Linking Molecular Pathways and Large-Scale Computational Modeling to Assess Candidate Disease Mechanisms and Pharmacodynamics in Alzheimer's Disease

Abstract

Introduction While the prevalence of neurodegenerative diseases associated with dementia such as Alzheimer’s disease (AD) increases, our knowledge on the underlying mechanisms, outcome predictors, or therapeutic targets is limited. In this work, we demonstrate how computational multi-scale brain modelling links phenomena of different scales and therefore identifies potential disease mechanisms leading the way to improved diagnostics and treatment. Methods The Virtual Brain (TVB; thevirtualbrain.org ) neuroinformatics platform allows standardized large-scale structural connectivity-based simulations of whole brain dynamics. We provide proof of concept for a novel approach that quantitatively links the effects of altered molecular pathways onto neuronal population dynamics. As a novelty, we connect chemical compounds measured with positron emission tomography (PET) with neural function in TVB addressing the phenomenon of hyperexcitability in AD related to the protein amyloid beta (Abeta). We construct personalized virtual brains based on individual PET derived distributions of Abeta in patients with mild cognitive impairment (MCI, N=8) and Alzheimer’s Disease (AD, N=10) and in age-matched healthy controls (HC, N=15) using data from ADNI-3 data base ( http://adni.lni.usc.edu ). In the personalized virtual brains, individual Abeta burden modulates regional inhibition, leading to disinhibition and hyperexcitation with high Abeta loads. We analyze simulated regional neural activity and electroencephalograms (EEG). Results Known empirical alterations of EEG in patients with AD compared to HCs were reproduced by simulations. The virtual AD group showed slower frequencies in simulated local field potentials and EEG compared to MCI and HC groups. The heterogeneity of the Abeta load is crucial for the virtual EEG slowing which is absent for control models with homogeneous Abeta distributions. Slowing phenomena primarily affect the network hubs, independent of the spatial distribution of Abeta. Modeling the N-methyl-D-aspartate (NMDA) receptor antagonism of memantine in local population models, reveals potential functional reversibility of the observed large-scale alterations (reflected by EEG slowing) in virtual AD brains. Discussion We demonstrate how TVB enables the simulation of systems effects caused by pathogenetic molecular candidate mechanisms in human virtual brains.

References 147

1. 1.
   Infection of Fungi and Bacteria in Brain Tissue From Elderly Persons and Patients With Alzheimer’s Disease · 2018

   No notice
2. 2.

   Alzheimer's Association (2018 ). 2018 Alzheimer's disease facts and figures. Alzheimer's Dement. 14, 367–429.

   Not in our library10.1016/j.jalz.2018.02.001

3. 3.

   Babiloni C. Del Percio C. Caroli A. Salvatore E. Nicolai E. Marzano N.. (2016 ). Cortical sources of resting state EEG rhythms are related to brain hypometabolism in subjects with Alzheimer's disease: an EEG-PET study. Neurobiol. Aging 48, 122–134.

   Not in our library10.1016/j.neurobiolaging.2016.08.021

4. 4.

   Bannai T. Mano T. Chen X. Ohtomo G. Ohtomo R. Tsuchida T.. (2019 ). Chronic cerebral hypoperfusion shifts the equilibrium of amyloid beta oligomers to aggregation-prone species with higher molecular weight. Sci. Rep. 9:2827.

   Not in our library10.1038/s41598-019-39494-7

5. 5.

   Biogen (2019 ). Biogen and EISAI to discontinue phase 3 engage and emerge trials of aducanumab in Alzheimer's disease 2019 [04/01/2019]. Available online at: http://investors.biogen.com/news-releases/news-release-details/biogen-and-eisai-discontinue-phase-3-engage-and-emerge-trials

   Not in our library

6. 6.

   Blennow K. de Leon M. J. Zetterberg H. (2006 ). Alzheimer's disease. Lancet 368, 387–403.

   Not in our library10.1016/s0140-6736(06)69113-7

7. 7.

   Bloom G. S. (2014 ). Amyloid-β and tau: The trigger and bullet in Alzheimer disease pathogenesis. JAMA Neurol. 71, 505–508.

   Not in our library10.1001/jamaneurol.2013.5847

8. 8.

   Bojak I. Oostendorp T. F. Reid A. T. Kotter R. (2010 ). Connecting mean field models of neural activity to EEG and fMRI data. Brain Topogr. 23, 139–149.

   Not in our library10.1007/s10548-010-0140-3

9. 9.

   Braak H. Alafuzoff I. Arzberger T. Kretzschmar H. Del Tredici K. (2006 ). Staging of Alzheimer disease-associated neurofibrillary pathology using paraffin sections and immunocytochemistry. Acta Neuropathol. 112, 389–404.

   Not in our library10.1007/s00401-006-0127-z

10. 10.

    Braak H. Braak E. (1991 ). Neuropathological stageing of Alzheimer-related changes. Acta Neuropathol. 82, 239–259.

    Not in our library10.1007/bf00308809

11. 11.

    Braak H. Braak E. (1997 ). Frequency of stages of Alzheimer-related lesions in different age categories. Neurobiol. Aging 18, 351–357.

    Not in our library10.1016/s0197-4580(97)00056-0

12. 12.

    Breakspear M. (2017 ). Dynamic models of large-scale brain activity. Nat. Neurosci. 20, 340–352.

