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Aberrant default mode network in amnestic mild cognitive impairment: a meta-analysis of independent component analysis studies

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Abstract

Independent component analysis (ICA) is one of the most popular and valid methods to investigate the default mode network (DMN), an intrinsic network which attracts particular attention in amnestic mild cognitive impairment (aMCI). However, previous studies present inconsistent results regarding the topographical organization of the DMN in aMCI. Therefore, we conducted a quantitative, voxel-wise meta-analysis of resting-state ICA studies using Seed-based d Mapping to establish the most consistent pattern of DMN functional connectivity alterations in aMCI. Twenty studies, comprising 23 independent datasets involving 535 patients and 586 healthy controls, met the inclusion criteria. Patients with aMCI exhibited reliably lower DMN functional connectivity than the healthy controls in the bilateral precuneus/posterior cingulate cortices and medial temporal lobes, which are implicated in episodic memory deficits. Moreover, an exploratory meta-regression analysis revealed that greater severity of global cognitive impairment in the patient groups was associated with stronger functional connectivity in the bilateral medial frontal cortices (including the anterior cingulate cortices), left angular gyrus, and right temporal pole extending to the middle temporal gyrus, likely reflecting a compensatory mechanism for maintaining cognitive efficiency. This meta-analysis identifies a consistent pattern of aberrant DMN functional connectivity in aMCI, which facilitates understanding of the neurobiological substrates of this disease.

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Abbreviations

AD:

Alzheimer’s disease

aMCI:

amnestic mild cognitive impairment

ACC:

anterior cingulate cortices

AVLT:

Auditory Verbal Learning Test

DMN:

default mode network

FWHM:

full width at half maximum

ICA:

independent component analysis

IPL:

inferior parietal lobules

MNI:

Montreal Neurological Institute

MTL:

medial temporal lobe

MOOSE:

Meta-analysis Of Observational Studies in Epidemiology

MMSE:

Mini-Mental State Examination

PCC:

posterior cingulate cortices

SDM:

Seed-based d Mapping

SMD:

standardized mean difference

rs-fMRI:

resting-state functional magnetic resonance imaging

References

  1. Petersen RC, Doody R, Kurz A, Mohs RC, Morris JC, Rabins PV, Ritchie K, Rossor M, Thal L, Winblad B (2001) Current concepts in mild cognitive impairment. Arch Neurol 58(12):1985–1992

    Article  CAS  PubMed  Google Scholar 

  2. Gauthier S, Reisberg B, Zaudig M, Petersen RC, Ritchie K, Broich K, Belleville S, Brodaty H, Bennett D, Chertkow H, Cummings JL, de Leon M, Feldman H, Ganguli M, Hampel H, Scheltens P, Tierney MC, Whitehouse P, Winblad B (2006) Mild cognitive impairment. Lancet (London, England) 367(9518):1262–1270. https://doi.org/10.1016/s0140-6736(06)68542-5

    Article  Google Scholar 

  3. Pievani M, Pini L, Ferrari C, Pizzini FB, Boscolo Galazzo I, Cobelli C, Cotelli M, Manenti R, Frisoni GB (2017) Coordinate-based meta-analysis of the default mode and salience network for target identification in non-invasive brain stimulation of Alzheimer’s disease and behavior variant frontotemporal dementia networks. J Alzheimer’s Dis (Preprint):1–19 (in press)

  4. Koch K, Myers NE, Gottler J, Pasquini L, Grimmer T, Forster S, Manoliu A, Neitzel J, Kurz A, Forstl H, Riedl V, Wohlschlager AM, Drzezga A, Sorg C (2015) Disrupted intrinsic networks link amyloid-beta pathology and impaired cognition in prodromal Alzheimer’s disease. Cereb Cortex (New York, NY: 1991) 25(12):4678–4688. https://doi.org/10.1093/cercor/bhu151

    Google Scholar 

  5. Badhwar A, Tam A, Dansereau C, Orban P, Hoffstaedter F, Bellec P (2017) Resting-state network dysfunction in Alzheimer’s disease: a systematic review and meta-analysis. Alzheimer’s Dement (Amsterdam, Netherlands) 8:73–85. https://doi.org/10.1016/j.dadm.2017.03.007

