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Cited by 95Functional Brain Connectivity StudiesDementia and Cognitive Impairment ResearchAlzheimer's disease research and treatments

Abnormal Resting-State Functional Connectivity Strength in Mild Cognitive Impairment and Its Conversion to Alzheimer’s Disease

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Li, Yuxia, Wang, Xiaoni, Li, Yongqiu, Sun, Yu, Sheng, Can, Li, Hongyan, Li, Xuanyu, Yu, Yang +8 more·2016·Neural Plasticity
DOI 10.1155/2016/4680972PMC PMC4710946
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Abstract

Individuals diagnosed with mild cognitive impairment (MCI) are at high risk of transition to Alzheimer’s disease (AD). However, little is known about functional characteristics of the conversion from MCI to AD. Resting-state functional magnetic resonance imaging was performed in 25 AD patients, 31 MCI patients, and 42 well-matched normal controls at baseline. Twenty-one of the 31 MCI patients converted to AD at approximately 24 months of follow-up. Functional connectivity strength (FCS) and seed-based functional connectivity analyses were used to assess the functional differences among the groups. Compared to controls, subjects with MCI and AD showed decreased FCS in the default-mode network and the occipital cortex. Importantly, the FCS of the left angular gyrus and middle occipital gyrus was significantly lower in MCI-converters as compared with MCI-nonconverters. Significantly decreased functional connectivity was found in MCI-converters compared to nonconverters between the left angular gyrus and bilateral inferior parietal lobules, dorsolateral prefrontal and lateral temporal cortices, and the left middle occipital gyrus and right middle occipital gyri. We demonstrated gradual but progressive functional changes during a median 2-year interval in patients converting from MCI to AD, which might serve as early indicators for the dysfunction and progression in the early stage of AD.

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  • The functional connectivity of the default mode network is selectively disrupted in patients with mild cognitive impairment and dementia due to Alzheimer's disease.

    “Based on accumulating evidence, the FC of the default mode network (DMN) is selectively disrupted in patients with MCI and dementia due to AD [52, 129, 130].”

    From Neuroimaging advances regarding subjective cognitive decline in preclinical Alzheimer's disease (2020) · cites this paper as [130]

    The Discussion (§4.1) reports decreased functional connectivity strength in the DMN in patients with MCI and AD. But it also reports decreases in the occipital cortex, and the Introduction says connectivity deficits are not confined to the DMN; the word “selectively” therefore overstates the finding. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