    Not in our library10.1038/nn.4497

13. 13.

    Busche M. A. Chen X. Henning H. A. Reichwald J. Staufenbiel M. Sakmann B.. (2012 ). Critical role of soluble amyloid-beta for early hippocampal hyperactivity in a mouse model of Alzheimer's disease. Proc. Natl. Acad. Sci. U.S.A. 109, 8740–8745.

    Not in our library10.1073/pnas.1206171109

14. 14.

    Busche M. A. Eichhoff G. Adelsberger H. Abramowski D. Wiederhold K. H. Haass C.. (2008 ). Clusters of hyperactive neurons near amyloid plaques in a mouse model of Alzheimer's disease. Science 321, 1686–1689.

    Not in our library10.1126/science.1162844

15. 15.

    Cabral J. Kringelbach M. L. Deco G. (2017 ). Functional connectivity dynamically evolves on multiple time-scales over a static structural connectome: models and mechanisms. Neuroimage 160, 84–96.

    Not in our library10.1016/j.neuroimage.2017.03.045

16. 16.

    Celebi O. Uzdogan A. Oguz K. K. Has A. C. Dolgun A. Cakmakli G. Y.. (2016 ). Default mode network connectivity is linked to cognitive functioning and CSF Abeta1-42 levels in Alzheimer's disease. Arch. Gerontol. Geriatr. 62, 125–132.

    Not in our library10.1016/j.archger.2015.09.010

17. 17.

    Chen C. (2005 ). beta-Amyloid increases dendritic Ca2+ influx by inhibiting the A-type K+ current in hippocampal CA1 pyramidal neurons. Biochem. Biophys. Res. Commun. 338, 1913–1919.

    Not in our library10.1016/j.bbrc.2005.10.169

18. 18.
    Treatment effects between monotherapy of donepezil versus combination with memantine for Alzheimer disease: A meta-analysis. · 2017

    Not checked
19. 19.

    Chiao P. Bedell B. J. Avants B. Zijdenbos A. P. Grand'Maison M. O'Neill P.. (2019 ). Impact of reference and target region selection on amyloid PET SUV ratios in the phase 1b PRIME study of Aducanumab. J. Nucl. Med. 60, 100–106.

    Not in our library10.2967/jnumed.118.209130

20. 20.

    Clark C. M. Schneider J. A. Bedell B. J. Beach T. G. Bilker W. B. Mintun M. A.. (2011 ). Use of florbetapir-pet for imaging β-amyloid pathology. JAMA. 305, 275–283.

    Not in our library10.1001/jama.2010.2008

21. 21.

    David O. Friston K. J. (2003 ). A neural mass model for MEG/EEG:: coupling and neuronal dynamics. NeuroImage 20, 1743–1755.

    Not in our library10.1016/j.neuroimage.2003.07.015

22. 22.

    David O. Kiebel S. J. Harrison L. M. Mattout J. Kilner J. M. Friston K. J. (2006 ). Dynamic causal modeling of evoked responses in EEG and MEG. NeuroImage 30, 1255–1272.

    Not in our library10.1016/j.neuroimage.2005.10.045

23. 23.
    The Dynamic Brain: From Spiking Neurons to Neural Masses and Cortical Fields · 2008

    No notice
24. 24.
    The dynamics of resting fluctuations in the brain: metastability and its dynamical cortical core · 2017

    No notice
25. 25.

    Dierks T. Jelic V. Pascual-Marqui R. D. Wahlund L. Julin P. Linden D. E.. (2000 ). Spatial pattern of cerebral glucose metabolism (PET) correlates with localization of intracerebral EEG-generators in Alzheimer's disease. Clin. Neurophysiol. 111, 1817–1824.

    Not in our library10.1016/s1388-2457(00)00427-2

26. 26.

    Doggrell S. A. (2018 ). Grasping at straws: the failure of solanezumab to modify mild Alzheimer's disease. Expert Opin. Biol. Ther. 18, 1189–1192.

    Not in our library10.1080/14712598.2018.1543397

27. 27.

    Falcon M. I. Riley J. D. Jirsa V. McIntosh A. R. Elinor Chen E. Solodkin A. (2016 ). Functional mechanisms of recovery after chronic stroke: modeling with the virtual brain. eNeuro 3:ENEURO.0158-15.2016.

    Not in our library10.1523/eneuro.0158-15.2016

28. 28.

    Falcon M. I. Riley J. D. Jirsa V. McIntosh A. R. Shereen A. D. Chen E. E.. (2015 ). The virtual brain: modeling biological correlates of recovery after chronic stroke. Front. Neurol. 6:228.

    Not in our library10.3389/fneur.2015.00228

29. 29.

    Freeman W. J. (ed). (1975 ). Mass Action in the Nervous System. San Diego, CA: Academic Press.

    Not in our library

30. 30.

    Fruchterman T. M. J. Reingold E. M. (1991 ). Graph drawing by force-directed placement. Softw. Pract. Exper. 21, 1129–1164.

    Not in our library10.1002/spe.4380211102

31. 31.

    Furukawa K. Barger S. W. Blalock E. M. Mattson M. P. (1996 ). Activation of K+ channels and suppression of neuronal activity by secreted beta-amyloid-precursor protein. Nature 379, 74–78.

