The DOI matches its Crossref record; 72 of the 73 references it cites were found in a registry or an index.
Intrinsic connectivity networks in healthy subjects explain clinical variability in Alzheimer’s disease
Open accessAbstract
Although previous studies have emphasized the vulnerability of the default mode network (DMN) in Alzheimer’s disease (AD), little is known about the involvement of other functional networks and their relationship to clinical phenotype. To test whether clinicoanatomic heterogeneity in AD is driven by the involvement of specific networks, network connectivity was assessed in healthy subjects by seeding regions commonly and specifically atrophied in three clinical AD variants: early-onset AD (age at onset, <65 y; memory and executive deficits), logopenic variant primary progressive aphasia (language deficits), and posterior cortical atrophy (visuospatial deficits). Four-millimeter seed regions of interest were used to obtain intrinsic connectivity maps in 131 healthy controls (age, 65.5 ± 3.5 y). Atrophy patterns in independent cohorts of AD variant patients and their correspondence to connectivity networks in controls were also assessed. The connectivity maps of commonly atrophied regions of interest support posterior DMN and precuneus network involvement across AD variants, whereas seeding regions specifically atrophied in each AD variant revealed distinct, syndrome-specific connectivity patterns. Goodness-of-fit analysis of each connectivity map with network templates showed the highest correspondence between the early-onset AD seed connectivity map and anterior salience and right executive-control networks, the logopenic aphasia seed connectivity map and the language network, and the posterior cortical atrophy seed connectivity map and the higher visual network. Connectivity maps derived from controls matched regions commonly and specifically atrophied in the patients. Our findings indicate that the posterior DMN and precuneus network are commonly affected in AD variants, whereas syndrome-specific neurodegenerative patterns are driven by the involvement of specific networks outside the DMN.
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
“An alternative explanation is that Aβ accumulation is caused by the high metabolic demand and metabolic stress in these neurons (high energy consumption and frequent fluctuations in activation and deactivation) and not the neuronal activation per se30.”
From Earliest accumulation of β-amyloid occurs within the default-mode network and concurrently affects brain connectivity (2017) · cites this paper as [30]
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Previous research has demonstrated lower connectivity among regions involved in specific brain networks of patients with AD, including the default mode network (Bai et al., 2011; Damoiseaux, Prater, Miller, & Greicius, 2012; Lehmann et al., 2013; Simic, Babic, Borovecki, & Hof, 2014).”
From Functional and structural connectome properties in the 5XFAD transgenic mouse model of Alzheimer’s disease (2018) · cites this paper as Lehmann 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
McKhann, G. M., Knopman, D. S., Chertkow, H., Hyman, B. T., Jack, C. R., Kawas, C. H., Klunk, W. E., Koroshetz, W. J., Manly, J. J., Mayeux, R., et al. (2011) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2011.03.005 · Cited by 18,657
Neuropathological stageing of Alzheimer-related changes.
Braak, H., & Braak, E. (1991) · Acta Neuropathologica · doi:10.1007/bf00308809 · Cited by 16,123 · cited 2×
“J Neuropsychiatry Clin Neurosci 22(1):iv–, 1–7.”
