The DOI matches its Crossref record; 203 of the 203 references it cites were found in a registry or an index.
Parietal cortex matters in Alzheimer's disease: An overview of structural, functional and metabolic findings
Abstract
Atrophy of the medial temporal lobe, especially the hippocampus and the parahippocampal gyrus, is considered to be the most predictive structural brain biomarker for Alzheimer's Dementia (AD). However, recent neuroimaging studies reported a possible mismatch between structural and metabolic findings, showing medial temporal lobe atrophy and medial parietal hypoperfusion as biomarkers for AD. The role of the parietal lobe in the development of AD is only recently beginning to attract attention. The current review discusses parietal lobe involvement in the early stages of AD, viz. mild cognitive impairment, as reported from structural, functional, perfusion and metabolic neuroimaging studies. The medial and posterior parts of the parietal lobe seem to be preferentially affected, compared to the other parietal lobe parts. On the basis of the reviewed literature we propose a model showing the relationship between the various pathological events, as measured by different neuroimaging techniques, in the development of AD. In this model myelin breakdown is a beginning of the chain of pathological events leading to AD pathology and an AD diagnosis.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
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?
In the citing paper
“given the impact of AD on parietal cortex 30”
From Alzheimer's disease and its progression reduce pyramidal cell gain and connectivity (2025) · cites this paper as [30]
Citations
Cites
Neuropathological stageing of Alzheimer-related changes.
Braak, H., & Braak, E. (1991) · Acta Neuropathologica · doi:10.1007/bf00308809 · Cited by 16,123
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
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
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
The 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
Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade
Jack, C. R., Knopman, D. S., Jagust, W. J., Shaw, L. M., Aisen, P. S., Weiner, M. W., Petersen, R. C., & Trojanowski, J. Q. (2010) · The Lancet Neurology · doi:10.1016/s1474-4422(09)70299-6 · Cited by 4,806
Imaging brain amyloid in Alzheimer's disease with Pittsburgh Compound‐B
Klunk, W. E., Engler, H., Nordberg, A., Wang, Y., Blomqvist, G., Holt, D. P., Bergström, M., Savitcheva, I., Huang, G., Estrada, S., et al. (2004) · Annals of Neurology · doi:10.1002/ana.20009 · Cited by 4,496
Phases of Aβ-deposition in the human brain and its relevance for the development of AD
Thal, D. R., Rüb, U., Orantes, M., & Braak, H. (2002) · Neurology · doi:10.1212/wnl.58.12.1791 · Cited by 3,490
Regional Brain Changes in Aging Healthy Adults: General Trends, Individual Differences and Modifiers
Raz, N., Lindenberger, U., Rodrigue, K. M., Kennedy, K. M., Head, D., Williamson, A., Dahle, C., Gerstorf, D., & Acker, J. D. (2005) · Cerebral Cortex · doi:10.1093/cercor/bhi044 · Cited by 2,875
Functional-anatomic fractionation of the brain’s default network
Andrews-Hanna, J. R., Reidler, J. S., Sepulcre, J., Poulin, R., & Buckner, R. L. (2010) · Neuron · doi:10.1016/j.neuron.2010.02.005 · Cited by 2,767
Cited by