    Not in our library10.1038/379074a0

32. 32.
    Impact of the biological definition of Alzheimer’s disease using amyloid, tau and neurodegeneration (ATN): what about the role of vascular changes, inflammation, Lewy body pathology? · 2018

    Not checked
33. 33.
    Noise during Rest Enables the Exploration of the Brain's Dynamic Repertoire · 2008

    No notice
34. 34.

    Glasser M. F. Coalson T. S. Robinson E. C. Hacker C. D. Harwell J. Yacoub E.. (2016 ). A multi-modal parcellation of human cerebral cortex. Nature 536, 171–178.

    Not in our library10.1038/nature18933

35. 35.

    Glasser M. F. Sotiropoulos S. N. Wilson J. A. Coalson T. S. Fischl B. Andersson J. L.. (2013 ). The minimal preprocessing pipelines for the human connectome project. Neuroimage 80, 105–124.

    Not in our library10.1016/j.neuroimage.2013.04.127

36. 36.

    Good T. A. Smith D. O. Murphy R. M. (1996 ). Beta-amyloid peptide blocks the fast-inactivating K+ current in rat hippocampal neurons. Biophys. J. 70, 296–304.

    Not in our library10.1016/s0006-3495(96)79570-x

37. 37.

    Grienberger C. Rochefort N. L. Adelsberger H. Henning H. A. Hill D. N. Reichwald J. (2012 ). Staged decline of neuronal function in vivo in an animal model of Alzheimers disease. Nat. Commun. 3:774

    Not in our library10.1038/ncomms1783

38. 38.
    Roles of tau protein in health and disease · 2017

    No notice
39. 39.

    Hardy J. Selkoe D. J. (2002 ). The amyloid hypothesis of Alzheimer's disease: progress and problems on the road to therapeutics. Science 297, 353–356.

    Not in our library10.1126/science.1072994

40. 40.

    Hazra A. Gu F. Aulakh A. Berridge C. Eriksen J. L. Ziburkus J. (2013 ). Inhibitory neuron and hippocampal circuit dysfunction in an aged mouse model of Alzheimer's disease. PLoS ONE 8:e64318.

    Not in our library10.1371/journal.pone.0064318

41. 41.

    Heneka M. T. Carson M. J. Khoury J. E. Landreth G. E. Brosseron F. Feinstein D. L.. (2015a ). Neuroinflammation in Alzheimer's disease. Lancet Neurol. 14, 388–405.

    Not in our library10.1016/s1474-4422(15)70016-5

42. 42.

    Heneka M. T. Golenbock D. T. Latz E. (2015b ). Innate immunity in Alzheimer's disease. Nat. Immunol. 16:229.

    Not in our library10.1038/ni.3102

43. 43.

    Hindmarsh J. Rose R. (1984 ). A model of neuronal bursting using three coupled first order differential equations. Proc. R. Soc. London B Biol. Sci. 221, 87–102.

    Not in our library10.1098/rspb.1984.0024

44. 44.

    Honey C. J. Kotter R. Breakspear M. Sporns O. (2007 ). Network structure of cerebral cortex shapes functional connectivity on multiple time scales. Proc. Natl. Acad. Sci. U.S.A. 104, 10240–10245.

    Not in our library10.1073/pnas.0701519104

45. 45.

    Honig L. S. Vellas B. Woodward M. Boada M. Bullock R. Borrie M.. (2018 ). Trial of solanezumab for mild dementia due to Alzheimer's disease. N. Engl. J. Med. 378, 321–330.

    Not in our library10.1056/nejmoa1705971

46. 46.

    Hudry E. Klickstein J. Cannavo C. Jackson R. Muzikansky A. Gandhi S.. (2019 ). Opposing roles of apolipoprotein E in aging and neurodegeneration. Life Sci. Alliance 2:e201900325.

    Not in our library10.26508/lsa.201900325

47. 47.

    Jack C. R. Wiste H. J. Weigand S. D. Rocca W. A. Knopman D. S. Mielke M. M. (2014 ). Age-specific population frequencies of amyloidosis and neurodegeneration among cognitively normal people age 50-89 years: a cross-sectional study. Lancet Neurol. 13, 997–1005.

    Not in our library10.1016/s1474-4422(14)70194-2

48. 48.

    Jack C. R. Jr. Bennett D. A. Blennow K. Carrillo M. C. Dunn B. Haeberlein S. B.. (2018 ). NIA-AA Research Framework: Toward a biological definition of Alzheimer's disease. Alzheimer's Dement. J. Alzheimer's Assoc. 14, 535–562.

    Not in our library10.1016/j.jalz.2018.02.018

49. 49.

    Jack C. R. Jr. Lowe V. J. Weigand S. D. Wiste H. J. Senjem M. L. Knopman D. S.. (2009 ). Serial PIB and MRI in normal, mild cognitive impairment and Alzheimer's disease: implications for sequence of pathological events in Alzheimer's disease. Brain 132(Pt 5), 1355–1365.

    Not in our library10.1093/brain/awp062

50. 50.

    Jansen B. H. Rit V. G. (1995 ). Electroencephalogram and visual evoked potential generation in a mathematical model of coupled cortical columns. Biol. Cybern. 73, 357–366.

    Not in our library10.1007/bf00199471

51. 51.