BackgroundA 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
The Brain's Default Network: Anatomy, Function, and Relevance to Disease
Buckner, R. L., Andrews‐Hanna, J. R., & Schacter, D. L. (2008) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1440.011 · Cited by 9,761
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
Functional 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
Self-citationThe precuneus: a review of its functional anatomy and behavioural correlates
Cavanna, A. E., & Trimble, M. R. (2006) · Brain · doi:10.1093/brain/awl004 · Cited by 5,128
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
Self-citationGusnard, D. A., Akbudak, E., Shulman, G. L., & Raichle, M. E. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.071043098 · Cited by 2,997
Buckner, R. L., Sepulcre, J., Talukdar, T., Krienen, F. M., Liu, H., Hedden, T., Andrews-Hanna, J. R., Sperling, R. A., & Johnson, K. A. (2009) · The Journal of Neuroscience · doi:10.1523/jneurosci.5062-08.2009 · Cited by 2,862
Cited by
Sorted by citations
Palmqvist, S., Schöll, M., Strandberg, O., Mattsson, N., Stomrud, E., Zetterberg, H., Blennow, K., Landau, S., Jagust, W., & Hansson, O. (2017) · Nature Communications · doi:10.1038/s41467-017-01150-x · Cited by 911
Self-citationMemory loss in Alzheimer's disease
Jahn, H. (2013) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2013.15.4/hjahn · Cited by 653
Imaging the evolution and pathophysiology of Alzheimer disease
Jagust, W. (2018) · Nature Reviews Neuroscience · doi:10.1038/s41583-018-0067-3 · Cited by 604
Self-citationOssenkoppele, R., Pijnenburg, Y. A. L., Perry, D. C., Cohn-Sheehy, B. I., Scheltens, N. M. E., Vogel, J. W., Kramer, J. H., van der Vlies, A. E., Joie, R. L., Rosen, H. J., et al. (2015) · Brain · doi:10.1093/brain/awv191 · Cited by 548
Self-citationA clinicopathological approach to the diagnosis of dementia
Elahi, F. M., & Miller, B. L. (2017) · Nature Reviews Neurology · doi:10.1038/nrneurol.2017.96 · Cited by 425
Self-citationMendez, M. F. (2017) · Neurologic Clinics · doi:10.1016/j.ncl.2017.01.005 · Cited by 389
Brain 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
Interpreting and Utilising Intersubject Variability in Brain Function
Seghier, M. L., & Price, C. J. (2018) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2018.03.003 · Cited by 306
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
Atrophy patterns in early clinical stages across distinct phenotypes of Alzheimer's disease
Ossenkoppele, R., Cohn‐Sheehy, B. I., La Joie, R., Vogel, J. W., Möller, C., Lehmann, M., van Berckel, B. N. M., Seeley, W. W., Pijnenburg, Y. A., Gorno‐Tempini, M. L., et al. (2015) · Human Brain Mapping · doi:10.1002/hbm.22927 · Cited by 243
Self-citationNetwork 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
Yu, M., Engels, M. M. A., Hillebrand, A., van Straaten, E. C. W., Gouw, A. A., Teunissen, C. E., van der Flier, W. M., Scheltens, P., & Stam, C. J. (2017) · Brain · doi:10.1093/brain/awx050 · Cited by 165
Joie, R. L., Landeau, B., Perrotin, A., Bejanin, A., Egret, S., Pèlerin, A., Mézenge, F., Belliard, S., Sayette, V. D. L., Eustache, F., et al. (2014) · Neuron · doi:10.1016/j.neuron.2014.01.026 · Cited by 165
Network localization of heterogeneous neuroimaging findings
Darby, R. R., Joutsa, J., & Fox, M. (2018) · Brain · doi:10.1093/brain/awy292 · Cited by 160
Grothe, M. J., Teipel, S. J., & Initiative, F. T. A. D. N. (2016) · Human Brain Mapping · doi:10.1002/hbm.23018 · Cited by 150
Wang, P., Zhou, B., Yao, H., Zhan, Y., Zhang, Z., Cui, Y. J., Xu, K., Ma, J., Wang, L., An, N., et al. (2015) · Scientific Reports · doi:10.1038/srep14824 · Cited by 148
Gorges, M., Müller, H., Lulé, D. E., Pinkhardt, E. H., Ludolph, A. C., & Kassubek, J. (2015) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2014.12.026 · Cited by 134
Within-patient correspondence of amyloid-β and intrinsic network connectivity in Alzheimer’s disease
Myers, N., Pasquini, L., Göttler, J., Grimmer, T., Koch, K., Ortner, M., Neitzel, J., Mühlau, M., Förster, S., Kurz, A., et al. (2014) · Brain · doi:10.1093/brain/awu103 · Cited by 132
“Since our model predicts that the same mechanism governs amyloid-b-related neurodegeneration, irrespective of the affected network, it should also apply to other variants of Alzheimer’s disease, such as posterior cortical atrophy or logopenic primary progressive aphasia (Lehmann et al., 2013a, b).”