Sorted by citations
Memory loss in Alzheimer's disease
Jahn, H. (2013) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2013.15.4/hjahn · Cited by 653
The cerebellum in Alzheimer’s disease: evaluating its role in cognitive decline
Jacobs, H. I. L., Hopkins, D. A., Mayrhofer, H. C., Bruner, E., van Leeuwen, F. W., Raaijmakers, W., & Schmahmann, J. D. (2017) · Brain · doi:10.1093/brain/awx194 · Cited by 349
Self-citationBrickman, A. M., Provenzano, F. A., Muraskin, J., Manly, J. J., Blum, S., Apa, Z. L., Stern, Y., Brown, T. R., Luchsinger, J. A., & Mayeux, R. P. (2012) · Archives of Neurology · doi:10.1001/archneurol.2012.1527 · Cited by 258
High‐order resting‐state functional connectivity network for MCI classification
Chen, X., Zhang, H., Gao, Y., Chong-yaw Wee, A., Li, G., Shen, D. G., & Initiative, T. A. D. N. (2016) · Human Brain Mapping · doi:10.1002/hbm.23240 · Cited by 244
A single-nuclei RNA sequencing study of Mendelian and sporadic AD in the human brain
Del-Aguila, J. L., Li, Z., Dube, U., Mihindukulasuriya, K. A., Budde, J. P., Fernandez, M. V., Ibanez, L., Bradley, J., Wang, F., Bergmann, K., et al. (2019) · Alzheimer's Research & Therapy · doi:10.1186/s13195-019-0524-x · Cited by 183
Abutalebi, J., Canini, M., Rosa, P. A. D., Green, D. W., & Weekes, B. (2014) · Journal of Neurolinguistics · doi:10.1016/j.jneuroling.2014.09.008 · Cited by 188
Bilingualism, dementia, cognitive and neural reserve
Perani, D., & Abutalebi, J. (2015) · Current Opinion in Neurology · doi:10.1097/wco.0000000000000267 · Cited by 180
Jahanshad, N., Rajagopalan, P., Hua, X., Hibar, D. P., Nir, T. M., Toga, A. W., Jack, C. R., Saykin, A. J., Green, R. C., Weiner, M. W., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1216206110 · Cited by 153
Whitfield, D., Vallortigara, J., Alghamdi, A., Howlett, D. R., Hortobágyi, T., Johnson, M., Attems, J., Newhouse, S., Ballard, C. G., Thomas, A. J., et al. (2014) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2014.06.015 · Cited by 144
Clerx, L., Visser, P. J., Verhey, F., & Aalten, P. (2012) · Journal of Alzheimer s Disease · doi:10.3233/jad-2011-110797 · Cited by 132
Self-citationAnatomically interpretable deep learning of brain age captures domain-specific cognitive impairment
Yin, C., Imms, P. E., Cheng, M., Amgalan, A., Chowdhury, N. F., Massett, R. J., Chaudhari, N. N., Chen, X., Thompson, P. M., Bogdan, P., et al. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2214634120 · Cited by 129
Voxel-based meta-analysis of grey matter changes in Alzheimer’s disease
Wang, W., Yu, J., Liu, Y., Yin, R., Wang, H.-F., Wang, J., Tan, L., Raduà, J., & Tan, L. (2015) · Translational Neurodegeneration · doi:10.1186/s40035-015-0027-z · Cited by 124
Meta-analysis of functional network alterations in Alzheimer's disease: Toward a network biomarker
Jacobs, H. I. L., Raduà, J., Lückmann, H. C., & Sack, A. T. (2013) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2013.03.009 · Cited by 116
Self-citationThe effect of white matter hyperintensities on neurodegeneration in mild cognitive impairment
Tosto, G., Zimmerman, M. E., Hamilton, J. L., Carmichael, O. T., Brickman, A. M., & Initiative, A. D. N. (2015) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2015.05.014 · Cited by 112
Can visuospatial measures improve the diagnosis of Alzheimer's disease?