    Google Scholar 

  6. Barkhof F, Haller S, Rombouts SA (2014) Resting-state functional MR imaging: a new window to the brain. Radiology 272(1):29–49. https://doi.org/10.1148/radiol.14132388

    Article  PubMed  Google Scholar 

  7. Rektorova I (2014) Resting-state networks in Alzheimer’s disease and Parkinson’s disease. Neurodegener Dis 13(2–3):186–188. https://doi.org/10.1159/000354237

    CAS  PubMed  Google Scholar 

  8. Buckner RL, Andrews-Hanna JR, Schacter DL (2008) The brain’s default network: anatomy, function, and relevance to disease. Ann N Y Acad Sci 1124:1–38. https://doi.org/10.1196/annals.1440.011

    Article  PubMed  Google Scholar 

  9. Qi Z, Wu X, Wang Z, Zhang N, Dong H, Yao L, Li K (2010) Impairment and compensation coexist in amnestic MCI default mode network. NeuroImage 50(1):48–55. https://doi.org/10.1016/j.neuroimage.2009.12.025

    Article  PubMed  Google Scholar 

  10. Yan H, Zhang Y, Chen H, Wang Y, Liu Y (2013) Altered effective connectivity of the default mode network in resting-state amnestic type mild cognitive impairment. J Int Neuropsychol Soc 19(4):400–409. https://doi.org/10.1017/s1355617712001580

    Article  PubMed  Google Scholar 

  11. Kim H (2012) A dual-subsystem model of the brain's default network: self-referential processing, memory retrieval processes, and autobiographical memory retrieval. NeuroImage 61(4):966–977. https://doi.org/10.1016/j.neuroimage.2012.03.025

    Article  CAS  PubMed  Google Scholar 

  12. Pasquini L, Scherr M, Tahmasian M, Meng C, Myers NE, Ortner M, Muhlau M, Kurz A, Forstl H, Zimmer C, Grimmer T, Wohlschlager AM, Riedl V, Sorg C (2015) Link between hippocampus’ raised local and eased global intrinsic connectivity in AD. Alzheimer’s Dement 11(5):475–484. https://doi.org/10.1016/j.jalz.2014.02.007

    Article  Google Scholar 

  13. Buckner RL, Snyder AZ, Shannon BJ, LaRossa G, Sachs R, Fotenos AF, Sheline YI, Klunk WE, Mathis CA, Morris JC, Mintun MA (2005) Molecular, structural, and functional characterization of Alzheimer’s disease: evidence for a relationship between default activity, amyloid, and memory. J Neurosci 25(34):7709–7717. https://doi.org/10.1523/JNEUROSCI.2177-05.2005

    Article  CAS  PubMed  Google Scholar 

  14. Cha J, Jo HJ, Kim HJ, Seo SW, Kim HS, Yoon U, Park H, Na DL, Lee JM (2013) Functional alteration patterns of default mode networks: comparisons of normal aging, amnestic mild cognitive impairment and Alzheimer’s disease. Eur J Neurosci 37(12):1916–1924. https://doi.org/10.1111/ejn.12177

    Article  PubMed  PubMed Central  Google Scholar 

  15. Binnewijzend MA, Schoonheim MM, Sanz-Arigita E, Wink AM, van der Flier WM, Tolboom N, Adriaanse SM, Damoiseaux JS, Scheltens P, van Berckel BN, Barkhof F (2012) Resting-state fMRI changes in Alzheimer’s disease and mild cognitive impairment. Neurobiol Aging 33(9):2018–2028. https://doi.org/10.1016/j.neurobiolaging.2011.07.003

    Article  PubMed  Google Scholar 

  16. Beckmann CF, DeLuca M, Devlin JT, Smith SM (2005) Investigations into resting-state connectivity using independent component analysis. Philos Trans R Soc Lond Ser B Biol Sci 360(1457):1001–1013. https://doi.org/10.1098/rstb.2005.1634

    Article  Google Scholar 

  17. Smitha KA, Akhil Raja K, Arun KM, Rajesh PG, Thomas B, Kapilamoorthy TR, Kesavadas C (2017) Resting state fMRI: a review on methods in resting state connectivity analysis and resting state networks. Neuroradiol J 1971400917697342:305–317. https://doi.org/10.1177/1971400917697342

    Article  Google Scholar 

  18. van den Heuvel MP, Hulshoff Pol HE (2010) Exploring the brain network: a review on resting-state fMRI functional connectivity. Eur Neuropsychopharmacol 20(8):519–534. https://doi.org/10.1016/j.euroneuro.2010.03.008