Teipel, S. J., Grothe, M. J., Zhou, J. H., Sepulcre, J., Dyrba, M., Sorg, C., & Babiloni, C. (2016) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617715000995 · Cited by 117
Network localization of clinical, cognitive, and neuropsychiatric symptoms in Alzheimer’s disease
Tetreault, A. M., Phan, T. X., Orlando, D., Lyu, I., Kang, H., Landman, B. A., Darby, R. R., & Initiative, O. B. O. A. D. N. (2020) · Brain · doi:10.1093/brain/awaa058 · Cited by 118
Oh, H., Madison, C. M., Baker, S. L., Rabinovici, G. D., & Jagust, W. J. (2016) · Brain · doi:10.1093/brain/aww108 · Cited by 113
Self-citationMapping Neurodegenerative Disease Onset and ProgressionPreprint
Seeley, W. W. (2017) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a023622 · Cited by 109
Self-citationOssenkoppele, R., Iaccarino, L., Schonhaut, D. R., Brown, J. A., Joie, R. L., O’Neil, J. P., Janabi, M., Baker, S. L., Kramer, J. H., Gorno‐Tempini, M., et al. (2019) · NeuroImage Clinical · doi:10.1016/j.nicl.2019.101848 · Cited by 109
Self-citationWhitwell, J. L., Jones, D. T., Duffy, J. R., Strand, E. A., Machulda, M. M., Przybelski, S. A., Vemuri, P., Gregg, B. E., Gunter, J. L., Senjem, M. L., et al. (2014) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2014.12.013 · Cited by 102
Preferential 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
Hansson, O., Grothe, M. J., Strandberg, T. O., Ohlsson, T. G., Hägerström, D., Jögi, J., Smith, R. A., & Schöll, M. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00167 · Cited by 102
Pathoconnectomics of cognitive impairment in small vessel disease: A systematic review
Dey, A., Stamenova, V., Turner, G. R., Black, S. E., & Levine, B. (2016) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2016.01.007 · Cited by 99
Mapping the Progression of Atrophy in Early- and Late-Onset Alzheimer’s Disease
Migliaccio, R., Agosta, F., Possin, K. L., Canu, E., Filippi, M., Rabinovici, G. D., Rosen, H. J., Miller, B. L., & Gorno‐Tempini, M. L. (2015) · Journal of Alzheimer s Disease · doi:10.3233/jad-142292 · Cited by 97
Self-citationMolecular imaging in dementia: Past, present, and future
Laforce, R. J., Soucy, J., Sellami, L., Dallaire‐Théroux, C., Brunet, F., Bergeron, D., Miller, B. L., & Ossenkoppele, R. (2018) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2018.06.2855 · Cited by 88
Self-citationPrimary progressive aphasia: a model for neurodegenerative disease
Tee, B. L., & Gorno‐Tempini, M. L. (2019) · Current Opinion in Neurology · doi:10.1097/wco.0000000000000673 · Cited by 81
Self-citationLehmann, M., Madison, C. M., Ghosh, P. M., Miller, Z., Greicius, M. D., Kramer, J. H., Coppola, G., Miller, B. L., Jagust, W. J., Gorno‐Tempini, M. L., et al. (2015) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2015.06.029 · Cited by 79
Self-citationZhan, Y., Initiative, A. D. N., Ma, J., Alexander‐Bloch, A. F., Xu, K., Cui, Y. J., Feng, Q., Jiang, T., & Liu, Y. (2016) · Journal of Alzheimer s Disease · doi:10.3233/jad-160008 · Cited by 78
Understanding the cause of sporadic Alzheimer’s disease
Zetterberg, H., & Mattsson, N. (2014) · Expert Review of Neurotherapeutics · doi:10.1586/14737175.2014.915740 · Cited by 73
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