Salimi, S., Irish, M., Foxe, D., Hodges, J. R., Piguet, O., & Burrell, J. R. (2017) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1016/j.dadm.2017.10.004 · Cited by 121
Functional Disintegration of the Default Mode Network in Prodromal Alzheimer’s Disease
Dillen, K. N. H., Jacobs, H. I. L., Kukolja, J., Richter, N., von Reutern, B., Onur, O. A., Langen, K., & Fink, G. R. (2017) · Journal of Alzheimer s Disease · doi:10.3233/jad-161120 · Cited by 114
Self-citationClerx, L., van Rossum, I. A., Burns, L., Knol, D. L., Scheltens, P., Verhey, F., Aalten, P., Lapuerta, P., van de Pol, L., van Schijndel, R., et al. (2013) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2013.02.002 · Cited by 98
Self-citationNeuro-degeneration profile of Alzheimer's patients: A brain morphometry study
Filho, S. R. B. D. S., Barbosa, J. H. O., Rondinoni, C., dos Santos, A. C., Salmón, C. E. G., Lima, N. K. D. C., Ferriolli, E., & Moriguti, J. C. (2017) · NeuroImage Clinical · doi:10.1016/j.nicl.2017.04.001 · Cited by 102
Cognitive benefits of exercise interventions: an fMRI activation likelihood estimation meta-analysis
Yu, Q., Herold, F., Becker, B., Klugah‐Brown, B., Zhang, Y., Perrey, S., Veronese, N., Müller, N. G., Kramer, A. F., & Zou, L. (2021) · Brain Structure and Function · doi:10.1007/s00429-021-02247-2 · Cited by 104
Baril, A., Gagnon, K., Arbour, C., Soucy, J., Montplaisir, J. Y., Gagnon, J., & Gosselin, N. (2015) · SLEEP · doi:10.5665/sleep.4986 · Cited by 99
Qiu, Z., Yang, P., Xiao, C., Wang, S., Xiao, X., Qin, J., Liu, C.-M., Wang, T., & Lei, B. (2024) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2024.3386937 · Cited by 95
Alzheimer's Disease: The Downside of a Highly Evolved Parietal Lobe?
Bruner, E., & Jacobs, H. I. L. (2013) · Journal of Alzheimer's Disease · doi:10.3233/jad-122299 · Cited by 87
Self-citationFunctional craniology and brain evolution: from paleontology to biomedicine
Bruner, E., de la Cuétara, J. M., Masters, M., Amano, H., & Ogihara, N. (2014) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2014.00019 · Cited by 87
Corpus callosal atrophy and associations with cognitive impairment in Parkinson disease
Goldman, J. G., Bledsoe, I. O., Merkitch, D., Dinh, V., Bernard, B. A., & Stebbins, G. T. (2017) · Neurology · doi:10.1212/wnl.0000000000003764 · Cited by 85
Mills, J. D., Nalpathamkalam, T., Jacobs, H. I. L., Janitz, C., Merico, D., Hu, P., & Janitz, M. (2013) · Neuroscience Letters · doi:10.1016/j.neulet.2012.12.042 · Cited by 86
Self-citationZhang, Y., Schuff, N. W., Camacho, M. R., Chao, L. L., Fletcher, T. P., Yaffe, K. S., Woolley, S. C., Madison, C. A., Rosen, H. J., Miller, B. L., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0066367 · Cited by 85
Dillen, K. N. H., Jacobs, H. I. L., Kukolja, J., von Reutern, B., Richter, N., Onur, Ö. A., Dronse, J., Langen, K.-J., & Fink, G. R. (2016) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2016.04.010 · Cited by 82
Self-citationRobust Identification of Alzheimer’s Disease subtypes based on cortical atrophy patterns
Park, J.-Y., Na, H. K., Kim, S. S., Kim, H., Kim, H. J., Seo, S. W., Na, D. L., Han, C. E., Seong, J., Initiative, A. D. N., et al. (2017) · Scientific Reports · doi:10.1038/srep43270 · Cited by 80
EEG Window Length Evaluation for the Detection of Alzheimer’s Disease over Different Brain Regions
Tzimourta, K. D., Giannakeas, N., Tzallas, A. T., Astrakas, L. G., Afrantou, T., Ioannidis, P., Grigoriadis, N., Angelidis, P., Tsalikakis, D. G., & Tsipouras, M. G. (2019) · Brain Sciences · doi:10.3390/brainsci9040081 · Cited by 79
Aging-associated sensory decline and Alzheimer’s disease
Hong, S., Baek, S.-H., Lai, M. K. P., Arumugam, T. V., & Jo, D.-G. (2024) · Molecular Neurodegeneration · doi:10.1186/s13024-024-00776-y · Cited by 76