    Jansen I. E. Savage J. E. Watanabe K. Bryois J. Williams D. M. Steinberg S.. (2019 ). Genome-wide meta-analysis identifies new loci and functional pathways influencing Alzheimer's disease risk. Nat. Genet. 51, 404–413.

    Not in our library10.1038/s41588-018-0311-9

52. 52.

    Jenkinson M. Beckmann C. F. Behrens T. E. Woolrich M. W. Smith S. M. (2012 ). FSL. Neuroimage 62, 782–790.

    Not in our library10.1016/j.neuroimage.2011.09.015

53. 53.

    Jirsa V. K. (2009 ). Neural field dynamics with local and global connectivity and time delay. Philos. Trans. A Math. Phys. Eng. Sci. 367, 1131–1143.

    Not in our library10.1098/rsta.2008.0260

54. 54.

    Jirsa V. K. Jantzen K. J. Fuchs A. Kelso J. A. S. (2002 ). Spatiotemporal forward solution of the EEG and MEG using network modeling. IEEE Trans. Med. Imag. 21, 493–504.

    Not in our library10.1109/tmi.2002.1009385

55. 55.

    Jirsa V. K. Kelso J. A. S. (2000 ). Spatiotemporal pattern formation in neural systems with heterogeneous connection topologies. Phys. Rev. E 62, 8462–8465.

    Not in our library10.1103/physreve.62.8462

56. 56.

    Jirsa V. K. Proix T. Perdikis D. Woodman M. M. Wang H. Gonzalez-Martinez J.. (2017 ). The virtual epileptic patient: individualized whole-brain models of epilepsy spread. Neuroimage 145(Pt B), 377–388.

    Not in our library10.1016/j.neuroimage.2016.04.049

57. 57.

    Jirsa V. K. Sporns O. Breakspear M. Deco G. McIntosh A. R. (2010 ). Towards the virtual brain: network modeling of the intact and the damaged brain. Arch. Ital. Biol. 148, 189–205.

    Not in our library10.4449/aib.v148i3.1223

58. 58.

    Jones E. Oliphant E. Peterson P. (2001 ). SciPy: Open Source Scientific Tools for Python. Available online at: http://www.scipy.org/ (accessed July 30, 2019).

    Not in our library

59. 59.

    Kirschstein T. Köhling R. (2009 ). What is the source of the EEG? Clin. EEG Neurosci. 40, 146–149.

    Not in our library10.1177/155005940904000305

60. 60.

    Kishi T. Matsunaga S. Oya K. Nomura I. Ikuta T. Iwata N. (2017 ). Memantine for Alzheimer's disease: an updated systematic review and meta-analysis. J. Alzheimers Dis. 60, 401–425.

    Not in our library10.3233/jad-170424

61. 61.

    Klunk W. E. Price J. C. Mathis C. A. Tsopelas N. D. Lopresti B. J. Ziolko S. K.. (2007 ). Amyloid deposition begins in the striatum of presenilin-1 mutation carriers from two unrelated pedigrees. J. Neurosci. 27, 6174–6184.

    Not in our library10.1523/jneurosci.0730-07.2007

62. 62.

    Kringelbach M. L. McIntosh A. R. Ritter P. Jirsa V. K. Deco G. (2015 ). The rediscovery of slowness: exploring the timing of cognition. Trends Cogn. Sci. 19, 616–628.

    Not in our library10.1016/j.tics.2015.07.011

63. 63.

    Kunze T. Hunold A. Haueisen J. Jirsa V. Spiegler A. (2016 ). Transcranial direct current stimulation changes resting state functional connectivity: a large-scale brain network modeling study. NeuroImage 140, 174–187.

    Not in our library10.1016/j.neuroimage.2016.02.015

64. 64.

    Limon A. Reyes-Ruiz J. M. Miledi R. (2012 ). Loss of functional GABA(A) receptors in the Alzheimer diseased brain. Proc. Natl. Acad. Sci. U.S.A. 109, 10071–10076.

    Not in our library10.1073/pnas.1204606109

65. 65.
    EEG and MEG Data Analysis in SPM8 · 2011

    No notice
66. 66.

    Loewenstein D. A. Barker W. W. Chang J. Y. Apicella A. Yoshii F. Kothari P.. (1989 ). Predominant left hemisphere metabolic dysfunction in dementia. Arch. Neurol. 46, 146–152.

    Not in our library10.1001/archneur.1989.00520380046012

67. 67.
    Safety and tolerability of BAN2401 - a clinical study in Alzheimer’s disease with a protofibril selective Aβ antibody · 2016

    No notice
68. 68.

    Lopes da Silva F. H. Hoeks A. Smits H. Zetterberg L. H. (1974 ). Model of brain rhythmic activity. The alpha-rhythm of the thalamus. Kybernetik 15, 27–37.

    Not in our library10.1007/bf00270757

69. 69.
    Cerebrovascular disease in ageing and Alzheimer’s disease · 2015

    No notice
70. 70.
    Apolipoprotein E: from cardiovascular disease to neurodegenerative disorders · 2016

    No notice
71. 71.

    Malek N. Baker M. R. Mann C. Greene J. (2017 ). Electroencephalographic markers in dementia. Acta Neurol. Scand. 135, 388–393.

    Not in our library10.1111/ane.12638

72. 72.

