Advertisement

Functional Connectivity in Dementia

  • Hugo Botha
  • David T. Jones
Chapter
Part of the Contemporary Clinical Neuroscience book series (CCNE)

Abstract

Novel structural and functional techniques have allowed in vivo analysis of large, distributed brain networks. Probing the systems or network level has been of particular interest in the field of neurodegenerative disease as it has become increasingly clear that degenerative diseases target large-scale brain networks. Task-free functional MRI (TF-fMRI) is a particularly appealing technique since it is safe, requires minimal patient cooperation (important in diseased populations), can be performed on most commercial MRI machines, and results in data that can be shared between centers easily. In this chapter, we provide a brief introduction to TF-fMRI, including the principles underlying the BOLD signal, image preprocessing, and data analysis. We then review age-related connectivity changes before moving on to Alzheimer’s disease, which is our primary focus within the dementias. Following this, we briefly review alterations in function connectivity in non-Alzheimer’s dementias. Finally, we discuss the future of functional connectivity in neurodegenerative research and clinical practice.

Keywords

Functional connectivity Alzheimer’s disease Functional MRI Networks 

References

  1. 1.
    Seeley WW, Crawford RK, Zhou J, Miller BL, Greicius MD (2009) Neurodegenerative diseases target large-scale human brain networks. Neuron 62(1):42–52.  https://doi.org/10.1016/j.neuron.2009.03.024CrossRefPubMedPubMedCentralGoogle Scholar
  2. 2.
    Fleisher AS, Sherzai A, Taylor C, Langbaum JB, Chen K, Buxton RB (2009) Resting-state BOLD networks versus task-associated functional MRI for distinguishing Alzheimer’s disease risk groups. Neuroimage 47(4):1678–1690.  https://doi.org/10.1016/j.neuroimage.2009.06.021CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Biswal B, Yetkin FZ, Haughton VM, Hyde JS (1995) Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med 34(4):537–541CrossRefPubMedGoogle Scholar
  4. 4.
    Smith SM, Fox PT, Miller KL, Glahn DC, Fox PM, Mackay CE, Filippini N, Watkins KE, Toro R, Laird AR, Beckmann CF (2009) Correspondence of the brain’s functional architecture during activation and rest. Proc Natl Acad Sci U S A 106(31):13040–13045.  https://doi.org/10.1073/pnas.0905267106CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Damoiseaux JS, Rombouts SA, Barkhof F, Scheltens P, Stam CJ, Smith SM, Beckmann CF (2006) Consistent resting-state networks across healthy subjects. Proc Natl Acad Sci U S A 103(37):13848–13853.  https://doi.org/10.1073/pnas.0601417103CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Jo HJ, Gotts SJ, Reynolds RC, Bandettini PA, Martin A, Cox RW, Saad ZS (2013) Effective preprocessing procedures virtually eliminate distance-dependent motion artifacts in resting state FMRI. J Appl Math 2013.  https://doi.org/10.1155/2013/935154
  7. 7.
    Power JD, Plitt M, Kundu P, Bandettini PA, Martin A (2017) Temporal interpolation alters motion in fMRI scans: magnitudes and consequences for artifact detection. PLoS One 12(9):e0182939.  https://doi.org/10.1371/journal.pone.0182939CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Behzadi Y, Restom K, Liau J, Liu TT (2007) A component based noise correction method (CompCor) for BOLD and perfusion based fMRI. Neuroimage 37(1):90–101.  https://doi.org/10.1016/j.neuroimage.2007.04.042CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Pruim RH, Mennes M, van Rooij D, Llera A, Buitelaar JK, Beckmann CF (2015) ICA-AROMA: a robust ICA-based strategy for removing motion artifacts from fMRI data. Neuroimage 112:267–277.  https://doi.org/10.1016/j.neuroimage.2015.02.064CrossRefPubMedGoogle Scholar
  10. 10.
    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/alzrt100CrossRefGoogle Scholar
  11. 11.
    Jones DT, Vemuri P, Murphy MC, Gunter JL, Senjem ML, Machulda MM, Przybelski SA, Gregg BE, Kantarci K, Knopman DS, Boeve BF, Petersen RC, Jack CR Jr (2012) Non-stationarity in the “resting brain’s” modular architecture. PLoS One 7(6):e39731.  https://doi.org/10.1371/journal.pone.0039731CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Travers J, Milgram S (1969) An experimental study of the small world problem. Sociometry 32(4):425–443.  https://doi.org/10.2307/2786545CrossRefGoogle Scholar
  13. 13.
    Watts DJ, Strogatz SH (1998) Collective dynamics of “small-world” networks. Nature 393(6684):3CrossRefGoogle Scholar
  14. 14.