Parallel ICA of FDG-PET and PiB-PET in three conditions with underlying Alzheimer's pathology
Laforce, R. J., Tosun, D., Ghosh, P. M., Lehmann, M., Madison, C. M., Weiner, M. W., Miller, B. L., Jagust, W. J., & Rabinovici, G. D. (2014) · NeuroImage Clinical · doi:10.1016/j.nicl.2014.03.005 · Cited by 75
Self-citationSintini, I., Graff‐Radford, J., Jones, D. T., Botha, H., Martin, P. R., Machulda, M. M., Schwarz, C. G., Senjem, M. L., Gunter, J. L., Jack, C. R., et al. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa319 · Cited by 74
Selective vulnerability in neurodegeneration: insights from clinical variants of Alzheimer's disease
Mattsson, N., Schott, J. M., Hardy, J., Turner, M. R., & Zetterberg, H. (2016) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp-2015-311321 · Cited by 72
Schulz, M., Malherbe, C., Cheng, B., Thomalla, G., & Schlemm, E. (2021) · BMC Medicine · doi:10.1186/s12916-021-01962-1 · Cited by 71
White Matter Degeneration in Atypical Alzheimer Disease
Caso, F., Agosta, F., Mattavelli, D., Migliaccio, R., Canu, E., Magnani, G., Marcone, A., Copetti, M., Falautano, M., Comı, G., et al. (2015) · Radiology · doi:10.1148/radiol.2015142766 · Cited by 69
Auditory spatial processing in Alzheimer’s disease
Golden, H. L., Nicholas, J. M., Yong, K. X. X., Downey, L. E., Schott, J. M., Mummery, C. J., Crutch, S. J., & Warren, J. D. (2014) · Brain · doi:10.1093/brain/awu337 · Cited by 70
Chen, J., Shu, H., Wang, Z., Zhan, Y., Liu, D., Liao, W., Xu, L., Liu, Y., & Zhang, Z. (2016) · Cortex · doi:10.1016/j.cortex.2016.08.001 · Cited by 65
Tau and atrophy: domain-specific relationships with cognition
Initiative, A. D. N., Digma, L. A., Madsen, J. R., Reas, E. T., Dale, A. M., Brewer, J. B., & Banks, S. J. (2019) · Alzheimer s Research & Therapy · doi:10.1186/s13195-019-0518-8 · Cited by 66
Jalilianhasanpour, R., Beheshtian, E., Sherbaf, G., Sahraian, S., & Sair, H. I. (2019) · Topics in Magnetic Resonance Imaging · doi:10.1097/rmr.0000000000000223 · Cited by 57
Agosta, F., Weiler, M., & Filippi, M. (2015) · CNS Neuroscience & Therapeutics · doi:10.1111/cns.12410 · Cited by 56
Uchihara, T. (2016) · Neuropathology · doi:10.1111/neup.12348 · Cited by 55
Amyloid Imaging in Atypical Presentations of Alzheimer’s Disease
Wolk, D. A. (2013) · Current Neurology and Neuroscience Reports · doi:10.1007/s11910-013-0412-x · Cited by 54
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
Therriault, J., Pascoal, T. A., Savard, M., Mathotaarachchi, S. S., Benedet, A. L., Chamoun, M., Tissot, C., Lussier, F. Z., Rahmouni, N., Stevenson, J., et al. (2022) · Science Translational Medicine · doi:10.1126/scitranslmed.abc8693 · Cited by 58
Klupp, E., Grimmer, T., Tahmasian, M., Sorg, C., Yakushev, I. Y., Yousefi, B. H., Drzezga, A. E., & Förster, S. (2015) · Journal of Nuclear Medicine · doi:10.2967/jnumed.114.149302 · Cited by 53
Dickerson, B. C., Brickhouse, M. J., McGinnis, S. M., Wolk, D. A., & Initiative, A. D. N. (2016) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1016/j.dadm.2016.12.007 · Cited by 55
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
Sun, N., Mormino, E. C., Chen, J., Sabuncu, M. R., & Yeo, B. T. T. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116043 · Cited by 47