    Martinez G. Vernooij R. W. Fuentes Padilla P. Zamora J. Bonfill Cosp X. Flicker L. (2017 ). 18F PET with florbetapir for the early diagnosis of Alzheimer's disease dementia and other dementias in people with mild cognitive impairment (MCI). Cochr. Database Syst. Rev. 11:Cd012216.

    Not in our library10.1002/14651858.cd012216.pub2

73. 73.

    McKhann G. Drachman D. Folstein M. Katzman R. Price D. Stadlan E. M. (1984 ). Clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA work group under the auspices of department of health and human services task force on Alzheimer's disease. Neurology 34, 939–944.

    Not in our library10.1212/wnl.34.7.939

74. 74.

    McLachlan D. R. C. Bergeron C. Alexandrov P. N. Walsh W. J. Pogue A. I. Percy M. E.. (2019 ). Aluminum in neurological and neurodegenerative disease. Mol. Neurobiol. 56, 1531–1538.

    Not in our library10.1007/s12035-018-1441-x

75. 75.

    Merlet I. Birot G. Salvador R. Molaee-Ardekani B. Mekonnen A. Soria-Frish A.. (2013 ). From oscillatory transcranial current stimulation to scalp EEG changes: a biophysical and physiological modeling study. PLoS ONE 8:e57330.

    Not in our library10.1371/journal.pone.0057330

76. 76.

    Meyer M. A. Caccia A. Martinez D. Mingos M. A. (2018 ). PET imaging of 18F-florbetapir in cognitively impaired individuals: lack of activity within the cerebellar cortex. Neurol Int. 10:7666.

    Not in our library10.4081/ni.2018.7666

77. 77.
    Diagnostic accuracy of 18F amyloid PET tracers for the diagnosis of Alzheimer’s disease: a systematic review and meta-analysis · 2015

    No notice
78. 78.

    Moses W. W. (2011 ). Fundamental limits of spatial resolution in PET. Nucl. Instrum. Methods Phys. Res. A. 648(Suppl. 1), S236–S240.

    Not in our library10.1016/j.nima.2010.11.092

79. 79.

    Murray M. E. Lowe V. J. Graff-Radford N. R. Liesinger A. M. Cannon A. Przybelski S. A. (2015 ). Clinicopathologic and (11)C-Pittsburgh compound B implications of Thal amyloid phase across the Alzheimer's disease spectrum. Brain 138, 1370–1381.

    Not in our library10.1093/brain/awv050

80. 80.

    Nakamura A. Cuesta P. Fernandez A. Arahata Y. Iwata K. Kuratsubo I.. (2018 ). Electromagnetic signatures of the preclinical and prodromal stages of Alzheimer's disease. Brain 141, 1470–1485.

    Not in our library10.1093/brain/awy044

81. 81.

    Ossenkoppele R. Jansen W. J. Rabinovici G. D. Knol D. L. van der Flier W. M. van Berckel B. N.. (2015 ). Prevalence of amyloid PET positivity in dementia syndromes: a meta-analysis. JAMA 313, 1939–1949.

    Not in our library10.1001/jama.2015.4669

82. 82.

    Osswald G. (2018 ). BioArctic Announces Positive Topline Results of BAN2401 Phase 2b at 18 Months in Early Alzheimer's Disease. BioArctic Press Release.

    Not in our library

83. 83.

    Panza F. Lozupone M. Dibello V. Greco A. Daniele A. Seripa D.. (2019 ). Are antibodies directed against amyloid-beta (Abeta) oligomers the last call for the Abeta hypothesis of Alzheimer's disease? Immunotherapy 11, 3–6.

    Not in our library10.2217/imt-2018-0119

84. 84.

    Petkoski S. Palva J. M. Jirsa V. K. (2018 ). Phase-lags in large scale brain synchronization: methodological considerations and in-silico analysis. PLOS Comput. Biol. 14:e1006160.

    Not in our library10.1371/journal.pcbi.1006160

85. 85.

    Petkoski S. Spiegler A. Proix T. Aram P. Temprado J.-J. Jirsa V. K. (2016 ). Heterogeneity of time delays determines synchronization of coupled oscillators. Phys. Rev. 94:012209.

    Not in our library10.1103/physreve.94.012209

86. 86.

    Pink J. O'Brien J. Robinson L. Longson D. (2018 ). Dementia: assessment, management and support: summary of updated NICE guidance. BMJ. 361:k2438.

    Not in our library10.1136/bmj.k2438

87. 87.

    Prasansuklab A. Tencomnao T. (2013 ). Amyloidosis in Alzheimer's disease: the toxicity of Amyloid Beta (Aβ), mechanisms of its accumulation and implications of medicinal plants for therapy. Evid. Based Complement. Alternat. Med. 2013:413808

    Not in our library10.1155/2013/413808

88. 88.

    Proix T. Bartolomei F. Guye M. Jirsa V. K. (2017 ). Individual brain structure and modelling predict seizure propagation. Brain 140, 641–654.

    Not in our library10.1093/brain/awx004

89. 89.

    Ren S.-Q. Yao W. Yan J.-Z. Jin C. Yin J.-J. Yuan J.. (2018 ). Amyloid β causes excitation/inhibition imbalance through dopamine receptor 1-dependent disruption of fast-spiking GABAergic input in anterior cingulate cortex. Sci. Rep. 8:302.

    Not in our library10.1038/s41598-017-18729-5

90. 90.