    Fornito A, Zalesky A, Edward T (2016) Bullmore. Academic Press, San Diego. ISBN 9780124079083Google Scholar
  15. 15.
    Sala-Llonch R, Bartres-Faz D, Junque C (2015) Reorganization of brain networks in aging: a review of functional connectivity studies. Front Psych 6:663.  https://doi.org/10.3389/fpsyg.2015.00663CrossRefGoogle Scholar
  16. 16.
    Damoiseaux JS (2017) Effects of aging on functional and structural brain connectivity. Neuroimage.  https://doi.org/10.1016/j.neuroimage.2017.01.077
  17. 17.
    Ferreira LK, Regina AC, Kovacevic N, Martin Mda G, Santos PP, Carneiro Cde G, Kerr DS, Amaro E Jr, McIntosh AR, Busatto GF (2016) Aging effects on whole-brain functional connectivity in adults free of cognitive and psychiatric disorders. Cereb Cortex 26(9):3851–3865.  https://doi.org/10.1093/cercor/bhv190CrossRefPubMedGoogle Scholar
  18. 18.
    Geerligs L, Renken RJ, Saliasi E, Maurits NM, Lorist MM (2015) A brain-wide study of age-related changes in functional connectivity. Cereb Cortex 25(7):1987–1999.  https://doi.org/10.1093/cercor/bhu012CrossRefPubMedGoogle Scholar
  19. 19.
    Chan MY, Park DC, Savalia NK, Petersen SE, Wig GS (2014) Decreased segregation of brain systems across the healthy adult lifespan. Proc Natl Acad Sci U S A 111(46):E4997–E5006.  https://doi.org/10.1073/pnas.1415122111CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Song J, Birn RM, Boly M, Meier TB, Nair VA, Meyerand ME, Prabhakaran V (2014) Age-related reorganizational changes in modularity and functional connectivity of human brain networks. Brain Connect 4(9):662–676.  https://doi.org/10.1089/brain.2014.0286CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Grady CL, Garrett DD (2014) Understanding variability in the BOLD signal and why it matters for aging. Brain Imaging Behav 8(2):274–283.  https://doi.org/10.1007/s11682-013-9253-0CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Park DC, Reuter-Lorenz P (2009) The adaptive brain: aging and neurocognitive scaffolding. Annu Rev Psychol 60:173–196.  https://doi.org/10.1146/annurev.psych.59.103006.093656CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Goh JO (2011) Functional dedifferentiation and altered connectivity in older adults: neural accounts of cognitive aging. Aging Dis 2(1):30–48PubMedPubMedCentralGoogle Scholar
  24. 24.
    Wu JT, Wu HZ, Yan CG, Chen WX, Zhang HY, He Y, Yang HS (2011) Aging-related changes in the default mode network and its anti-correlated networks: a resting-state fMRI study. Neurosci Lett 504(1):62–67.  https://doi.org/10.1016/j.neulet.2011.08.059CrossRefPubMedGoogle Scholar
  25. 25.
    Meier TB, Desphande AS, Vergun S, Nair VA, Song J, Biswal BB, Meyerand ME, Birn RM, Prabhakaran V (2012) Support vector machine classification and characterization of age-related reorganization of functional brain networks. Neuroimage 60(1):601–613.  https://doi.org/10.1016/j.neuroimage.2011.12.052CrossRefPubMedGoogle Scholar
  26. 26.
    Chai XJ, Ofen N, Gabrieli JD, Whitfield-Gabrieli S (2014) Selective development of anticorrelated networks in the intrinsic functional organization of the human brain. J Cogn Neurosci 26(3):501–513.  https://doi.org/10.1162/jocn_a_00517CrossRefPubMedGoogle Scholar
  27. 27.
    Ferreira LK, Busatto GF (2013) Resting-state functional connectivity in normal brain aging. Neurosci Biobehav Rev 37(3):384–400.  https://doi.org/10.1016/j.neubiorev.2013.01.017CrossRefPubMedGoogle Scholar
  28. 28.
    Stam CJ (2010) Characterization of anatomical and functional connectivity in the brain: a complex networks perspective. Int J Psychophysiol 77(3):186–194.  https://doi.org/10.1016/j.ijpsycho.2010.06.024CrossRefPubMedGoogle Scholar
  29. 29.