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  1. [1]Dubois B. Feldman H. H. Jacova C. Advancing research diagnostic criteria for Alzheimer's disease: the IWG-2 criteria The Lancet Neurology 2014 13 6 614 629 10.1016/s1474-4422(14)70090-0 2-s2.0-84900988440 24849862 · DOI · Paper page
  2. [2]Petersen R. C. Doody R. Kurz A. Current concepts in mild cognitive impairment Archives of Neurology 2001 58 12 1985 1992 10.1001/archneur.58.12.1985 2-s2.0-0035195760 11735772 · DOI · Paper page
  3. [3]Fayed N. Modrego P. J. Salinas G. R. Gazulla J. Magnetic resonance imaging based clinical research in Alzheimer's disease Journal of Alzheimer's Disease 2012 31 supplement 3 S5 S18 10.3233/jad-2011-111292 2-s2.0-84866856165 22233763 · DOI
  4. [4]Wattjes M. P. Structural MRI International Psychogeriatrics/IPA 2011 23 supplement 2 S13 S24 10.1017/s1041610211000913 2-s2.0-84856507736 21729419 · DOI
  5. [5]Apostolova L. G. Mosconi L. Thompson P. M. Subregional hippocampal atrophy predicts Alzheimer's dementia in the cognitively normal Neurobiology of Aging 2010 31 7 1077 1088 10.1016/j.neurobiolaging.2008.08.008 2-s2.0-77952878939 18814937 PMC2873083 · DOI
  6. [6]Bai F. Xie C. Watson D. R. Aberrant hippocampal subregion networks associated with the classifications of aMCI subjects: a longitudinal resting-state study PLoS ONE 2011 6 12 e29288 10.1371/journal.pone.0029288 2-s2.0-84455169819 PMC3246487 22216234 · DOI
  7. [7]Eskildsen S. F. Coupé P. Fonov V. S. Pruessner J. C. Collins D. L. Structural imaging biomarkers of Alzheimer's disease: predicting disease progression Neurobiology of Aging 2015 36 supplement 1 S23 S31 10.1016/j.neurobiolaging.2014.04.034 2-s2.0-84916608467 25260851 · DOI
  8. [9]Binnewijzend M. A. A. Schoonheim M. M. Sanz-Arigita E. Resting-state fMRI changes in Alzheimer's disease and mild cognitive impairment Neurobiology of Aging 2012 33 9 2018 2028 10.1016/j.neurobiolaging.2011.07.003 2-s2.0-84863452625 21862179 · DOI
  9. [10]Dipasquale O. Griffanti L. Clerici M. Nemni R. Baselli G. Baglio F. High-dimensional ica analysis detects within-network functional connectivity damage of default-mode and sensory-motor networks in alzheimer's disease Frontiers in Human Neuroscience 2015 9, article 43 10.3389/fnhum.2015.00043 PMC4315015 25691865 · DOI
  10. [11]Wang Z. Liang P. Jia X. The baseline and longitudinal changes of PCC connectivity in mild cognitive impairment: a combined structure and resting-state fMRI study PLoS ONE 2012 7 5 e36838 10.1371/journal.pone.0036838 2-s2.0-84862089794 PMC3356348 22629335 · DOI
  11. [12]Wang Z. Jia X. Liang P. Changes in thalamus connectivity in mild cognitive impairment: evidence from resting state fMRI European Journal of Radiology 2012 81 2 277 285 10.1016/j.ejrad.2010.12.044 2-s2.0-84855598374 21273022 · DOI
  12. [13]Dai Z. Yan C. Li K. Identifying and mapping connectivity patterns of brain network hubs in Alzheimer's disease Cerebral Cortex 2015 25 10 3723 3742 10.1093/cercor/bhu246 25331602 · DOI
  13. [14]Liang X. Zou Q. He Y. Yang Y. Coupling of functional connectivity and regional cerebral blood flow reveals a physiological basis for network hubs of the human brain Proceedings of the National Academy of Sciences of the United States of America 2013 110 5 1929 1934 10.1073/pnas.1214900110 2-s2.0-84873171641 23319644 PMC3562840 · DOI · Paper page
  14. [16]Petersen R. C. Mild cognitive impairment as a diagnostic entity Journal of Internal Medicine 2004 256 3 183 194 10.1111/j.1365-2796.2004.01388.x 2-s2.0-4544335597 15324362 · DOI · Paper page
  15. [17]Dubois B. Feldman H. H. Jacova C. Research criteria for the diagnosis of Alzheimer's disease: revising the NINCDS-ADRDA criteria The Lancet Neurology 2007 6 8 734 746 10.1016/s1474-4422(07)70178-3 2-s2.0-34447322271 17616482 · DOI · Paper page
  16. [18]American Psychiatric Association Diagnostic and Statistical Manual of Mental Disorders 1994 4th Washington, DC, USA American Psychiatric Press
  17. [19]Zhenxin Z. Xia H. Hui L. et al The mini-mental state examination in the Chinese residents population aged 55 years and over in the urban and rural areas of Beijing Chinese Journal of Neurology 1999 32 3 149 153 2-s2.0-0032810112
  18. [20]Lu J. Li D. Li F. Montreal cognitive assessment in detecting cognitive impairment in Chinese elderly individuals: a population-based study Journal of Geriatric Psychiatry and Neurology 2011 24 4 184 190 10.1177/0891988711422528 2-s2.0-84855467990 22228824 · DOI
  19. [22]Morris J. C. The Clinical Dementia Rating (CDR): current version and scoring rules Neurology 1993 43 11 2412 2414 2-s2.0-0027425211 8232972
  20. [23]Oldfield R. C. The assessment and analysis of handedness: the Edinburgh inventory Neuropsychologia 1971 9 1 97 113 10.1016/0028-3932(71)90067-4 2-s2.0-0015021890 5146491 · DOI · Paper page