Self-citationWeiler, M., Agosta, F., Canu, E., Copetti, M., Magnani, G., Marcone, A., Pagani, E., Balthazar, M. L. F., Comı, G., Falini, A., et al. (2015) · Journal of Alzheimer s Disease · doi:10.3233/jad-150196 · Cited by 40
Disruptions of the olfactory and default mode networks in Alzheimer's disease
Lu, J., Yang, Q. X., Zhang, H., Eslinger, P. J., Zhang, X., Wu, S., Zhang, B., Zhu, B., & Karunanayaka, P. (2019) · Brain and Behavior · doi:10.1002/brb3.1296 · Cited by 40
Regional associations of white matter hyperintensities and early cortical amyloid pathology
Lorenzini, L., Ansems, L. T., Lopes Alves, I., Ingala, S., Vállez García, D., Tomassen, J., Sudre, C., Salvadó, G., Shekari, M., Operto, G., et al. (2022) · Brain Communications · doi:10.1093/braincomms/fcac150 · Cited by 36
Sitnikova, T., Hughes, J. W., Ahlfors, S. P., Woolrich, M. W., & Salat, D. H. (2018) · NeuroImage Clinical · doi:10.1016/j.nicl.2018.05.028 · Cited by 37
Anterior dorsal attention network tau drives visual attention deficits in posterior cortical atrophy
Katsumi, Y., Putcha, D., Eckbo, R., Wong, B., Quimby, M., McGinnis, S. M., Touroutoglou, A., & Dickerson, B. C. (2022) · Brain · doi:10.1093/brain/awac245 · Cited by 37
Small vessel disease is linked to disrupted structural network covariance in Alzheimer's disease
Nestor, S. M., Mišić, B., Ramirez, J., Zhao, J., Graham, S. J., Verhoeff, N. P. L. G., Stuss, D. T., Masellis, M., & Black, S. E. (2017) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2016.12.007 · Cited by 37
Tract-defined regional white matter hyperintensities and memory
Rizvi, B. M., Lao, P. J., Colón, J. M., Hale, C., Igwe, K. C., Narkhede, A., Budge, M., Manly, J. J., Schupf, N., & Brickman, A. M. (2019) · NeuroImage Clinical · doi:10.1016/j.nicl.2019.102143 · Cited by 37
Kesler, S. R., Acton, P., Rao, V., & Ray, W. J. (2018) · Network Neuroscience · doi:10.1162/netn_a_00048 · Cited by 34
“Previous research has demonstrated lower connectivity among regions involved in specific brain networks of patients with AD, including the default mode network (Bai et al., 2011; Damoiseaux, Prater, Miller, & Greicius, 2012; Lehmann et al., 2013; Simic, Babic, Borovecki, & Hof, 2014).”
BackgroundCarroll, C. M., & Macauley, S. L. (2019) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2019.00258 · Cited by 32
Agosta, F., Mandić‐Stojmenović, G., Canu, E., Stojković, T., Imperiale, F., Caso, F., Stefanova, E. D., Copetti, M., Kostić, V., & Filippi, M. (2018) · NeuroImage Clinical · doi:10.1016/j.nicl.2018.06.013 · 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
Klupp, E., Förster, S., Grimmer, T., Tahmasian, M., Yakushev, I. Y., Sorg, C., Yousefi, B. H., & Drzezga, A. E. (2014) · Brain Connectivity · doi:10.1089/brain.2013.0212 · Cited by 31
Effects of bilingualism on age at onset in two clinical Alzheimer's disease variants
de Leon, J., Grasso, S. M., Welch, A. E., Miller, Z., Shwe, W., Rabinovici, G. D., Miller, B. L., Henry, M. L., & Gorno‐Tempini, M. L. (2020) · Alzheimer s & Dementia · doi:10.1002/alz.12170 · Cited by 34
Self-citationLowe, A. J., Paquola, C., de Wael, R. V., Girn, M., Larivière, S., Tavakol, S., Caldairou, B., Royer, J., Schrader, D. V., Bernasconi, A., et al. (2019) · Human Brain Mapping · doi:10.1002/hbm.24767 · Cited by 30