    Hawellek DJ, Hipp JF, Lewis CM, Corbetta M, Engel AK (2011) Increased functional connectivity indicates the severity of cognitive impairment in multiple sclerosis. Proc Natl Acad Sci U S A 108(47):19066–19071.  https://doi.org/10.1073/pnas.1110024108CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    Bonnelle V, Ham TE, Leech R, Kinnunen KM, Mehta MA, Greenwood RJ, Sharp DJ (2012) Salience network integrity predicts default mode network function after traumatic brain injury. Proc Natl Acad Sci U S A 109(12):4690–4695.  https://doi.org/10.1073/pnas.1113455109CrossRefPubMedPubMedCentralGoogle Scholar
  31. 31.
    Brier MR, Thomas JB, Snyder AZ, Wang L, Fagan AM, Benzinger T, Morris JC, Ances BM (2014) Unrecognized preclinical Alzheimer disease confounds rs-fcMRI studies of normal aging. Neurology 83(18):1613–1619.  https://doi.org/10.1212/WNL.0000000000000939CrossRefPubMedPubMedCentralGoogle Scholar
  32. 32.
    Jones DT, Machulda MM, Vemuri P, McDade EM, Zeng G, Senjem ML, Gunter JL, Przybelski SA, Avula RT, Knopman DS, Boeve BF, Petersen RC, Jack CR Jr (2011) Age-related changes in the default mode network are more advanced in Alzheimer’s disease. Neurology 77(16):1524–1531.  https://doi.org/10.1212/WNL.0b013e318233b33dCrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Cabeza R (2002) Hemispheric asymmetry reduction in older adults: the HAROLD model. Psychol Aging 17(1):85–100CrossRefPubMedGoogle Scholar
  34. 34.
    Reuter-Lorenz PA, Cappell KA (2008) Neurocognitive aging and the compensation hypothesis. Curr Dir Psychol Sci 17(3):177–182CrossRefGoogle Scholar
  35. 35.
    Davis SW, Dennis NA, Daselaar SM, Fleck MS, Cabeza R (2008) Que. PASA? The posterior-anterior shift in aging. Cereb Cortex 18(5):1201–1209.  https://doi.org/10.1093/cercor/bhm155CrossRefPubMedGoogle Scholar
  36. 36.
    Greicius MD, Srivastava G, Reiss AL, Menon V (2004) Default-mode network activity distinguishes Alzheimer’s disease from healthy aging: evidence from functional MRI. Proc Natl Acad Sci U S A 101(13):4637–4642.  https://doi.org/10.1073/pnas.0308627101CrossRefPubMedPubMedCentralGoogle Scholar
  37. 37.
    Raichle ME (2015) The brain’s default mode network. Annu Rev Neurosci 38:433–447.  https://doi.org/10.1146/annurev-neuro-071013-014030CrossRefPubMedGoogle Scholar
  38. 38.
    Lee ES, Yoo K, Lee YB, Chung J, Lim JE, Yoon B, Jeong Y, Alzheimer’s Disease Neuroimaging I (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.0000000000000143CrossRefPubMedGoogle Scholar
  39. 39.
    Tao W, Li X, Zhang J, Chen Y, Ma C, Liu Z, Yang C, Wang W, Chen K, Wang J, Zhang Z (2017) Inflection point in course of mild cognitive impairment: increased functional connectivity of default mode network. J Alzheimers Dis 60(2):679–690.  https://doi.org/10.3233/jad-170,252CrossRefPubMedGoogle Scholar
  40. 40.
    Wang Z, Liang P, Jia X, Jin G, Song H, Han Y, Lu J, Li K (2012) The baseline and longitudinal changes of PCC connectivity in mild cognitive impairment: a combined structure and resting-state fMRI study. PLoS One 7(5):e36838.  https://doi.org/10.1371/journal.pone.0036838CrossRefPubMedPubMedCentralGoogle Scholar
  41. 41.
    Wang Z, Liang P, Jia X, Qi Z, Yu L, Yang Y, Zhou W, Lu J, Li K (2011) Baseline and longitudinal patterns of hippocampal connectivity in mild cognitive impairment: evidence from resting state fMRI. J Neurol Sci 309(1–2):79–85.  https://doi.org/10.1016/j.jns.2011.07.017CrossRefPubMedGoogle Scholar
  42. 42.
    Damoiseaux JS, Prater KE, Miller BL, Greicius MD (2012) Functional connectivity tracks clinical deterioration in Alzheimer’s disease. Neurobiol Aging 33(4):828.e819–828.e830.  https://doi.org/10.1016/j.neurobiolaging.2011.06.024CrossRefGoogle Scholar
  43. 43.
    Jones DT, Knopman DS, Gunter JL, Graff-Radford J, Vemuri P, Boeve BF, Petersen RC, Weiner MW, Jack CR Jr, Alzheimer’s Disease Neuroimaging I (2016) Cascading network failure across the Alzheimer’s disease spectrum. Brain 139(Pt 2):547–562.  https://doi.org/10.1093/brain/awv338CrossRefPubMedGoogle Scholar
  44. 44.