APOE2 orchestrated differences in transcriptomic and lipidomic profiles of postmortem AD brain
Lefterov, I., Wolfe, C. M., Fitz, N. F., Nam, K. N., Letronne, F., Biedrzycki, R. J., Kofler, J., Han, X., Wang, J., Schug, J., et al. (2019) · Alzheimer's Research & Therapy · doi:10.1186/s13195-019-0558-0 · Cited by 74
AD Course Map charts Alzheimer’s disease progression
Koval, I., Bône, A., Louis, M., Lartigue, T., Bottani, S., Marcoux, A., Samper‐Gonzàlez, J., Burgos, N., Charlier, B., Bertrand, A., et al. (2021) · Scientific Reports · doi:10.1038/s41598-021-87434-1 · Cited by 73
Increased O-GlcNAc levels correlate with decreased O-GlcNAcase levels in Alzheimer disease brain
Förster, S., Welleford, A. S., Triplett, J. C., Rukhsana Sultana, A., Schmitz, B., & Butterfield, D. A. (2014) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2014.05.014 · Cited by 73
Cortical Gyrification and Sulcal Spans in Early Stage Alzheimer's Disease
Liu, T., Lipnicki, D. M., Zhu, W., Tao, D., Chengqi Zhang, B., Cui, Y. J., Jin, J. S., Sachdev, P. S., & Wen, W. X. (2012) · PLoS ONE · doi:10.1371/journal.pone.0031083 · Cited by 73
Functional integration of parietal lobe activity in early Alzheimer disease
Jacobs, H. I. L., van Boxtel, M. P. J., Heinecke, A., Gronenschild, E. H. B. M., Backes, W. H., Ramakers, I. H. G. B., Jolles, J., & Verhey, F. R. J. (2012) · Neurology · doi:10.1212/wnl.0b013e318245287d · Cited by 71
Self-citationFesta, F., Medori, S., & Macrì, M. (2023) · Biomedicines · doi:10.3390/biomedicines11061765 · Cited by 85
Wharton, W., Stein, J. H., Korcarz, C. E., Sachs, J., Olson, S. R., Zetterberg, H., Dowling, N. M., Ye, S., Gleason, C. E., Underbakke, G. L., et al. (2012) · Journal of Alzheimer s Disease · doi:10.3233/jad-2012-120763 · Cited by 73
Deficits in Spontaneous Cognition as an Early Marker of Alzheimer’s Disease
Kvavilashvili, L., Niedźwieńska, A., Gilbert, S. J., & Markostamou, I. (2020) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2020.01.005 · Cited by 74
Midsagittal brain variation and MRI shape analysis of the precuneus in adult individuals
Bruner, E., Lázaro, G. R., de la Cuétara, J. M., Martín‐Loeches, M., Colom, R., & Jacobs, H. I. L. (2014) · Journal of Anatomy · doi:10.1111/joa.12155 · Cited by 67
Self-citationNeuropsychology of Alzheimer's Disease
Peña‐Casanova, J., Sánchez‐Benavides, G., de Sola, S., Manero-Borràs, R. M., & Casals-Coll, M. (2012) · Archives of Medical Research · doi:10.1016/j.arcmed.2012.08.015 · Cited by 65
Advances in MRI Biomarkers for the Diagnosis of Alzheimer’s Disease
Kehoe, E. G., McNulty, J. P., Mullins, P. G., & Bokde, A. L. W. (2014) · Biomarkers in Medicine · doi:10.2217/bmm.14.42 · Cited by 70
Visuospatial processing in early Alzheimer’s disease: A multimodal neuroimaging study
Jacobs, H. I. L., Gronenschild, E. H. B. M., Evers, E. A. T., Ramakers, I. H. G. B., Hofman, P. A. M., Backes, W. H., Jolles, J., Verhey, F. R. J., & van Boxtel, M. P. J. (2012) · Cortex · doi:10.1016/j.cortex.2012.01.005 · Cited by 64
Self-citationChuang, Y., Eldreth, D. A., Erickson, K. I., Varma, V. R., Harris, G., Fried, L. P., Rebok, G. W., Tanner, E. K., & Carlson, M. C. (2013) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2013.12.008 · Cited by 59
Ma, H. R., Sheng, L. Q., Pan, P. L., Wang, G. D., Luo, R., Shi, H. C., Dai, Z. Y., & Zhong, J. G. (2018) · Translational Neurodegeneration · doi:10.1186/s40035-018-0114-z · Cited by 57
Ramanan, S., Irish, M., Patterson, K. E., Rowe, J. B., Gorno‐Tempini, M. L., & Ralph, M. A. L. (2022) · Brain · doi:10.1093/brain/awac208 · Cited by 52
Hao, X., Li, C., Yan, J., Yao, X., Risacher, S. L., Saykin, A. J., Shen, L., Zhang, D., & Initiative, A. D. N. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx245 · Cited by 55