    Article  PubMed  Google Scholar 

  19. Jin M, Pelak VS, Cordes D (2012) Aberrant default mode network in subjects with amnestic mild cognitive impairment using resting-state functional MRI. Magn Reson Imaging 30(1):48–61. https://doi.org/10.1016/j.mri.2011.07.007

    Article  PubMed  Google Scholar 

  20. Song J, Qin W, Liu Y, Duan Y, Liu J, He X, Li K, Zhang X, Jiang T, Yu C (2013) Aberrant functional organization within and between resting-state networks in AD. PLoS One 8(5):e63727. https://doi.org/10.1371/journal.pone.0063727

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Sorg C, Riedl V, Muhlau M, Calhoun VD, Eichele T, Laer L, Drzezga A, Forstl H, Kurz A, Zimmer C, Wohlschlager AM (2007) Selective changes of resting-state networks in individuals at risk for Alzheimer’s disease. Proc Natl Acad Sci U S A 104(47):18760–18765. https://doi.org/10.1073/pnas.0708803104

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Hahn K, Myers N, Prigarin S, Rodenacker K, Kurz A, Forstl H, Zimmer C, Wohlschlager AM, Sorg C (2013) Selectively and progressively disrupted structural connectivity of functional brain networks in Alzheimer’s disease—revealed by a novel framework to analyze edge distributions of networks detecting disruptions with strong statistical evidence. NeuroImage 81:96–109. https://doi.org/10.1016/j.neuroimage.2013.05.011

    Article  PubMed  Google Scholar 

  23. Wang Y, Risacher SL, West JD, McDonald BC, Magee TR, Farlow MR, Gao S, O'Neill DP, Saykin AJ (2013) Altered default mode network connectivity in older adults with cognitive complaints and amnestic mild cognitive impairment. J Alzheimer's Dis 35(4):751–760. https://doi.org/10.3233/jad-130080

    Google Scholar 

  24. Lee ES, Yoo K, Lee YB, Chung J, Lim JE, Yoon B, Jeong Y (2016) Default mode network functional connectivity in early and late mild cognitive impairment: results from the Alzheimer’s disease neuroimaging initiative. Alzheimer Dis Assoc Disord 30(4):289–296. https://doi.org/10.1097/wad.0000000000000143

    Article  PubMed  Google Scholar 

  25. Bharath S, Joshi H, John JP, Balachandar R, Sadanand S, Saini J, Kumar KJ, Varghese M (2017) A multimodal structural and functional neuroimaging study of amnestic mild cognitive impairment. Am J Geriatr Psychiatry 25(2):158–169. https://doi.org/10.1016/j.jagp.2016.05.001

    Article  PubMed  Google Scholar 

  26. Bai F, Watson DR, Shi Y, Wang Y, Yue C, YuhuanTeng WD, Yuan Y, Zhang Z (2011) Specifically progressive deficits of brain functional marker in amnestic type mild cognitive impairment. PLoS One 6(9):e24271. https://doi.org/10.1371/journal.pone.0024271

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. De Vogelaere F, Santens P, Achten E, Boon P, Vingerhoets G (2012) Altered default-mode network activation in mild cognitive impairment compared with healthy aging. Neuroradiology 54(11):1195–1206. https://doi.org/10.1007/s00234-012-1036-6

    Article  PubMed  Google Scholar 

  28. Esposito R, Mosca A, Pieramico V, Cieri F, Cera N, Sensi SL (2013) Characterization of resting state activity in MCI individuals. PeerJ 1:e135. https://doi.org/10.7717/peerj.135

    Article  PubMed  PubMed Central  Google Scholar 

  29. Serra L, Cercignani M, Mastropasqua C, Torso M, Spano B, Makovac E, Viola V, Giulietti G, Marra C, Caltagirone C, Bozzali M (2016) Longitudinal changes in functional brain connectivity predicts conversion to Alzheimer’s disease. J Alzheimer’s Dis 51(2):377–389. https://doi.org/10.3233/jad-150961