    Li M, Zheng G, Zheng Y, Xiong Z, Xia R, Zhou W, Wang Q, Liang S, Tao J, Chen L (2017) Alterations in resting-state functional connectivity of the default mode network in amnestic mild cognitive impairment: an fMRI study. BMC Med Imaging 17(1):48.  https://doi.org/10.1186/s12880-017-0221-9CrossRefPubMedPubMedCentralGoogle Scholar
  45. 45.
    Chen G, Ward BD, Xie C, Li W, Wu Z, Jones JL, Franczak M, Antuono P, Li SJ (2011) Classification of Alzheimer disease, mild cognitive impairment, and normal cognitive status with large-scale network analysis based on resting-state functional MR imaging. Radiology 259(1):213–221.  https://doi.org/10.1148/radiol.10100734CrossRefPubMedPubMedCentralGoogle Scholar
  46. 46.
    Zhou B, Yao H, Wang P, Zhang Z, Zhan Y, Ma J, Xu K, Wang L, An N, Liu Y, Zhang X (2015) Aberrant functional connectivity architecture in Alzheimer’s disease and mild cognitive impairment: a whole-brain, data-driven analysis. Biomed Res Int 2015:495375.  https://doi.org/10.1155/2015/495375CrossRefPubMedPubMedCentralGoogle Scholar
  47. 47.
    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 (2016) Abnormal resting-state functional connectivity strength in mild cognitive impairment and its conversion to Alzheimer’s disease. Neural Plast 2016:4680972.  https://doi.org/10.1155/2016/4680972CrossRefPubMedGoogle Scholar
  48. 48.
    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.2011.07.003CrossRefPubMedGoogle Scholar
  49. 49.
    Lehmann M, Madison CM, Ghosh PM, Seeley WW, Mormino E, Greicius MD, Gorno-Tempini ML, Kramer JH, Miller BL, Jagust WJ, Rabinovici GD (2013) Intrinsic connectivity networks in healthy subjects explain clinical variability in Alzheimer’s disease. Proc Natl Acad Sci U S A 110(28):11606–11,611.  https://doi.org/10.1073/pnas.1221536110CrossRefPubMedPubMedCentralGoogle Scholar
  50. 50.
    Ranasinghe KG, Hinkley LB, Beagle AJ, Mizuiri D, Dowling AF, Honma SM, Finucane MM, Scherling C, Miller BL, Nagarajan SS, Vossel KA (2014) Regional functional connectivity predicts distinct cognitive impairments in Alzheimer’s disease spectrum. Neuroimage Clin 5:385–395.  https://doi.org/10.1016/j.nicl.2014.07.006CrossRefPubMedPubMedCentralGoogle Scholar
  51. 51.
    Lehmann M, Madison C, Ghosh PM, Miller ZA, Greicius MD, Kramer JH, Coppola G, Miller BL, Jagust WJ, Gorno-Tempini ML, Seeley WW, Rabinovici GD (2015) Loss of functional connectivity is greater outside the default mode network in nonfamilial early-onset Alzheimer’s disease variants. Neurobiol Aging 36(10):2678–2686.  https://doi.org/10.1016/j.neurobiolaging.2015.06.029CrossRefPubMedPubMedCentralGoogle Scholar
  52. 52.
    Dickerson BC, Brickhouse M, McGinnis S, Wolk DA (2017) Alzheimer’s disease: The influence of age on clinical heterogeneity through the human brain connectome. Alzheimers Dement 6:122–135.  https://doi.org/10.1016/j.dadm.2016.12.007CrossRefGoogle Scholar
  53. 53.
    Whitwell JL, Jones DT, Duffy JR, Strand EA, Machulda MM, Przybelski SA, Vemuri P, Gregg BE, Gunter JL, Senjem ML, Petersen RC, Jack CR Jr, Josephs KA (2015) Working memory and language network dysfunctions in logopenic aphasia: a task-free fMRI comparison with Alzheimer’s dementia. Neurobiol Aging 36(3):1245–1252.  https://doi.org/10.1016/j.neurobiolaging.2014.12.013CrossRefPubMedGoogle Scholar
  54. 54.
    Migliaccio R, Gallea C, Kas A, Perlbarg V, Samri D, Trotta L, Michon A, Lacomblez L, Dubois B, Lehericy S, Bartolomeo P (2016) Functional connectivity of ventral and dorsal visual streams in posterior cortical atrophy. J Alzheimers Dis 51(4):1119–1130.  https://doi.org/10.3233/jad-150934CrossRefPubMedGoogle Scholar
  55. 55.