Functional Craniology and Brain Evolution
Bruner, E. (2014) · Springer series in bio-/neuroinformatics · doi:10.1007/978-3-319-08500-5_4 · Cited by 52
Tao, Q., Akhter‐Khan, S. C., Ang, T. F. A., DeCarli, C. S., Alosco, M. L., Mez, J., Killiany, R., Devine, S., Rokach, A., Itchapurapu, I. S., et al. (2022) · EClinicalMedicine · doi:10.1016/j.eclinm.2022.101643 · Cited by 56
Frantzidιs, C. A., Ladas, A. I., Vivas, A. B., Tsolaki, M., & Bamidis, P. D. (2014) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2014.01.007 · Cited by 54
Impaired Hippocampal-Cortical Interactions during Sleep in a Mouse Model of Alzheimer’s Disease
Cushing, S. D., Skelin, I., Moseley, S. C., Stimmell, A. C., Dixon, J. R., Melilli, A. S., Molina, L. A., McNaughton, B. L., & Wilber, A. A. (2020) · Current Biology · doi:10.1016/j.cub.2020.04.087 · Cited by 51
Na, H. K., Kang, D. R., Kim, S. S., Seo, S. W., Heilman, K. M., Noh, Y., & Na, D. L. (2016) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2016.08.001 · Cited by 49
Arenaza‐Urquijo, E. M., Molinuevo, J. L., Sala‐Llonch, R., Solé‐Padullés, C., Balasa, M., Bosch, B., Olives, J., Antonell, A., Lladó, A., Sánchez‐Valle, R., et al. (2013) · Journal of Alzheimer s Disease · doi:10.3233/jad-121906 · Cited by 50
Expression of Ambra1 in mouse brain during physiological and Alzheimer type aging
Sepe, S., Nardacci, R., Fanelli, F., Rosso, P., Bernardi, C., Cecconi, F., Mastroberardino, P. G., Piacentini, M., & Moreno, S. (2014) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2013.07.001 · Cited by 41
Noninvasive Gamma Sensory Stimulation May Reduce White Matter and Myelin Loss in Alzheimer’s Disease
Da, X., Hempel, E., Ou, Y., Rowe, O., Malchano, Z., Hajós, M., Kern, R. Z., Megerian, J. T., & Cimenser, A. (2023) · Journal of Alzheimer s Disease · doi:10.3233/jad-230506 · Cited by 47
Octodon degus : A Model for the Cognitive Impairment Associated with A lzheimer's Disease
Tarragón, E., Lopez, D., Estrada, C. M., Cuello, A. M. G., Schenker, E., Pifferi, F., Bordet, R., Richardson, J. C., & Herrero, M. T. (2013) · CNS Neuroscience & Therapeutics · doi:10.1111/cns.12125 · Cited by 49
Guo, H., Liu, L., Chen, J., Xu, Y. J., & Xiang, J. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00639 · Cited by 46
Zhang, J., Cao, X., Li, X., Li, X., Sun, X., Xia, Y., Hao, M., Sun, C., Xia, Y., Huang, H., et al. (2023) · American Journal of Clinical Nutrition · doi:10.1016/j.ajcnut.2023.05.007 · Cited by 43
The Fossil Evidence of Human Brain Evolution
Bruner, E. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-804042-3.00105-6 · Cited by 42
Das, M. M., Mao, W., Voskobiynyk, Y., Necula, D., Lew, I., Petersen, C., Zahn, A., Yu, G.-Q., Yu, X., Smith, N., et al. (2023) · Neurobiology of Disease · doi:10.1016/j.nbd.2023.106263 · Cited by 41
Wang, C., Pan, Y., Liu, Y., Xu, K., Hao, L., Huang, F., Ke, J., Sheng, L., Ma, H., & Guo, W. (2018) · Neurological Sciences · doi:10.1007/s10072-018-3306-5 · Cited by 41
Pietzuch, M., King, A. E., Ward, D. D., & Vickers, J. C. (2019) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2019.00030 · Cited by 45
Visuospatial dysfunction in Alzheimer's disease and behavioural variant frontotemporal dementia
Salimi, S., Irish, M., Foxe, D., Hodges, J. R., Piguet, O., & Burrell, J. R. (2019) · Journal of the Neurological Sciences · doi:10.1016/j.jns.2019.04.019 · Cited by 40
Cortical surface area and cortical thickness in the precuneus of adult humans
Bruner, E., Román, F. J., de la Cuétara, J. M., Martín‐Loeches, M., & Colom, R. (2014) · Neuroscience · doi:10.1016/j.neuroscience.2014.11.063 · Cited by 42
Alzheimer's disease: an evolutionary approach.