    Reuter M. Schmansky N. J. Rosas H. D. Fischl B. (2012 ). Within-subject template estimation for unbiased longitudinal image analysis. Neuroimage 61, 1402–1418.

    Not in our library10.1016/j.neuroimage.2012.02.084

91. 91.

    Rice D. M. Buchsbaum M. S. Starr A. Auslander L. Hagman J. Evans W. J. (1990 ). Abnormal EEG slow activity in left temporal areas in senile dementia of the Alzheimer type. J. Gerontol. 45, M145–M151.

    Not in our library10.1093/geronj/45.4.m145

92. 92.

    Ripoli C. Cocco S. Li Puma D. D. Piacentini R. Mastrodonato A. Scala F.. (2014 ). Intracellular accumulation of amyloid-β (Aβ) protein plays a major role in Aβ-induced alterations of glutamatergic synaptic transmission and plasticity. J. Neurosci. 34, 12893–12903.

    Not in our library10.1523/jneurosci.1201-14.2014

93. 93.

    Ritter P. Schirner M. McIntosh A. R. Jirsa V. K. (2013 ). The virtual brain integrates computational modeling and multimodal neuroimaging. Brain Connect. 3, 121–145.

    Not in our library10.1089/brain.2012.0120

94. 94.

    Robinson E. C. Jbabdi S. Glasser M. F. Andersson J. Burgess G. C. Harms M. P.. (2014 ). MSM: a new flexible framework for multimodal surface matching. Neuroimage 100, 414–426.

    Not in our library10.1016/j.neuroimage.2014.05.069

95. 95.

    Robinson J. L. Corrada M. M. Kovacs G. G. Dominique M. Caswell C. Xie S. X.. (2018a ). Non-Alzheimer's contributions to dementia and cognitive resilience in The 90+ Study. Acta Neuropathol. 136, 377–388.

    Not in our library10.1007/s00401-018-1872-5

96. 96.

    Robinson J. L. Lee E. B. Xie S. X. Rennert L. Suh E. Bredenberg C.. (2018b ). Neurodegenerative disease concomitant proteinopathies are prevalent, age-related and APOE4-associated. Brain 141, 2181–2193.

    Not in our library10.1093/brain/awy146

97. 97.

    Roche (2019 ). Roche to Discontinue Phase III CREAD 1 and 2 Clinical Studies of Crenezumab in Early Alzheimer's Disease (AD)-Other Company Programmes in AD Continue 2019 [updated 04/01/2019]. Available online at: https://www.roche.com/dam/jcr:e3181d56-8cac-4db8-a7d4-2f883ee2847c/en/20190130-MR_CREN_EN.pdf

    Not in our library

98. 98.

    Sadigh-Eteghad S. Sabermarouf B. Majdi A. Talebi M. Farhoudi M. Mahmoudi J. (2015 ). Amyloid-beta: a crucial factor in Alzheimer's disease. Med. Principles Pract. 24, 1–10.

    Not in our library10.1159/000369101

99. 99.
    Amyloid positron emission tomography and cerebrospinal fluid results from a crenezumab anti-amyloid-beta antibody double-blind, placebo-controlled, randomized phase II study in mild-to-moderate Alzheimer’s disease (BLAZE) · 2018

    No notice
100. 100.
     The Virtual Brain: a simulator of primate brain network dynamics · 2013

     No notice
101. 101.

     Sanz-Leon P. Knock S. A. Spiegler A. Jirsa V. K. (2015 ). Mathematical framework for large-scale brain network modeling in The Virtual Brain. Neuroimage 111, 385–430.

     Not in our library10.1016/j.neuroimage.2015.01.002

102. 102.

     Schirner M. Rothmeier S. Jirsa V. K. McIntosh A. R. Ritter P. (2015 ). An automated pipeline for constructing personalized virtual brains from multimodal neuroimaging data. Neuroimage 117, 343–357.

     Not in our library10.1016/j.neuroimage.2015.03.055

103. 103.

     Schmolesky M. (2005 ). The primary visual cortex, in Webvision: The Organization of the Retina and Visual System [Internet], eds Kolb H. Fernandez E. Nelson R. (Salt Lake City, UT: University of Utah Health Sciences Center).

     Not in our library

104. 104.

     Schöll M. Lockhart Samuel N. Schonhaut Daniel R. O'Neil James P. Janabi M. Ossenkoppele R.. (2016 ). PET imaging of Tau deposition in the aging human brain. Neuron 89, 971–982.

     Not in our library10.1016/j.neuron.2016.01.028

105. 105.

     Schüz A. Braitenberg V. (ed) (2002 ). The human cortical white matter: quantitative aspects of cortico-cortical long- range connectivity, in Cortical Areas: Unity and Diversity (London; New York, NY: Taylor & Davis), 377f.

     Not in our library10.4324/9780203219911_chapter_16

106. 106.
     The amyloid hypothesis of Alzheimer's disease at 25 years · 2016

     No notice
107. 107.

     Smith R. E. Tournier J.-D. Calamante F. Connelly A. (2012 ). Anatomically-constrained tractography: improved diffusion MRI streamlines tractography through effective use of anatomical information. NeuroImage 62, 1924–1938.

     Not in our library10.1016/j.neuroimage.2012.06.005

108. 108.