    Article  Google Scholar 

  30. Adriaanse SM, Sanz-Arigita EJ, Binnewijzend MA, Ossenkoppele R, Tolboom N, van Assema DM, Wink AM, Boellaard R, Yaqub M, Windhorst AD, van der Flier WM, Scheltens P, Lammertsma AA, Rombouts SA, Barkhof F, van Berckel BN (2014) Amyloid and its association with default network integrity in Alzheimer’s disease. Hum Brain Mapp 35(3):779–791. https://doi.org/10.1002/hbm.22213

    Article  PubMed  Google Scholar 

  31. Zamboni G, Wilcock GK, Douaud G, Drazich E, McCulloch E, Filippini N, Tracey I, Brooks JCW, Smith SM, Jenkinson M, Mackay CE (2013) Resting functional connectivity reveals residual functional activity in Alzheimer’s disease. Biol Psychiatry 74(5):375–383. https://doi.org/10.1016/j.biopsych.2013.04.015

    Article  PubMed  Google Scholar 

  32. Radua J, Rubia K, Canales-Rodriguez EJ, Pomarol-Clotet E, Fusar-Poli P, Mataix-Cols D (2014) Anisotropic kernels for coordinate-based meta-analyses of neuroimaging studies. Front Psychiatry 5:13. https://doi.org/10.3389/fpsyt.2014.00013

    Article  PubMed  PubMed Central  Google Scholar 

  33. Alegria AA, Radua J, Rubia K (2016) Meta-analysis of fMRI studies of disruptive behavior disorders. Am J Psychiatry 173(11):1119–1130. https://doi.org/10.1176/appi.ajp.2016.15081089

    Article  PubMed  Google Scholar 

  34. Norman LJ, Carlisi C, Lukito S, Hart H, Mataix-Cols D, Radua J, Rubia K (2016) Structural and functional brain abnormalities in attention-deficit/hyperactivity disorder and obsessive-compulsive disorder: a comparative meta-analysis. JAMA Psychiat 73(8):815–825. https://doi.org/10.1001/jamapsychiatry.2016.0700

    Article  Google Scholar 

  35. Petersen RC, Smith GE, Waring SC, Ivnik RJ, Tangalos EG, Kokmen E (1999) Mild cognitive impairment: clinical characterization and outcome. Arch Neurol 56(3):303–308

    Article  CAS  PubMed  Google Scholar 

  36. Winblad B, Palmer K, Kivipelto M, Jelic V, Fratiglioni L, Wahlund LO, Nordberg A, Backman L, Albert M, Almkvist O, Arai H, Basun H, Blennow K, de Leon M, DeCarli C, Erkinjuntti T, Giacobini E, Graff C, Hardy J, Jack C, Jorm A, Ritchie K, van Duijn C, Visser P, Petersen RC (2004) Mild cognitive impairment—beyond controversies, towards a consensus: report of the International Working Group on Mild Cognitive Impairment. J Intern Med 256(3):240–246. https://doi.org/10.1111/j.1365-2796.2004.01380.x

    Article  CAS  PubMed  Google Scholar 

  37. Petersen RC (2004) Mild cognitive impairment as a diagnostic entity. J Intern Med 256(3):183–194. https://doi.org/10.1111/j.1365-2796.2004.01388.x

    Article  CAS  PubMed  Google Scholar 

  38. Albert MS, DeKosky ST, Dickson D, Dubois B, Feldman HH, Fox NC, Gamst A, Holtzman DM, Jagust WJ, Petersen RC, Snyder PJ, Carrillo MC, Thies B, Phelps CH (2011) The diagnosis of mild cognitive impairment due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s Dement 7(3):270–279. https://doi.org/10.1016/j.jalz.2011.03.008

    Article  Google Scholar 

  39. Pan P, Zhan H, Xia M, Zhang Y, Guan D, Xu Y (2017) Aberrant regional homogeneity in Parkinson’s disease: a voxel-wise meta-analysis of resting-state functional magnetic resonance imaging studies. Neurosci Biobehav Rev 72:223–231. https://doi.org/10.1016/j.neubiorev.2016.11.018

    Article  PubMed  Google Scholar 

  40. Iwabuchi SJ, Krishnadas R, Li C, Auer DP, Radua J, Palaniyappan L (2015) Localized connectivity in depression: a meta-analysis of resting state functional imaging studies. Neurosci Biobehav Rev 51:77–86. https://doi.org/10.1016/j.neubiorev.2015.01.006