Bufill, E., Blesa, R., & Augustí, J. (2013) · PubMed · doi:10.4436/jass.91001 · Cited by 43
Zhang, B., Lin, L., & Wu, S. (2021) · Journal of Alzheimer s Disease · doi:10.3233/jad-201274 · Cited by 40
Wittens, M. M. J., Allemeersch, G., Sima, D. M., Naeyaert, M., Vanderhasselt, T., Vanbinst, A., Buls, N., Brucker, Y. D., Raeymaekers, H., Fransén, E., et al. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.746982 · Cited by 41
Decreased gray matter diffusivity: A potential early Alzheimer's disease biomarker?
Jacobs, H. I. L., van Boxtel, M. P. J., Gronenschild, E. H. B. M., Uylings, H. B. M., Jolles, J., & Verhey, F. R. J. (2012) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2011.11.004 · Cited by 38
Self-citationDecreased Oligodendrocyte Nuclear Diameter in Alzheimer's Disease and Lewy Body Dementia
Gagyi, E., Kormos, B., Castellanos, K. J., Valyi‐Nagy, K., Korneff, D., LoPresti, P., Woltjer, R., & Valyi‐Nagy, T. (2012) · Brain Pathology · doi:10.1111/j.1750-3639.2012.00595.x · Cited by 38
Norris, J. E., McGeown, W. J., Guerrini, C., & Castronovo, J. (2015) · Frontiers in Psychology · doi:10.3389/fpsyg.2015.00999 · Cited by 41
Selective Attention and Sensory Modality in Aging: Curses and Blessings
Gerven, P. W. M. V., & Guerreiro, M. J. S. (2016) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2016.00147 · Cited by 42
The Evolution of the Parietal Lobes in the Genus Homo
Bruner, E., Amano, H., Pereira‐Pedro, A. S., & Ogihara, N. (2017) · Springer eBooks · doi:10.1007/978-4-431-56582-6_15 · Cited by 36
Yu, J. H., Kim, R. E. Y., Jung, J., Park, S. Y., Lee, D. Y., Cho, H. J., Kim, N. H., Yoo, H. J., Seo, J. A., Kim, S. G., et al. (2021) · BMC Geriatrics · doi:10.1186/s12877-021-02581-4 · Cited by 42
Vangberg, T. R., Eikenes, L., & Haberg, A. K. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116158 · Cited by 37
Connectivity network measures predict volumetric atrophy in mild cognitive impairment
Nir, T. M., Jahanshad, N., Toga, A. W., Bernstein, M. A., Jack, C. R., Weiner, M. W., & Thompson, P. M. (2014) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2014.04.038 · Cited by 34
Güntekin, B., Hanoğlu, L., Aktürk, T., Fide, E., Emek‐Savaş, D. D., Ruşen, E., Yıldırım, E., & Yener, G. (2019) · Psychophysiology · doi:10.1111/psyp.13434 · Cited by 38
Lazarou, I., Georgiadis, K., Nikolopoulos, S., Oikonomou, V. P., Tsolaki, A., Kompatsiaris, I. Y., Tsolaki, M., & Kugiumtzis, D. (2020) · Brain Sciences · doi:10.3390/brainsci10060392 · Cited by 36
Lattanzio, F., Carboni, L., Carretta, D., Rimondini, R., Candeletti, S., & Romualdi, P. (2013) · Neuroscience · doi:10.1016/j.neuroscience.2013.10.017 · Cited by 34
Sulcal pattern, extension, and morphology of the precuneus in adult humans
Pereira‐Pedro, A. S., & Bruner, E. (2016) · Annals of Anatomy - Anatomischer Anzeiger · doi:10.1016/j.aanat.2016.05.001 · Cited by 35