Network anatomy in logopenic variant of primary progressive aphasia
Mandelli, M. L., Lorca‐Puls, D. L., Lukic, S., Montembeault, M., Gajardo‐Vidal, A., Licata, A. E., Scheffler, A., Battistella, G., Grasso, S. M., Bogley, R., et al. (2023) · Human Brain Mapping · doi:10.1002/hbm.26388 · Cited by 30
Self-citationVulnerability of multiple large‐scale brain networks in dementia with Lewy bodies
Sala, A., Caminiti, S. P., Iaccarino, L., Beretta, L., Iannaccone, S., Magnani, G., Padovani, A., Ferini‐Strambi, L., & Perani, D. (2019) · Human Brain Mapping · doi:10.1002/hbm.24719 · Cited by 30
3D Shape Perception in Posterior Cortical Atrophy: A Visual Neuroscience Perspective
Gillebert, C. R., Schaeverbeke, J. M., Bastin, C., Neyens, V., Bruffaerts, R., Weer, A. D., Seghers, A., Sunaert, S. G., Laere, K. V., Versijpt, J. J., et al. (2015) · Journal of Neuroscience · doi:10.1523/jneurosci.3651-14.2015 · Cited by 29
Intrinsic connectivity networks in posterior cortical atrophy: A role for the pulvinar?
Fredericks, C. A., Brown, J. A., Deng, J., Kramer, A., Ossenkoppele, R., Rankin, K. P., Kramer, J. H., Miller, B. L., Rabinovici, G. D., & Seeley, W. W. (2018) · NeuroImage Clinical · doi:10.1016/j.nicl.2018.101628 · Cited by 29
Self-citationIntrinsic 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
Network Localization of Alien Limb in Patients with Corticobasal Syndrome
Tetreault, A. M., Phan, T. X., Petersen, K. J., Claassen, D. O., Neth, B. J., Graff‐Radford, J., Albrecht, F., Fließbach, K., Schneider, A., Synofzik, M., et al. (2020) · Annals of Neurology · doi:10.1002/ana.25901 · Cited by 28
Eldaief, M. C., Brickhouse, M. J., Katsumi, Y., Rosen, H. J., Carvalho, N., Touroutoglou, A., & Dickerson, B. C. (2023) · Brain · doi:10.1093/brain/awad167 · Cited by 25
Altered within- and between-network functional connectivity in atypical Alzheimer’s disease
Singh, N. A., Martin, P. R., Graff‐Radford, J., Sintini, I., Machulda, M. M., Duffy, J. R., Gunter, J. L., Botha, H., Jones, D. T., Lowe, V. J., et al. (2023) · Brain Communications · doi:10.1093/braincomms/fcad184 · Cited by 24
Corriveau‐Lecavalier, N., Gunter, J. L., Kamykowski, M. G., Dicks, E., Botha, H., Kremers, W. K., Graff‐Radford, J., Wiepert, D. A., Schwarz, C. G., Yacoub, E. S., et al. (2023) · Brain Communications · doi:10.1093/braincomms/fcad058 · Cited by 23
Future Directions in Imaging Neurodegeneration
Masdeu, J. C. (2017) · Current Neurology and Neuroscience Reports · doi:10.1007/s11910-017-0718-1 · Cited by 22
Functional brain network centrality is related to APOE genotype in cognitively normal elderly
Wink, A. M., Tijms, B. M., ten Kate, M., Raspor, E., de Munck, J. C., Altena, E., Ecay‐Torres, M., Clerigué, M., Estanga, A., García‐Sebastián, M., et al. (2018) · Brain and Behavior · doi:10.1002/brb3.1080 · Cited by 24
Cha, J., Guffanti, G., Gingrich, J. A., Talati, A., WICKRAMARATNE, P. J., Weissman, M. M., & Posner, J. E. (2017) · Cerebral Cortex · doi:10.1093/cercor/bhx097 · Cited by 21
Initiative, A. D. N., van Hooren, R. W. E., Riphagen, J. M., & Jacobs, H. I. L. (2018) · Alzheimer s Research & Therapy · doi:10.1186/s13195-018-0420-9 · Cited by 19