    Sheline YI, Morris JC, Snyder AZ, Price JL, Yan Z, D’Angelo G, Liu C, Dixit S, Benzinger T, Fagan A, Goate A, Mintun MA (2010) APOE4 allele disrupts resting state fMRI connectivity in the absence of amyloid plaques or decreased CSF Abeta42. J Neurosci 30(50):17035–17040.  https://doi.org/10.1523/jneurosci.3987-10.2010CrossRefPubMedPubMedCentralGoogle Scholar
  56. 56.
    Zheng LJ, Su YY, Wang YF, Schoepf UJ, Varga-Szemes A, Pannell J, Liang X, Zheng G, Lu GM, Yang GF, Zhang LJ (2017) Different Hippocampus functional connectivity patterns in healthy young adults with mutations of APP/Presenilin-1/2 and APOEepsilon4. Mol Neurobiol.  https://doi.org/10.1007/s12035-017-0540-4
  57. 57.
    Shen J, Qin W, Xu Q, Xu L, Xu J, Zhang P, Liu H, Liu B, Jiang T, Yu C (2017) Modulation of APOE and SORL1 genes on hippocampal functional connectivity in healthy young adults. Brain Struct Funct 222(6):2877–2889.  https://doi.org/10.1007/s00429-017-1377-3CrossRefPubMedPubMedCentralGoogle Scholar
  58. 58.
    Machulda MM, Jones DT, Vemuri P, McDade E, Avula R, Przybelski S, Boeve BF, Knopman DS, Petersen RC, Jack CR Jr (2011) Effect of APOE epsilon4 status on intrinsic network connectivity in cognitively normal elderly subjects. Arch Neurol 68(9):1131–1136.  https://doi.org/10.1001/archneurol.2011.108CrossRefPubMedPubMedCentralGoogle Scholar
  59. 59.
    Thomas JB, Brier MR, Bateman RJ, Snyder AZ, Benzinger TL, Xiong C, Raichle M, Holtzman DM, Sperling RA, Mayeux R, Ghetti B, Ringman JM, Salloway S, McDade E, Rossor MN, Ourselin S, Schofield PR, Masters CL, Martins RN, Weiner MW, Thompson PM, Fox NC, Koeppe RA, Jack CR Jr, Mathis CA, Oliver A, Blazey TM, Moulder K, Buckles V, Hornbeck R, Chhatwal J, Schultz AP, Goate AM, Fagan AM, Cairns NJ, Marcus DS, Morris JC, Ances BM (2014) Functional connectivity in autosomal dominant and late-onset Alzheimer disease. JAMA Neurol 71(9):1111–1122.  https://doi.org/10.1001/jamaneurol.2014.1654CrossRefPubMedPubMedCentralGoogle Scholar
  60. 60.
    Wang L, Roe CM, Snyder AZ, Brier MR, Thomas JB, Xiong C, Benzinger TL, Morris JC, Ances BM (2012) Alzheimer disease family history impacts resting state functional connectivity. Ann Neurol 72(4):571–577.  https://doi.org/10.1002/ana.23643CrossRefPubMedPubMedCentralGoogle Scholar
  61. 61.
    Jack CR Jr, Wiste HJ, Weigand SD, Knopman DS, Lowe V, Vemuri P, Mielke MM, Jones DT, Senjem ML, Gunter JL, Gregg BE, Pankratz VS, Petersen RC (2013) Amyloid-first and neurodegeneration-first profiles characterize incident amyloid PET positivity. Neurology 81(20):1732–1740.  https://doi.org/10.1212/01.wnl.0000435556.21319.e4CrossRefPubMedPubMedCentralGoogle Scholar
  62. 62.
    Jones DT, Graff-Radford J, Lowe VJ, Wiste HJ, Gunter JL, Senjem ML, Botha H, Kantarci K, Boeve BF, Knopman DS, Petersen RC, Jack CR Jr (2017) Tau, amyloid, and cascading network failure across the Alzheimer’s disease spectrum. Cortex.  https://doi.org/10.1016/j.cortex.2017.09.018
  63. 63.
    Schultz AP, Chhatwal JP, Hedden T, Mormino EC, Hanseeuw BJ, Sepulcre J, Huijbers W, LaPoint M, Buckley RF, Johnson KA, Sperling RA (2017) Phases of hyperconnectivity and hypoconnectivity in the default mode and salience networks track with Amyloid and Tau in clinically normal individuals. J Neurosci 37(16):4323–4331.  https://doi.org/10.1523/jneurosci.3263-16.2017CrossRefPubMedPubMedCentralGoogle Scholar
  64. 64.