  21. [25]Ashburner J. A fast diffeomorphic image registration algorithm NeuroImage 2007 38 1 95 113 10.1016/j.neuroimage.2007.07.007 2-s2.0-34548832230 17761438 · DOI · Paper page
  22. [26]Ledberg A. Åkerman S. Roland P. E. Estimation of the probabilities of 3D clusters in functional brain images NeuroImage 1998 8 2 113 128 10.1006/nimg.1998.0336 2-s2.0-0031658817 9740755 · DOI
  23. [27]Song X.-W. Dong Z.-Y. Long X.-Y. REST: a toolkit for resting-state functional magnetic resonance imaging data processing PLoS ONE 2011 6 9 e25031 10.1371/journal.pone.0025031 2-s2.0-80052944191 PMC3176805 21949842 · DOI
  24. [28]Zeng L.-L. Wang D. Fox M. D. Neurobiological basis of head motion in brain imaging Proceedings of the National Academy of Sciences of the United States of America 2014 111 16 6058 6062 10.1073/pnas.1317424111 24711399 PMC4000812 · DOI
  25. [29]van Dijk K. R. A. Sabuncu M. R. Buckner R. L. The influence of head motion on intrinsic functional connectivity MRI NeuroImage 2012 59 1 431 438 10.1016/j.neuroimage.2011.07.044 2-s2.0-81155162516 21810475 PMC3683830 · DOI · Paper page
  26. [30]Power J. D. Barnes K. A. Snyder A. Z. Schlaggar B. L. Petersen S. E. Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion NeuroImage 2012 59 3 2142 2154 10.1016/j.neuroimage.2011.10.018 2-s2.0-84855455705 22019881 PMC3254728 · DOI · Paper page
  27. [31]Fox M. D. Zhang D. Snyder A. Z. Raichle M. E. The global signal and observed anticorrelated resting state brain networks Journal of Neurophysiology 2009 101 6 3270 3283 10.1152/jn.90777.2008 2-s2.0-66349133709 19339462 PMC2694109 · DOI · Paper page
  28. [32]Birn R. M. Diamond J. B. Smith M. A. Bandettini P. A. Separating respiratory-variation-related fluctuations from neuronal-activity-related fluctuations in fMRI NeuroImage 2006 31 4 1536 1548 10.1016/j.neuroimage.2006.02.048 2-s2.0-33746852686 16632379 · DOI
  29. [33]Weissenbacher A. Kasess C. Gerstl F. Lanzenberger R. Moser E. Windischberger C. Correlations and anticorrelations in resting-state functional connectivity MRI: a quantitative comparison of preprocessing strategies NeuroImage 2009 47 4 1408 1416 10.1016/j.neuroimage.2009.05.005 2-s2.0-67651033257 19442749 · DOI · Paper page
  30. [35]Han Y. Wang J. Zhao Z. Frequency-dependent changes in the amplitude of low-frequency fluctuations in amnestic mild cognitive impairment: a resting-state fMRI study NeuroImage 2011 55 1 287 295 10.1016/j.neuroimage.2010.11.059 2-s2.0-78951472554 21118724 · DOI
  31. [36]Wang J. Zuo X. Dai Z. Disrupted functional brain connectome in individuals at risk for Alzheimer's disease Biological Psychiatry 2013 73 5 472 481 10.1016/j.biopsych.2012.03.026 2-s2.0-84873647166 22537793 · DOI · Paper page
  32. [37]Toussaint P.-J. Maiz S. Coynel D. Characteristics of the default mode functional connectivity in normal ageing and Alzheimer's disease using resting state fMRI with a combined approach of entropy-based and graph theoretical measurements NeuroImage 2014 101 778 786 10.1016/j.neuroimage.2014.08.003 2-s2.0-84907058022 25111470 · DOI
  33. [38]Gour N. Felician O. Didic M. Functional connectivity changes differ in early and late-onset Alzheimer's disease Human Brain Mapping 2014 35 7 2978 2994 10.1002/hbm.22379 2-s2.0-84902123948 24123475 PMC6869697 · DOI
  34. [39]Cha J. Jo H. J. Kim H. J. Functional alteration patterns of default mode networks: comparisons of normal aging, amnestic mild cognitive impairment and Alzheimer's disease The European Journal of Neuroscience 2013 37 12 1916 1924 10.1111/ejn.12177 2-s2.0-84879240834 23773060 PMC3694739 · DOI
  35. [40]Persson J. Pudas S. Nilsson L.-G. Nyberg L. Longitudinal assessment of default-mode brain function in aging Neurobiology of Aging 2014 35 9 2107 2117 10.1016/j.neurobiolaging.2014.03.012 2-s2.0-84902118094 24767950 · DOI
  36. [41]Sorg C. Riedl V. Mühlau M. Selective changes of resting-state networks in individuals at risk for Alzheimer's disease Proceedings of the National Academy of Sciences of the United States of America 2007 104 47 18760 18765 10.1073/pnas.0708803104 2-s2.0-36749045805 18003904 PMC2141850 · DOI · Paper page
  37. [42]Mintun M. A. Larossa G. N. Sheline Y. I. [11C]PIB in a nondemented population: potential antecedent marker of Alzheimer disease Neurology 2006 67 3 446 452 10.1212/01.wnl.0000228230.26044.a4 2-s2.0-33747048954 16894106 · DOI · Paper page
  38. [43]Matsuda H. Cerebral blood flow and metabolic abnormalities in Alzheimer's disease Annals of Nuclear Medicine 2001 15 2 85 92 10.1007/bf02988596 2-s2.0-0034983181 11448080 · DOI
  39. [44]Damoiseaux J. S. Prater K. E. Miller B. L. Greicius M. D. Functional connectivity tracks clinical deterioration in Alzheimer's disease Neurobiology of Aging 2012 33 4 828.e19 828.e30 10.1016/j.neurobiolaging.2011.06.024 2-s2.0-84856974910 21840627 PMC3218226 · DOI
  40. [45]Hu Z. Sheng C. Sun Y. Structural and resting state functional MRI characteristics of patients at high risk for Alzheimer's disease Chinese Journal of Neurology 2014 47 12 824 830