     Smith R. E. Tournier J. D. Calamante F. Connelly A. (2015 ). SIFT2: enabling dense quantitative assessment of brain white matter connectivity using streamlines tractography. Neuroimage 119, 338–351.

     Not in our library10.1016/j.neuroimage.2015.06.092

109. 109.

     Smith S. M. Jenkinson M. Woolrich M. W. Beckmann C. F. Behrens T. E. Johansen-Berg H.. (2004 ). Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage 23(Suppl. 1), S208–S219.

     Not in our library10.1016/j.neuroimage.2004.07.051

110. 110.

     Song Z. Insel P. S. Buckley S. Yohannes S. Mezher A. Simonson A.. (2015 ). Brain amyloid-beta burden is associated with disruption of intrinsic functional connectivity within the medial temporal lobe in cognitively normal elderly. J. Neurosci. 35, 3240–3247.

     Not in our library10.1523/jneurosci.2092-14.2015

111. 111.

     Sotero R. C. Trujillo-Barreto N. J. (2008 ). Biophysical model for integrating neuronal activity, EEG, fMRI and metabolism. NeuroImage 39, 290–309.

     Not in our library10.1016/j.neuroimage.2007.08.001

112. 112.

     Sotero R. C. Trujillo-Barreto N. J. Iturria-Medina Y. Carbonell F. Jimenez J. C. (2007 ). Realistically coupled neural mass models can generate EEG rhythms. Neural. Comput. 19, 478–512.

     Not in our library10.1162/neco.2007.19.2.478

113. 113.

     Spiegler A. (2011 ). Dynamics of Biologically Informed Neural Mass Models of the Brain. Ilmenau: Universitätsverlag Ilmenau.

     Not in our library

114. 114.

     Spiegler A. Jirsa V. (2013 ). Systematic approximations of neural fields through networks of neural masses in the virtual brain. NeuroImage 83, 704–725.

     Not in our library10.1016/j.neuroimage.2013.06.018

115. 115.

     Spiegler A. Kiebel S. J. Atay F. M. Knösche T. R. (2010 ). Bifurcation analysis of neural mass models: impact of extrinsic inputs and dendritic time constants. NeuroImage 52, 1041–1058.

     Not in our library10.1016/j.neuroimage.2009.12.081

116. 116.

     Spiegler A. Knösche T. R. Schwab K. Haueisen J. Atay F. M. (2011 ). Modeling brain resonance phenomena using a neural mass model. PLOS Comput. Biol. 7:e1002298.

     Not in our library10.1371/journal.pcbi.1002298

117. 117.
     A low dimensional description of globally coupled heterogeneous neural networks of excitatory and inhibitory neurons. · 2008

     Not checked
118. 118.

     Stefanovski L. Ghani A. McIntosh A. R. Ritter P. (2016 ). Linking connectomics and dynamics in the human brain. e-Neuroforum 7, 64–70.

     Not in our library10.1007/s13295-016-0027-1

119. 119.

     Storck S. E. Pietrzik Claus U. (2018 ). The Blood brain-barrier and its role in Alzheimer's disease. Neuroforum 24:A197

     Not in our library10.1515/nf-2018-a014

120. 120.

     Strogatz S. H. (2015 ). Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering: Second Edition. Boulder, CO: Westview Press, a member of the Perseus Books Group.

     Not in our library

121. 121.
     Brainstorm: A User-Friendly Application for MEG/EEG Analysis · 2011

     No notice
122. 122.

     Takatori S. Wang W. Iguchi A. Tomita T. (2019 ). Genetic risk factors for alzheimer disease: emerging roles of microglia in disease pathomechanisms. Adv. Exp. Med. Biol. 1118, 83–116.

     Not in our library10.1007/978-3-030-05542-4_5

123. 123.

     Tapia-Rojas C. Cabezas-Opazo F. Deaton C. A. Vergara E. H. Johnson G. V. W. Quintanilla R. A. (2019 ). It's all about tau. Prog. Neurobiol. 175, 54–76.

     Not in our library10.1016/j.pneurobio.2018.12.005

124. 124.

     Thal D. R. Rub U. Orantes M. Braak H. (2002 ). Phases of a beta-deposition in the human brain and its relevance for the development of AD. Neurology 58, 1791–1800.

     Not in our library10.1212/wnl.58.12.1791

125. 125.

     Thomas B. A. Cuplov V. Bousse A. Mendes A. Thielemans K. Hutton B. F.. (2016 ). PETPVC: a toolbox for performing partial volume correction techniques in positron emission tomography. Phys. Med. Biol. 61, 7975–7993.

     Not in our library10.1088/0031-9155/61/22/7975

126. 126.

     Tournier J. D. Calamante F. Connelly A. (2007 ). Robust determination of the fibre orientation distribution in diffusion MRI: non-negativity constrained super-resolved spherical deconvolution. Neuroimage 35, 1459–1472.

     Not in our library10.1016/j.neuroimage.2007.02.016

127. 127.

     Tournier J. D. Calamante F. Connelly A. (2010 ). Improved probabilistic streamlines tractography by 2nd order integration over fibre orientation distributions. Proc. Intl. Soc. Mag. Reson. Med. 18:1670.

     Not in our library

128. 128.

     Tournier J. D. Calamante F. Connelly A. (2013 ). Determination of the appropriate b value and number of gradient directions for high-angular-resolution diffusion-weighted imaging. NMR Biomed. 26, 1775–1786.