    Article  PubMed  Google Scholar 

  41. Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, Moher D, Becker BJ, Sipe TA, Thacker SB (2000) Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA 283(15):2008–2012

    Article  CAS  PubMed  Google Scholar 

  42. Radua J, Grau M, van den Heuvel OA, Thiebaut de Schotten M, Stein DJ, Canales-Rodriguez EJ, Catani M, Mataix-Cols D (2014) Multimodal voxel-based meta-analysis of white matter abnormalities in obsessive-compulsive disorder. Neuropsychopharmacology 39(7):1547–1557. https://doi.org/10.1038/npp.2014.5

    Article  PubMed  PubMed Central  Google Scholar 

  43. Radua J, Mataix-Cols D (2009) Voxel-wise meta-analysis of grey matter changes in obsessive-compulsive disorder. Br J Psychiatry 195(5):393–402. https://doi.org/10.1192/bjp.bp.108.055046

    Article  PubMed  Google Scholar 

  44. Radua J, Mataix-Cols D, Phillips ML, El-Hage W, Kronhaus DM, Cardoner N, Surguladze S (2012) A new meta-analytic method for neuroimaging studies that combines reported peak coordinates and statistical parametric maps. Eur Psychiatry 27(8):605–611. https://doi.org/10.1016/j.eurpsy.2011.04.001

    Article  CAS  PubMed  Google Scholar 

  45. Lim L, Radua J, Rubia K (2014) Gray matter abnormalities in childhood maltreatment: a voxel-wise meta-analysis. Am J Psychiatry 171(8):854–863. https://doi.org/10.1176/appi.ajp.2014.13101427

    Article  PubMed  Google Scholar 

  46. Palaniyappan L, Balain V, Radua J, Liddle PF (2012) Structural correlates of auditory hallucinations in schizophrenia: a meta-analysis. Schizophr Res 137(1–3):169–173. https://doi.org/10.1016/j.schres.2012.01.038

    Article  PubMed  Google Scholar 

  47. Agosta F, Pievani M, Geroldi C, Copetti M, Frisoni GB, Filippi M (2012) Resting state fMRI in Alzheimer’s disease: beyond the default mode network. Neurobiol Aging 33(8):1564–1578. https://doi.org/10.1016/j.neurobiolaging.2011.06.007

    Article  PubMed  Google Scholar 

  48. Minati L, Chan D, Mastropasqua C, Serra L, Spano B, Marra C, Caltagirone C, Cercignani M, Bozzali M (2014) Widespread alterations in functional brain network architecture in amnestic mild cognitive impairment. J Alzheimer's Dis 40(1):213–220. https://doi.org/10.3233/jad-131766

    Google Scholar 

  49. Yi D, Choe YM, Byun MS, Sohn BK, Seo EH, Han J, Park J, Woo JI, Lee DY (2015) Differences in functional brain connectivity alterations associated with cerebral amyloid deposition in amnestic mild cognitive impairment. Front Aging Neurosci 7:1–10. https://doi.org/10.3389/fnagi.2015.00015

    Article  CAS  Google Scholar 

  50. Fransson P, Marrelec G (2008) The precuneus/posterior cingulate cortex plays a pivotal role in the default mode network: evidence from a partial correlation network analysis. NeuroImage 42(3):1178–1184. https://doi.org/10.1016/j.neuroimage.2008.05.059

    Article  PubMed  Google Scholar 

  51. Jacobs HI, Radua J, Luckmann HC, Sack AT (2013) Meta-analysis of functional network alterations in Alzheimer’s disease: toward a network biomarker. Neurosci Biobehav Rev 37(5):753–765. https://doi.org/10.1016/j.neubiorev.2013.03.009

    Article  PubMed  Google Scholar 

  52. Jacobs HI, Van Boxtel MP, Jolles J, Verhey FR, Uylings HB (2012) Parietal cortex matters in Alzheimer’s disease: an overview of structural, functional and metabolic findings. Neurosci Biobehav Rev 36(1):297–309. https://doi.org/10.1016/j.neubiorev.2011.06.009

    Article  PubMed  Google Scholar 

  53. Jack CR Jr, Wiste HJ, Vemuri P, Weigand SD, Senjem ML, Zeng G, Bernstein MA, Gunter JL, Pankratz VS, Aisen PS, Weiner MW, Petersen RC, Shaw LM, Trojanowski JQ, Knopman DS (2010) Brain beta-amyloid measures and magnetic resonance imaging atrophy both predict time-to-progression from mild cognitive impairment to Alzheimer’s disease. Brain 133(11):3336–3348. https://doi.org/10.1093/brain/awq277