Jacobs, H. I. L., Clerx, L., Gronenschild, E. H. B. M., Aalten, P., & Verhey, F. R. J. (2014) · Journal of Alzheimer s Disease · doi:10.3233/jad-131232 · Cited by 35
Self-citationStricker, N. H., Salat, D. H., Foley, J. M., Zink, T. A., Kellison, I. L., McFarland, C. P., Grande, L. J., McGlinchey, R. E., Milberg, W., & Leritz, E. C. (2013) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617713000660 · Cited by 33
A Role for PGC-1a in the Control of Abnormal Mitochondrial Dynamics in Alzheimer’s Disease
Wang, J., Liu, W., Shi, H.-Z., Zhai, H.-R., Qian, J.-J., & Zhang, W. (2022) · Cells · doi:10.3390/cells11182849 · Cited by 34
Communicability disruption in Alzheimer’s disease connectivity networks
Lella, E., Amoroso, N., Lombardi, A., Maggipinto, T., Tangaro, S., Bellotti, R., & Initiative, A. D. N. (2018) · Journal of Complex Networks · doi:10.1093/comnet/cny009 · Cited by 32
Spatial Navigation and Visuospatial Strategies in Typical and Atypical Aging
Laczó, M., Wiener, J. M., Kalinová, J., Matušková, V., Vyhnálek, M., Hort, J., & Laczó, J. (2021) · Brain Sciences · doi:10.3390/brainsci11111421 · Cited by 30
Odusami, M., Damaševičius, R., Belousovienė, E., & Maskeliūnas, R. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e34402 · Cited by 30
Wang, M., Hao, X., Huang, J., Shao, W., & Zhang, D. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty911 · Cited by 27
Inclusion of African American/Black adults in a pilot brain proteomics study of Alzheimer's disease
Stepler, K. E., Mahoney, E. R., Kofler, J., Hohman, T. J., López, O. L., & Robinson, R. A. S. (2020) · Neurobiology of Disease · doi:10.1016/j.nbd.2020.105129 · Cited by 26
Zheng, H., Ford, B. N., Bergamino, M., Kuplicki, R., Tulsa 1000 Investigators, Aupperle, R. L., Bodurka, J., Cha, Y., Feinstein, J. S., Khalsa, S. S., et al. (2020) · Molecular Psychiatry · doi:10.1038/s41380-020-00932-y · Cited by 28
Anatomy and White Matter Connections of the Superior Parietal Lobule
Lin, Y., Dadario, N. B., Hormovas, J., Young, I. M., Briggs, R. G., Mackenzie, A., Palejwala, A. H., Fonseka, R. D., Kim, S. J., Tanglay, O., et al. (2021) · Operative Neurosurgery · doi:10.1093/ons/opab174 · Cited by 28
Krajčovičová, L., Bartoň, M., Elfmarková, N., Mikl, M., Mareček, R., & Rektorová, I. (2017) · Journal of Neural Transmission · doi:10.1007/s00702-017-1789-5 · Cited by 28
Cheng, C., Wang, P., Mao, H., & Hsiao, F. (2020) · Aging · doi:10.18632/aging.102859 · Cited by 28
Chronotype differences in cortical thickness: grey matter reflects when you go to bed
Rosenberg, J., Jacobs, H. I. L., Maximov, I. I., Reske, M., & Shah, N. J. (2018) · Brain Structure and Function · doi:10.1007/s00429-018-1697-y · Cited by 25
Self-citationJović, M., Lončarević‐Vasiljković, N., Ivković, S., Dinić, J., Milanović, D., Zloković, B. V., & Kanazir, S. (2019) · PLoS ONE · doi:10.1371/journal.pone.0216726 · Cited by 27
Functional connectivity changes in mild cognitive impairment: A meta-analysis of M/EEG studies