     Not in our library10.1002/nbm.3017

129. 129.

     Ulrich D. (2015 ). Amyloid-beta impairs synaptic inhibition via GABA(A) receptor endocytosis. J. Neurosci. 35, 9205–9210.

     Not in our library10.1523/jneurosci.0950-15.2015

130. 130.

     Veraart J. Novikov D. S. Christiaens D. Ades-aron B. Sijbers J. Fieremans E. (2016 ). Denoising of diffusion MRI using random matrix theory. NeuroImage 142, 394–406.

     Not in our library10.1016/j.neuroimage.2016.08.016

131. 131.

     Verret L. Mann Edward O. Hang Giao B. Barth Albert M. I. Cobos I. Ho K.. (2012 ). Inhibitory interneuron deficit links altered network activity and cognitive dysfunction in Alzheimer model. Cell 149, 708–721.

     Not in our library10.1016/j.cell.2012.02.046

132. 132.

     Villemagne V. L. Ataka S. Mizuno T. Brooks W. S. Wada Y. Kondo M.. (2009 ). High striatal amyloid beta-peptide deposition across different autosomal Alzheimer disease mutation types. Arch. Neurol. 66, 1537–1544.

     Not in our library10.1001/archneurol.2009.285

133. 133.

     Walsh D. M. Selkoe D. J. (2007 ). A beta oligomers - a decade of discovery. J. Neurochem. 101, 1172–1184.

     Not in our library10.1111/j.1471-4159.2006.04426.x

134. 134.

     Wang S. Colonna M. (2019 ). Microglia in Alzheimer's disease: a target for immunotherapy. J. Leukoc. Biol. 106, 219–227.

     Not in our library10.1002/jlb.mr0818-319r

135. 135.

     Wendling F. Bartolomei F. Bellanger J. J. Chauvel P. (2002 ). Epileptic fast activity can be explained by a model of impaired GABAergic dendritic inhibition. Eur. J. Neurosci. 15, 1499–1508.

     Not in our library10.1046/j.1460-9568.2002.01985.x

136. 136.

     Wendling F. Bellanger J. J. Bartolomei F. Chauvel P. (2000 ). Relevance of nonlinear lumped-parameter models in the analysis of depth-EEG epileptic signals. Biol. Cybernet. 83, 367–378.

     Not in our library10.1007/s004220000160

137. 137.

     WHO (2011 ). Global Health and Ageing. Aging UNIo, WHO.

     Not in our library

138. 138.

     Wilson H. R. Cowan J. D. (1972 ). Excitatory and inhibitory interactions in localized populations of model neurons. Biophys. J. 12, 1–24.

     Not in our library10.1016/s0006-3495(72)86068-5

139. 139.
     The worldwide costs of dementia 2015 and comparisons with 2010 · 2016

     No notice
140. 140.

     Wimo A. Jonsson L. Gustavsson A. McDaid D. Ersek K. Georges J.. (2011 ). The economic impact of dementia in Europe in 2008-cost estimates from the Eurocode project. Int. J. Geriatr. Psychiatry 26, 825–832.

     Not in our library10.1002/gps.2610

141. 141.

     Wong K.-F. Wang X.-J. (2006 ). A recurrent network mechanism of time integration in perceptual decisions. J. Neurosci. 26, 1314–1328.

     Not in our library10.1523/jneurosci.3733-05.2006

142. 142.

     Woolrich M. W. Jbabdi S. Patenaude B. Chappell M. Makni S. Behrens T.. (2009 ). Bayesian analysis of neuroimaging data in FSL. Neuroimage 45(1 Suppl.), S173–S186.

     Not in our library10.1016/j.neuroimage.2008.10.055

143. 143.

     Wright J. J. Liley D. T. J. (2010 ). Dynamics of the brain at global and microscopic scales: neural networks and the EEG. Behav. Brain Sci. 19, 285–295.

     Not in our library10.1017/s0140525x00042679

144. 144.
     The economic burden of dementia in China, 1990–2030: implications for health policy · 2016

     No notice
145. 145.

     Zetterberg L. H. Kristiansson L. Mossberg K. (1978 ). Performance of a model for a local neuron population. Biol. Cybernet. 31, 15–26.

     Not in our library10.1007/bf00337367

146. 146.

     Zhou J. Yu W. Zhang M. Tian X. Li Y. Lu Y. (2019 ). Imbalance of microglial TLR4/TREM2 in LPS-treated APP/PS1 transgenic mice: a potential link between Alzheimer's disease and systemic inflammation. Neurochem. Res. 44, 1138–1151.

     Not in our library10.1007/s11064-019-02748-x

147. 147.

     Zimmermann J. Perry A. Breakspear M. Schirner M. Sachdev P. Wen W.. (2018 ). Differentiation of Alzheimer's disease based on local and global parameters in personalized Virtual Brain models. NeuroImage Clin. 19, 240–251.

     Not in our library10.1016/j.nicl.2018.04.017

Cited by papers we hold 3

• Whole-Brain Network Models: From Physics to Bedside · 2022
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• Increased Excursions to Functional Networks in Schizophrenia in the Absence of Task · 2022
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• Quantitative systems pharmacology in neuroscience: Novel methodologies and technologies · 2021
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