  41. [46]Bays P. M. Husain M. Dynamic shifts of limited working memory resources in human vision Science 2008 321 5890 851 854 10.1126/science.1158023 2-s2.0-49449102090 18687968 PMC2532743 · DOI
  42. [47]Weiler M. Fukuda A. Massabki L. H. P. Default mode, executive function, and language functional connectivity networks are compromised in mild Alzheimeŕs disease Current Alzheimer Research 2014 11 3 274 282 10.2174/1567205011666140131114716 2-s2.0-84897455607 24484280 · DOI
  43. [48]Cai S. Huang L. Zou J. Changes in thalamic connectivity in the early and late stages of amnestic mild cognitive impairment: a resting-state functional magnetic resonance study from ADNI PLoS ONE 2015 10 2 e0115573 10.1371/journal.pone.0115573 2-s2.0-84923059835 PMC4332494 25679386 · DOI
  44. [49]Zhou B. Liu Y. Zhang Z. Impaired functional connectivity of the thalamus in Alzheimer's disease and mild cognitive impairment: a resting-state fMRI study Current Alzheimer Research 2013 10 7 754 766 10.2174/15672050113109990146 2-s2.0-84888244733 23905993 · DOI
  45. [50]Ewers M. Insel P. S. Stern Y. Weiner M. W. The Alzheimer's Disease Neuroimaging Initiative Cognitive reserve associated with FDG-PET in preclinical Alzheimer disease Neurology 2013 80 13 1194 1201 10.1212/wnl.0b013e31828970c2 2-s2.0-84876279596 23486873 PMC3691784 · DOI
  46. [51]Motomura K. Fujii M. Maesawa S. Kuramitsu S. Natsume A. Wakabayashi T. Association of dorsal inferior frontooccipital fasciculus fibers in the deep parietal lobe with both reading and writing processes: a brain mapping study Journal of Neurosurgery 2014 121 1 142 148 10.3171/2014.2.jns131234 2-s2.0-84903904269 24655122 · DOI
  47. [53]Jacobs H. I. L. Van Boxtel M. P. J. Heinecke A. Functional integration of parietal lobe activity in early Alzheimer disease Neurology 2012 78 5 352 360 10.1212/wnl.0b013e318245287d 2-s2.0-84858068396 22262753 · DOI
  48. [54]Bai F. Liao W. Watson D. R. Abnormal whole-brain functional connection in amnestic mild cognitive impairment patients Behavioural Brain Research 2011 216 2 666 672 10.1016/j.bbr.2010.09.010 2-s2.0-78149497644 20851147 · DOI
  49. [55]Caroli A. Geroldi C. Nobili F. Functional compensation in incipient Alzheimer's disease Neurobiology of Aging 2010 31 3 387 397 10.1016/j.neurobiolaging.2008.05.001 2-s2.0-74249087764 18554752 · DOI
  50. [56]Abuhassan K. Coyle D. Belatreche A. Maguire L. Compensating for synaptic loss in Alzheimer's disease Journal of Computational Neuroscience 2014 36 1 19 37 10.1007/s10827-013-0462-8 2-s2.0-84893802132 23728490 · DOI
  51. [57]Tramutola A. Triplett J. C. Di Domenico F. Alteration of mTOR signaling occurs early in the progression of Alzheimer disease (AD): analysis of brain from subjects with pre-clinical AD, amnestic mild cognitive impairment and late-stage AD Journal of Neurochemistry 2015 133 5 739 749 10.1111/jnc.13037 25645581 · DOI · Paper page
  52. [58]Yamashita K.-I. Taniwaki Y. Utsunomiya H. Taniwaki T. Cerebral blood flow reduction associated with orientation for time in amnesic mild cognitive impairment and Alzheimer disease patients Journal of Neuroimaging 2014 24 6 590 594 10.1111/jon.12096 2-s2.0-84895175423 24593247 · DOI
  53. [59]Zhang H.-Y. Wang S.-J. Xing J. Detection of PCC functional connectivity characteristics in resting-state fMRI in mild Alzheimer's disease Behavioural Brain Research 2009 197 1 103 108 10.1016/j.bbr.2008.08.012 2-s2.0-57649224343 18786570 · DOI
  54. [60]Apostolova L. G. Steiner C. A. Akopyan G. G. Three-dimensional gray matter atrophy mapping in mild cognitive impairment and mild Alzheimer disease Archives of Neurology 2007 64 10 1489 1495 10.1001/archneur.64.10.1489 2-s2.0-34250735918 17923632 PMC3197839 · DOI
  55. [61]Ossenkoppele R. Tolboom N. Foster-Dingley J. C. Longitudinal imaging of Alzheimer pathology using [11C]PIB, [18F]FDDNP and [18F]FDG PET European Journal of Nuclear Medicine and Molecular Imaging 2012 39 6 990 1000 10.1007/s00259-012-2102-3 2-s2.0-84862646168 22441582 · DOI
  56. [62]Li S. Yuan X. Pu F. Abnormal changes of multidimensional surface features using multivariate pattern classification in amnestic mild cognitive impairment patients The Journal of Neuroscience 2014 34 32 10541 10553 10.1523/jneurosci.4356-13.2014 2-s2.0-84905703520 25100588 PMC4122798 · DOI
  57. [63]Lin S.-H. Yu C.-Y. Pai M.-C. The occipital white matter lesions in Alzheimer's disease patients with visual hallucinations Clinical Imaging 2006 30 6 388 393 10.1016/j.clinimag.2006.09.025 2-s2.0-33750707603 17101407 · DOI
  58. [65]Yang G. J. Murray J. D. Repovs G. Altered global brain signal in schizophrenia Proceedings of the National Academy of Sciences of the United States of America 2014 111 20 7438 7443 10.1073/pnas.1405289111 2-s2.0-84901045152 24799682 PMC4034208 · DOI