    Sepulcre J, Sabuncu MR, Li Q, El Fakhri G, Sperling R, Johnson KA (2017) Tau and amyloid-beta proteins distinctively associate to functional network changes in the aging brain. Alzheimers Dement.  https://doi.org/10.1016/j.jalz.2017.02.011
  65. 65.
    Jones DT, Lowe VJ, Wiste HJ, Senjem ML, Radford JG, Boeve BF, Knopman DS, Petersen RC, Jack CR Jr (2016) NETWORK-BASED TAU DEPOSITION PATTERNS ARE RELATED TO FUNCTIONAL NETWORK FAILURE LARGELY VIA BETA-AMYLOID ACROSS THE ALZHEIMER’S SPECTRUM. Alzheimers Dement 12(7):P11–P12.  https://doi.org/10.1016/j.jalz.2016.06.074CrossRefGoogle Scholar
  66. 66.
    Amboni M, Tessitore A, Esposito F, Santangelo G, Picillo M, Vitale C, Giordano A, Erro R, de Micco R, Corbo D, Tedeschi G, Barone P (2015) Resting-state functional connectivity associated with mild cognitive impairment in Parkinson’s disease. J Neurol 262(2):425–434.  https://doi.org/10.1007/s00415-014-7591-5CrossRefPubMedGoogle Scholar
  67. 67.
    Kobeleva X, Firbank M, Peraza L, Gallagher P, Thomas A, Burn DJ, O’Brien J, Taylor JP (2017) Divergent functional connectivity during attentional processing in Lewy body dementia and Alzheimer’s disease. Cortex 92:8–18.  https://doi.org/10.1016/j.cortex.2017.02.016CrossRefPubMedPubMedCentralGoogle Scholar
  68. 68.
    Peraza LR, Kaiser M, Firbank M, Graziadio S, Bonanni L, Onofrj M, Colloby SJ, Blamire A, O’Brien J, Taylor JP (2014) fMRI resting state networks and their association with cognitive fluctuations in dementia with Lewy bodies. Neuroimage Clin 4:558–565.  https://doi.org/10.1016/j.nicl.2014.03.013CrossRefPubMedPubMedCentralGoogle Scholar
  69. 69.
    Peraza LR, Colloby SJ, Firbank MJ, Greasy GS, McKeith IG, Kaiser M, O’Brien J, Taylor JP (2015) Resting state in Parkinson’s disease dementia and dementia with Lewy bodies: commonalities and differences. Int J Geriatr Psychiatry 30(11):1135–1146.  https://doi.org/10.1002/gps.4342CrossRefPubMedPubMedCentralGoogle Scholar
  70. 70.
    Kenny ER, Blamire AM, Firbank MJ, O’Brien JT (2012) Functional connectivity in cortical regions in dementia with Lewy bodies and Alzheimer’s disease. Brain 135(Pt 2):569–581.  https://doi.org/10.1093/brain/awr327CrossRefPubMedGoogle Scholar
  71. 71.
    Rosskopf J, Gorges M, Muller HP, Lule D, Uttner I, Ludolph AC, Pinkhardt E, Juengling FD, Kassubek J (2017) Intrinsic functional connectivity alterations in progressive supranuclear palsy: differential effects in frontal cortex, motor, and midbrain networks. Mov Disord 32(7):1006–1015.  https://doi.org/10.1002/mds.27039CrossRefPubMedGoogle Scholar
  72. 72.
    Whitwell JL, Avula R, Master A, Vemuri P, Senjem ML, Jones DT, Jack CR Jr, Josephs KA (2011) Disrupted thalamocortical connectivity in PSP: a resting-state fMRI, DTI, and VBM study. Parkinsonism Relat Disord 17(8):599–605.  https://doi.org/10.1016/j.parkreldis.2011.05.013CrossRefPubMedPubMedCentralGoogle Scholar
  73. 73.
    Bharti K, Bologna M, Upadhyay N, Piattella MC, Suppa A, Petsas N, Gianni C, Tona F, Berardelli A, Pantano P (2017) Abnormal resting-state functional connectivity in progressive supranuclear palsy and corticobasal syndrome. Front Neurol 8:248.  https://doi.org/10.3389/fneur.2017.00248CrossRefPubMedPubMedCentralGoogle Scholar
  74. 74.
    Upadhyay N, Suppa A, Piattella MC, Gianni C, Bologna M, Di Stasio F, Petsas N, Tona F, Fabbrini G, Berardelli A, Pantano P (2017) Functional disconnection of thalamic and cerebellar dentate nucleus networks in progressive supranuclear palsy and corticobasal syndrome. Parkinsonism Relat Disord 39:52–57.  https://doi.org/10.1016/j.parkreldis.2017.03.008CrossRefPubMedGoogle Scholar
  75. 75.
