E., Bateman, R., Fagan, A. M., Goate, A. M., Xiong, C., Buckles, V. D., Morris, J. C., & Sperling, R. A.
- Affiliations
- Harvard University (US)
- From the Departments of Neurology (J.P.C., A.P.S., K.J., C.A.S., R.A.S.) and Radiology (K.J.), and Martinos Center for Biomedical Imaging (J.P.C., A.P.S., K.J., C.A.S., R.A.S.), Massachusetts General Hospital, Harvard Medical School, Boston; Department of Radiology, Section of Neuroradiology (T.L.S.B., D.S.M.), Mallinckrodt Institute of Radiology (T.L.S.B., B.M.A., D.S.M.), Departments of Neurology (B.M.A., R.B., A.M.F., V.D.B., J.C.M.), Genetics (A.M.G.), and Psychiatry (A.M.G.), and Division of...
- ORCID
- Chhatwal, Jasmeer P.
- Schultz, Aaron P.
- Johnson, Keith
- Benzinger, Tammie L.S.
- Jack, Clifford
- Ances, Beau M.
- Salloway, Stephen P.
- Ringman, John M.
- Koeppe, Robert A.
- Marcus, Daniel S.
- Thompson, Paul
- Saykin, Andrew J.
- Correia, Stephen
- Schofield, Peter R.
- Fox, Nick C.
- Brickman, Adam M.
- Mayeux, Richard
- McDade, Eric
- Bateman, Randall
- Fagan, Anne M.
- Xiong, Chengjie
- Morris, John C.
- Sperling, Reisa A.
- Venue
- Neurology
- Published
- 2013-08-20
- Volume
- 81
- Issue
- 8
- Pages
- 736-744
- ISSN
- 0028-3878 (ISSN-L)
- 1526-632X
- PMC
- PMC3776464
- OpenAlex
- W2165942026
- Cited by
- 179
- References
- 42
- Citations by year
- 2026: 2 · 2025: 7 · 2024: 8 · 2023: 10 · 2022: 10 · 2021: 14 · 2020: 11 · 2019: 33 · 2018: 18 · 2017: 19 · 2016: 10 · 2015: 12 · 2014: 24 · 2013: 1
- FWCI
- 8.59
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Neurology (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- National Institute for Health and Care Research (NF-SI-0508-10123)
- National Institute on Aging (K24AG035007, P50AG005134, U19AG032438, U24AG021886, P30AG062421)
- National Institute of Nursing Research (R01NR012657)
- National Institute of Neurological Disorders and Stroke (P30NS048056)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- 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
- Keywords
- autosomal dominant Alzheimer's disease, default mode network, functional connectivity, presenilin 1 mutations, amyloid precursor protein mutations, mutation carriers, asymptomatic carriers, precuneus, posterior cingulate cortex, parietal cortex, Clinical Dementia Rating, early biomarkers
- MeSH terms
- Adult, Alzheimer Disease, Brain, Female, Genes, Dominant, Heterozygote, Humans, Male, Nerve Net, Prevalence, Amyloid beta-Protein Precursor, Genetic Predisposition to Disease, Internationality, Presenilin-1, Presenilin-2, Connectome
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