Cited by

Sorted by citations

Authors
Li, Y., Wang, X., Li, Y., Sun, Y., Sheng, C., Li, H., Li, X., Yu, Y., Chen, G., Hu, X., Jing, B., Wang, D., Li, K., Jessen, F., Xia, M., & Han, Y.
Affiliations
  • Capital Medical University (CN)
  • University Hospital Cologne (DE)
  • Chinese University of Hong Kong (HK)
  • Beijing Normal University (CN)
Corresponding author
  • Xia, Mingrui
  • Han, Ying
ORCID
Venue
Neural Plasticity
Publisher
Wiley
Published
2016
Volume
2016
Pages
1-12
ISSN
  • 1687-5443 (ISSN-L)
  • 2090-5904
DOI
10.1155/2016/4680972
PMC
PMC4710946
OpenAlex
W2214920251
Cited by
95
References
6
Citations by year
2026: 4 · 2025: 9 · 2024: 9 · 2023: 9 · 2022: 11 · 2021: 13 · 2020: 8 · 2019: 15 · 2018: 6 · 2017: 7 · 2016: 4
FWCI
3.41
Type
journal article
Language
en
Open access
Licence
Locations
  • Neural Plasticity (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Kölner Universitäts PublikationsServer (Universität zu Köln) (publishedVersion)
  • National University of Singapore (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • National Natural Science Foundation of China (31371007, 81430037, 30970823, 81401479, Z131100006813022)
  • Chinese Health and Family Planning Committee (31371007, 81430037, 30970823, 81401479, Z131100006813022)
  • Beijing Municipal Science & Technology Commission (31371007, 81430037, 30970823, 81401479, Z131100006813022)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
  • Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
Keywords
mild cognitive impairment, Alzheimer's disease, conversion to Alzheimer's disease, resting-state functional connectivity, default mode network, angular gyrus, middle occipital gyrus, inferior parietal lobule, early biomarkers, functional brain changes
MeSH terms
Aged, Aged, 80 and over, Alzheimer Disease, Brain, Brain Mapping, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Nerve Net, Disease Progression, Cognitive Dysfunction, Connectome

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