    Collins JA, Montal V, Hochberg D, Quimby M, Mandelli ML, Makris N, Seeley WW, Gorno-Tempini ML, Dickerson BC (2017) Focal temporal pole atrophy and network degeneration in semantic variant primary progressive aphasia. Brain 140(2):457–471.  https://doi.org/10.1093/brain/aww313CrossRefPubMedGoogle Scholar
  76. 76.
    Mandelli ML, Vilaplana E, Brown JA, Hubbard HI, Binney RJ, Attygalle S, Santos-Santos MA, Miller ZA, Pakvasa M, Henry ML, Rosen HJ, Henry RG, Rabinovici GD, Miller BL, Seeley WW, Gorno-Tempini ML (2016) Healthy brain connectivity predicts atrophy progression in non-fluent variant of primary progressive aphasia. Brain 139(Pt 10):2778–2791.  https://doi.org/10.1093/brain/aww195CrossRefPubMedPubMedCentralGoogle Scholar
  77. 77.
    Bonakdarpour B, Rogalski EJ, Wang A, Sridhar J, Mesulam MM, Hurley RS (2017) Functional connectivity is reduced in early-stage primary progressive Aphasia when atrophy is not prominent. Alzheimer Dis Assoc Disord 31(2):101–106.  https://doi.org/10.1097/wad.0000000000000193CrossRefPubMedPubMedCentralGoogle Scholar
  78. 78.
    Chen Y, Chen K, Ding J, Zhang Y, Yang Q, Lv Y, Guo Q, Han Z (2017) Brain network for the core deficits of Semantic Dementia: a neural network connectivity-behavior mapping study. Front Hum Neurosci 11:267.  https://doi.org/10.3389/fnhum.2017.00267CrossRefPubMedPubMedCentralGoogle Scholar
  79. 79.
    Sonty SP, Mesulam MM, Weintraub S, Johnson NA, Parrish TB, Gitelman DR (2007) Altered effective connectivity within the language network in primary progressive aphasia. J Neurosci 27(6):1334–1345.  https://doi.org/10.1523/jneurosci.4127-06.2007CrossRefPubMedGoogle Scholar
  80. 80.
    Botha H, Jones DT, Whitwell JL, Duffy JR, Strand EA, Machulda MM, Knopman DS, Petersen R, Jack CR, Josephs KA (2016) Language network dysfunction in primary progressive apraxia of speech. Paper presented at the fifth biennial conference on resting state brain connectivity, Vienna, Austria,Google Scholar
  81. 81.
    Zhou J, Greicius MD, Gennatas ED, Growdon ME, Jang JY, Rabinovici GD, Kramer JH, Weiner M, Miller BL, Seeley WW (2010) Divergent network connectivity changes in behavioural variant frontotemporal dementia and Alzheimer’s disease. Brain 133(Pt 5):1352–1367.  https://doi.org/10.1093/brain/awq075CrossRefPubMedPubMedCentralGoogle Scholar
  82. 82.
    Whitwell JL, Josephs KA, Avula R, Tosakulwong N, Weigand SD, Senjem ML, Vemuri P, Jones DT, Gunter JL, Baker M, Wszolek ZK, Knopman DS, Rademakers R, Petersen RC, Boeve BF, Jack CR Jr (2011) Altered functional connectivity in asymptomatic MAPT subjects: a comparison to bvFTD. Neurology 77(9):866–874.  https://doi.org/10.1212/WNL.0b013e31822c61f2CrossRefPubMedPubMedCentralGoogle Scholar
  83. 83.
    Seeley WW, Menon V, Schatzberg AF, Keller J, Glover GH, Kenna H, Reiss AL, Greicius MD (2007) Dissociable intrinsic connectivity networks for salience processing and executive control. J Neurosci 27(9):2349–2356.  https://doi.org/10.1523/jneurosci.5587-06.2007CrossRefPubMedPubMedCentralGoogle Scholar
  84. 84.
    Day GS, Farb NA, Tang-Wai DF, Masellis M, Black SE, Freedman M, Pollock BG, Chow TW (2013) Salience network resting-state activity: prediction of frontotemporal dementia progression. JAMA Neurol 70(10):1249–1253.  https://doi.org/10.1001/jamaneurol.2013.3258CrossRefPubMedGoogle Scholar
  85. 85.