Chen, J., Shu, H., Wang, Z., Zhan, Y., Liu, D., Liu, Y., & Zhang, Z. (2019) · Brain Imaging and Behavior · doi:10.1007/s11682-019-00098-4 · Cited by 20
Lang, A. E. (2014) · Movement Disorders · doi:10.1002/mds.26105 · Cited by 19
Prodromal posterior cortical atrophy: clinical, neuropsychological, and radiological correlation
Chan, L., Lynch, W., May, M. G. D., Horton, J. C., Miller, B. L., & Rabinovici, G. D. (2013) · Neurocase · doi:10.1080/13554794.2013.860176 · Cited by 16
Self-citationDifferences in topological progression profile among neurodegenerative diseases from imaging data
Garbarino, S., Lorenzi, M., Oxtoby, N. P., Vinke, E. J., Marinescu, R. V., Eshaghi, A., Ikram, M. A., Niessen, W. J., Ciccarelli, O., Barkhof, F., et al. (2019) · eLife · doi:10.7554/elife.49298 · Cited by 16
Anticholinergic Amnesia is Mediated by Alterations in Human Network Connectivity Architecture
Chhatwal, J. P., Schultz, A. P., Hedden, T., Boot, B. P., Wigman, S. E., Rentz, D. M., Johnson, K. A., & Sperling, R. A. (2018) · Cerebral Cortex · doi:10.1093/cercor/bhy214 · Cited by 15
Greicius, M. D. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-800105-9.00016-0 · Cited by 14
Self-citationMethylene blue modulates functional connectivity in the human brain
Rodriguez, P., Singh, A. P., Malloy, K. E., Zhou, W., Barrett, D. W., Franklin, C. G., Altmeyer, W. B., Gutierrez, J. E., Li, J., Heyl, B. L., et al. (2016) · Brain Imaging and Behavior · doi:10.1007/s11682-016-9541-6 · Cited by 13
Chow, T. E., Veziris, C. R., Mundada, N. S., Martinez-Arroyo, A. I., Kramer, J. H., Miller, B. L., Rosen, H. J., Gorno‐Tempini, M. L., Rankin, K. P., Seeley, W. W., et al. (2023) · Journal of Alzheimer s Disease · doi:10.3233/jad-230367 · Cited by 13
Self-citationClinical implications of head trauma in frontotemporal dementia and primary progressive aphasia
Asken, B. M., Bove, J., Bauer, R. M., Tanner, J. A., Casaletto, K. B., Staffaroni, A. M., VandeVrede, L. A., Alosco, M. L., Mez, J., Stern, R. A., et al. (2024) · Alzheimer s Research & Therapy · doi:10.1186/s13195-024-01553-1 · Cited by 9
Self-citationThe Brain Network Hub Degeneration in Alzheimer’s Disease
Jin, S., Wang, J., & Yong He, A. (2024) · Biophysics Reports · doi:10.52601/bpr.2024.230025 · Cited by 11
Shepherd, T. M., & Nayak, G. K. (2019) · Topics in Magnetic Resonance Imaging · doi:10.1097/rmr.0000000000000225 · Cited by 11
Brain State Transition Disruptions in Alzheimer's Disease: Insights from EEG State Dynamics
Razavi, S. M., Tran, T. M., Wilson, S. E., & Khanmohammadi, S. (2025) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi60581.2025.10981035 · Cited by 10
The predictive value of normal EEGs in dementia due to Alzheimer’s disease
Briels, C. T., Stam, C. J., Scheltens, P., & Gouw, A. A. (2021) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.51339 · Cited by 9
Sadeghi, M., Azargoonjahromi, A., Nasiri, H., Yaghoobi, A., Sadeghi, M., Chavoshi, S. S., Baghaeikia, S., Mahzari, N., Valipour, A., Oskouei, R. R., et al. (2024) · Molecular Brain · doi:10.1186/s13041-024-01136-z · Cited by 8
fMRI in Neurodegenerative Diseases: From Scientific Insights to Clinical Applications
Dickerson, B. C., Agosta, F., & Filippi, M. (2016) · Neuromethods · doi:10.1007/978-1-4939-5611-1_23 · Cited by 8