Buzi, G., Fornari, C., Perinelli, A., & Mazza, V. (2023) · Clinical Neurophysiology · doi:10.1016/j.clinph.2023.10.011 · Cited by 29
Sil, S., Ghosh, R., Sanyal, M., Guha, D., & Ghosh, T. (2015) · Journal of Immunotoxicology · doi:10.3109/1547691x.2015.1030804 · Cited by 25
Enhanced temporal complexity of EEG signals in older individuals with high cognitive functions
Iinuma, Y., Nobukawa, S., Mizukami, K., Kawaguchi, M., Higashima, M., Tanaka, Y., Yamanishi, T., & Takahashi, T. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.878495 · Cited by 24
Carbonell, F., Charil, A., Zijdenbos, A. P., Evans, A. C., Bedell, B. J., & Initiative4, T. A. D. N. (2014) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1038/jcbfm.2014.66 · Cited by 23
Wang, X., Cui, X., Ding, C., Li, D., Chen, C., Wang, B., & Xiang, J. (2020) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.27453 · Cited by 24
Zhang, Y., Liu, T., Lanfranchi, V., & Yang, P. (2022) · IEEE Journal of Translational Engineering in Health and Medicine · doi:10.1109/jtehm.2022.3219775 · Cited by 24
Guelib, B., Zarour, K., Hermessi, H., Bounab, R., & Khlifa, N. (2023) · IEEE Access · doi:10.1109/access.2023.3276722 · Cited by 25
Hierarchical Multivariate Covariance Analysis of Metabolic Connectivity
Carbonell, F., Charil, A., Zijdenbos, A. P., Evans, A. C., Bedell, B. J., & Initiative, A. D. N. (2014) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1038/jcbfm.2014.165 · Cited by 24
Metadata
- Authors
- Jacobs, H. I. L., Van Boxtel, M. P. J., Jolles, J., Verhey, F. R. J., & Uylings, H. B. M.
- Affiliations
- Maastricht University (NL)
- Corresponding author
- Jacobs, Heidi I.L.
- Venue
- Neuroscience & Biobehavioral Reviews
- Publisher
- Elsevier BV
- Published
- 2012-01
- Volume
- 36
- Issue
- 1
- Pages
- 297-309
- ISSN
- 0149-7634 (ISSN-L)
- OpenAlex
- W2119341498
- Cited by
- 293
- References
- 202
- Citations by year
- 2026: 16 · 2025: 40 · 2024: 28 · 2023: 28 · 2022: 25 · 2021: 21 · 2020: 15 · 2019: 15 · 2018: 11 · 2017: 17 · 2016: 9 · 2015: 12 · 2014: 21 · 2013: 22 · 2012: 12
- FWCI
- 2.30
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Neuroscience & Biobehavioral Reviews (publishedVersion)
- PubMed (publishedVersion)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion)
- VU Research Portal (publishedVersion)
- Research Publications (Maastricht University) (submittedVersion)
- Pure Amsterdam UMC (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- 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 › Neurology › Neurological Disease Mechanisms and Treatments
- Keywords
- Alzheimer's disease, parietal lobe, medial temporal lobe atrophy, hippocampus, parahippocampal gyrus, mild cognitive impairment, brain metabolism, myelin breakdown, neuroimaging biomarkers
- MeSH terms
- Alzheimer Disease, Cognition Disorders, Humans, Models, Biological, Parietal Lobe, Radionuclide Imaging, Retrospective Studies, PubMed, Neuroimaging
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