    Agosta F, Sala S, Valsasina P, Meani A, Canu E, Magnani G, Cappa SF, Scola E, Quatto P, Horsfield MA, Falini A, Comi G, Filippi M (2013) Brain network connectivity assessed using graph theory in frontotemporal dementia. Neurology 81(2):134–143.  https://doi.org/10.1212/WNL.0b013e31829a33f8CrossRefPubMedGoogle Scholar
  86. 86.
    Farb NA, Grady CL, Strother S, Tang-Wai DF, Masellis M, Black S, Freedman M, Pollock BG, Campbell KL, Hasher L, Chow TW (2013) Abnormal network connectivity in frontotemporal dementia: evidence for prefrontal isolation. Cortex 49(7):1856–1873.  https://doi.org/10.1016/j.cortex.2012.09.008CrossRefPubMedGoogle Scholar
  87. 87.
    Ranasinghe KG, Rankin KP, Pressman PS, Perry DC, Lobach IV, Seeley WW, Coppola G, Karydas AM, Grinberg LT, Shany-Ur T, Lee SE, Rabinovici GD, Rosen HJ, Gorno-Tempini ML, Boxer AL, Miller ZA, Chiong W, DeMay M, Kramer JH, Possin KL, Sturm VE, Bettcher BM, Neylan M, Zackey DD, Nguyen LA, Ketelle R, Block N, Wu TQ, Dallich A, Russek N, Caplan A, Geschwind DH, Vossel KA, Miller BL (2016) Distinct subtypes of behavioral variant Frontotemporal Dementia based on patterns of network degeneration. JAMA Neurol 73(9):1078–1088.  https://doi.org/10.1001/jamaneurol.2016.2016CrossRefPubMedPubMedCentralGoogle Scholar
  88. 88.
    Rytty R, Nikkinen J, Paavola L, Abou Elseoud A, Moilanen V, Visuri A, Tervonen O, Renton AE, Traynor BJ, Kiviniemi V, Remes AM (2013) GroupICA dual regression analysis of resting state networks in a behavioral variant of frontotemporal dementia. Front Hum Neurosci 7:461.  https://doi.org/10.3389/fnhum.2013.00461CrossRefPubMedPubMedCentralGoogle Scholar
  89. 89.
    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.2012.09.017CrossRefPubMedGoogle Scholar
  90. 90.
    Dopper EG, Rombouts SA, Jiskoot LC, den Heijer T, de Graaf JR, de Koning I, Hammerschlag AR, Seelaar H, Seeley WW, Veer IM, van Buchem MA, Rizzu P, van Swieten JC (2014) Structural and functional brain connectivity in presymptomatic familial frontotemporal dementia. Neurology 83(2):e19–e26.  https://doi.org/10.1212/wnl.0000000000000583CrossRefPubMedGoogle Scholar
  91. 91.
    Lee SE, Khazenzon AM, Trujillo AJ, Guo CC, Yokoyama JS, Sha SJ, Takada LT, Karydas AM, Block NR, Coppola G, Pribadi M, Geschwind DH, Rademakers R, Fong JC, Weiner MW, Boxer AL, Kramer JH, Rosen HJ, Miller BL, Seeley WW (2014) Altered network connectivity in frontotemporal dementia with C9orf72 hexanucleotide repeat expansion. Brain 137(Pt 11):3047–3060.  https://doi.org/10.1093/brain/awu248CrossRefPubMedPubMedCentralGoogle Scholar
  92. 92.
    Lee SE, Sias AC, Mandelli ML, Brown JA, Brown AB, Khazenzon AM, Vidovszky AA, Zanto TP, Karydas AM, Pribadi M, Dokuru D, Coppola G, Geschwind DH, Rademakers R, Gorno-Tempini ML, Rosen HJ, Miller BL, Seeley WW (2017) Network degeneration and dysfunction in presymptomatic C9ORF72 expansion carriers. Neuroimage Clin 14:286–297.  https://doi.org/10.1016/j.nicl.2016.12.006CrossRefPubMedGoogle Scholar
  93. 93.
    Premi E, Cauda F, Gasparotti R, Diano M, Archetti S, Padovani A, Borroni B (2014) Multimodal FMRI resting-state functional connectivity in granulin mutations: the case of fronto-parietal dementia. PLoS One 9(9):e106500.  https://doi.org/10.1371/journal.pone.0106500CrossRefPubMedPubMedCentralGoogle Scholar
  94. 94.
    Wiepert DA, Lowe VJ, Knopman DS, Boeve BF, Graff-Radford J, Petersen RC, Jack CR Jr, Jones DT (2017) A robust biomarker of large-scale network failure in Alzheimer’s disease. Alzheimers Dement 6:152–161.  https://doi.org/10.1016/j.dadm.2017.01.004CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of NeurologyMayo ClinicRochesterUSA

Personalised recommendations