Kim, E.-J., Vatsavayai, S., & Seeley, W. W. (2016) · The Behavioral Neurology of Dementia · doi:10.1017/9781139924771.008 · Cited by 7
Self-citationShen, S., Liu, W., Zhou, M., Yang, R., Li, J., & Zhou, D. (2021) · BMC Neurology · doi:10.1186/s12883-021-02403-5 · Cited by 7
Comparative approximations of criticality in a neural and quantum regime
Bettinger, J. S. (2017) · Progress in Biophysics and Molecular Biology · doi:10.1016/j.pbiomolbio.2017.09.007 · Cited by 6
Low CSF β-amyloid levels predict early regional grey matter atrophy in multiple sclerosis
Pietroboni, A. M., Colombi, A., Carandini, T., Contarino, V. E., Ghezzi, L., Fumagalli, G., Arighi, A., Fenoglio, C., Riz, M. A. D., Triulzi, F. M., et al. (2019) · Multiple Sclerosis and Related Disorders · doi:10.1016/j.msard.2019.101899 · Cited by 8
Speech-language within and between network disruptions in primary progressive aphasia variants
Singh, N. A., Botha, H., Duffy, J. R., Clark, H. M., Utianski, R. L., Machulda, M. M., Graff‐Radford, J., Schwarz, C. G., Petersen, R. C., Lowe, V. J., et al. (2024) · NeuroImage Clinical · doi:10.1016/j.nicl.2024.103639 · Cited by 6
Contributions of connectional pathways to shaping Alzheimer’s disease pathologies
Bougacha, S., Roquet, D., Landeau, B., Saul, E., Naveau, M., Sherif, S., Bejanin, A., Dhénain, M., Raj, A., Vivien, D., et al. (2024) · Brain Communications · doi:10.1093/braincomms/fcae459 · Cited by 6
Metadata
- Authors
- Lehmann, M., Madison, C. M., Ghosh, P. M., Seeley, W. W., Mormino, E., Greicius, M. D., Gorno-Tempini, M. L., Kramer, J. H., Miller, B. L., Jagust, W. J., & Rabinovici, G. D.
- Affiliations
- University of California, San Francisco (US)
- University of California, Berkeley (US)
- Stanford Medicine (US)
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA 94158;
- Lawrence Berkeley National Laboratory (US)
- ORCID
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2013-06-24
- Volume
- 110
- Issue
- 28
- Pages
- 11606-11611
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC3710820
- OpenAlex
- W1999605218
- Cited by
- 122
- References
- 73
- Citations by year
- 2026: 1 · 2025: 6 · 2024: 6 · 2023: 5 · 2022: 4 · 2021: 7 · 2020: 9 · 2019: 17 · 2018: 14 · 2017: 10 · 2016: 15 · 2015: 13 · 2014: 11 · 2013: 4
- FWCI
- 7.83
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Institutional Research Information System (Università degli Studi di Trento) (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- Hellman Family Foundation
- National Institute on Aging (P01 AG1972403, K23AG031861, P01AG019724, R01AG034570, P50AG023501)
- National Institute of Neurological Disorders and Stroke (R01NS073498, R01NS050915)
- 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
- Alzheimer's disease, resting-state networks, default mode network, precuneus, early-onset Alzheimer's disease, logopenic variant primary progressive aphasia, posterior cortical atrophy, brain atrophy, clinical phenotype, salience network, frontoparietal network, language network, healthy controls
- MeSH terms
- Aged, Alzheimer Disease, Brain, Female, Humans, Male, Middle Aged, Nerve Net, Reference Values, Task Performance and Analysis, Cohort Studies
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