    Article  PubMed  PubMed Central  Google Scholar 

  54. Klunk WE, Engler H, Nordberg A, Wang Y, Blomqvist G, Holt DP, Bergstrom M, Savitcheva I, Huang GF, Estrada S, Ausen B, Debnath ML, Barletta J, Price JC, Sandell J, Lopresti BJ, Wall A, Koivisto P, Antoni G, Mathis CA, Langstrom B (2004) Imaging brain amyloid in Alzheimer’s disease with Pittsburgh Compound-B. Ann Neurol 55(3):306–319. https://doi.org/10.1002/ana.20009

    Article  CAS  PubMed  Google Scholar 

  55. Vemuri P, Jones DT, Jack CR Jr (2012) Resting state functional MRI in Alzheimer’s Disease. Alzheimer’s Res Ther 4(1):2. https://doi.org/10.1186/alzrt100

    Article  Google Scholar 

  56. Bai F, Watson DR, Yu H, Shi Y, Yuan Y, Zhang Z (2009) Abnormal resting-state functional connectivity of posterior cingulate cortex in amnestic type mild cognitive impairment. Brain Res 1302:167–174. https://doi.org/10.1016/j.brainres.2009.09.028

    Article  CAS  PubMed  Google Scholar 

  57. Gili T, Cercignani M, Serra L, Perri R, Giove F, Maraviglia B, Caltagirone C, Bozzali M (2011) Regional brain atrophy and functional disconnection across Alzheimer’s disease evolution. J Neurol Neurosurg Psychiatry 82(1):58–66. https://doi.org/10.1136/jnnp.2009.199935

    Article  CAS  PubMed  Google Scholar 

  58. Yuan B, Xie C, Shu H, Liao W, Wang Z, Liu D, Zhang Z (2016) Differential effects of APOE genotypes on the anterior and posterior subnetworks of default mode network in amnestic mild cognitive impairment. J Alzheimer's Dis 54(4):1409–1423. https://doi.org/10.3233/JAD-160353

    Article  CAS  Google Scholar 

  59. Joo SH, Lee CU, Lim HK (2017) Apathy and intrinsic functional connectivity networks in amnestic mild cognitive impairment. Neuropsychiatr Dis Treat 13:61–67. https://doi.org/10.2147/NDT.S123338

    Article  PubMed  Google Scholar 

  60. Han SD, Arfanakis K, Fleischman DA, Leurgans SE, Tuminello ER, Edmonds EC, Bennett DA (2012) Functional connectivity variations in mild cognitive impairment: associations with cognitive function. J Int Neuropsychol Soc 18(1):39–48. https://doi.org/10.1017/S1355617711001299

    Article  PubMed  Google Scholar 

  61. Yang H, Wang C, Zhang Y, Xia L, Feng Z, Li D, Xu S, Xie H, Chen F, Shi Y, Wang J (2017) Disrupted causal connectivity anchored in the posterior cingulate cortex in amnestic mild cognitive impairment. Front Neurol 8(10). https://doi.org/10.3389/fneur.2017.00010

  62. Pan P, Zhu L, Yu T, Shi H, Zhang B, Qin R, Zhu X, Qian L, Zhao H, Zhou H, Xu Y (2017) Aberrant spontaneous low-frequency brain activity in amnestic mild cognitive impairment: a meta-analysis of resting-state fMRI studies. Ageing Res Rev 35:12–21. https://doi.org/10.1016/j.arr.2016.12.001

    Article  PubMed  Google Scholar 

  63. Yuan X, Han Y, Wei Y, Xia M, Sheng C, Jia J, He Y (2016) Regional homogeneity changes in amnestic mild cognitive impairment patients. Neurosci Lett 629:1–8. https://doi.org/10.1016/j.neulet.2016.06.047

    Article  CAS  PubMed  Google Scholar 

  64. Langbaum JB, Chen K, Lee W, Reschke C, Bandy D, Fleisher AS, Alexander GE, Foster NL, Weiner MW, Koeppe RA, Jagust WJ, Reiman EM (2009) Categorical and correlational analyses of baseline fluorodeoxyglucose positron emission tomography images from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). NeuroImage 45(4):1107–1116. https://doi.org/10.1016/j.neuroimage.2008.12.072

    Article  PubMed  PubMed Central  Google Scholar 

  65. Dai W, Lopez OL, Carmichael OT, Becker JT, Kuller LH, Gach HM (2009) Mild cognitive impairment and Alzheimer disease: patterns of altered cerebral blood flow at MR imaging. Radiology 250(3):856–866. https://doi.org/10.1148/radiol.2503080751

    Article  PubMed  PubMed Central  Google Scholar 

  66. Hirao K, Ohnishi T, Hirata Y, Yamashita F, Mori T, Moriguchi Y, Matsuda H, Nemoto K, Imabayashi E, Yamada M, Iwamoto T, Arima K, Asada T (2005) The prediction of rapid conversion to Alzheimer’s disease in mild cognitive impairment using regional cerebral blood flow SPECT. NeuroImage 28(4):1014–1021. https://doi.org/10.1016/j.neuroimage.2005.06.066

    Article  PubMed  Google Scholar 

  67. Nickl-Jockschat T, Kleiman A, Schulz JB, Schneider F, Laird AR, Fox PT, Eickhoff SB, Reetz K (2012) Neuroanatomic changes and their association with cognitive decline in mild cognitive impairment: a meta-analysis. Brain Struct Funct 217(1):115–125. https://doi.org/10.1007/s00429-011-0333-x

    Article  PubMed  Google Scholar 

  68. Chirles TJ, Reiter K, Weiss LR, Alfini AJ, Nielson KA, Smith JC (2017) Exercise training and functional connectivity changes in mild cognitive impairment and healthy elders. J Alzheimer's Dis 57(3):845–856. https://doi.org/10.3233/JAD-161151

    Article  Google Scholar 

  69. Leech R, Sharp DJ (2014) The role of the posterior cingulate cortex in cognition and disease. Brain 137(Pt 1):12–32. https://doi.org/10.1093/brain/awt162

    Article  PubMed  Google Scholar 

  70. Wang P, Li J, Li HJ, Huo L, Li R (2016) Mild cognitive impairment is not “mild” at all in altered activation of episodic memory brain networks: evidence from ALE meta-analysis. Front Aging Neurosci 8:260. https://doi.org/10.3389/fnagi.2016.00260

    PubMed  PubMed Central  Google Scholar 

  71. Dickerson BC, Sperling RA (2009) Large-scale functional brain network abnormalities in Alzheimer’s disease: insights from functional neuroimaging. Behav Neurol 21(1):63–75. https://doi.org/10.3233/BEN-2009-0227

    Article  PubMed  PubMed Central  Google Scholar 

  72. Perri R, Serra L, Carlesimo GA, Caltagirone C, Early Diagnosis Group of the Italian Interdisciplinary Network on Alzheimer’s D (2007) Amnestic mild cognitive impairment: difference of memory profile in subjects who converted or did not convert to Alzheimer’s disease. Neuropsychology 21(5):549–558. https://doi.org/10.1037/0894-4105.21.5.549

    Article  PubMed  Google Scholar 

  73. Terry DP, Sabatinelli D, Puente AN, Lazar NA, Miller LS (2015) A meta-analysis of fMRI activation differences during episodic memory in Alzheimer’s disease and mild cognitive impairment. J Neuroimaging 25(6):849–860. https://doi.org/10.1111/jon.12266

    Article  PubMed  Google Scholar 

  74. Filippi M, Agosta F, Scola E, Canu E, Magnani G, Marcone A, Valsasina P, Caso F, Copetti M, Comi G, Cappa SF, Falini A (2013) Functional network connectivity in the behavioral variant of frontotemporal dementia. Cortex 49(9):2389–2401. https://doi.org/10.1016/j.cortex.2012.09.017

    Article  PubMed  Google Scholar 

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We thank all the authors of the included studies.

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Correspondence to WeiFeng Guo.

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Wang, C., Pan, Y., Liu, Y. et al. Aberrant default mode network in amnestic mild cognitive impairment: a meta-analysis of independent component analysis studies. Neurol Sci 39, 919–931 (2018). https://doi.org/10.1007/s10072-018-3306-5

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  • DOI: https://doi.org/10.1007/s10072-018-3306-5

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