CoChat
Sign Up
Cited by 66Dementia and Cognitive Impairment ResearchAlzheimer's disease research and treatmentsFunctional Brain Connectivity Studies

Detecting Early Cognitive Decline in Alzheimer’s Disease with Brain Synaptic Structural and Functional Evaluation

Open access
Ribarič, Samo·2023·Biomedicines
DOI 10.3390/biomedicines11020355PMC PMC9952956
Open this paper in CoChat — free accountOpen PDF

Abstract

Early cognitive decline in patients with Alzheimer’s (AD) is associated with quantifiable structural and functional connectivity changes in the brain. AD dysregulation of Aβ and tau metabolism progressively disrupt normal synaptic function, leading to loss of synapses, decreased hippocampal synaptic density and early hippocampal atrophy. Advances in brain imaging techniques in living patients have enabled the transition from clinical signs and symptoms-based AD diagnosis to biomarkers-based diagnosis, with functional brain imaging techniques, quantitative EEG, and body fluids sampling. The hippocampus has a central role in semantic and episodic memory processing. This cognitive function is critically dependent on normal intrahippocampal connections and normal hippocampal functional connectivity with many cortical regions, including the perirhinal and the entorhinal cortex, parahippocampal cortex, association regions in the temporal and parietal lobes, and prefrontal cortex. Therefore, decreased hippocampal synaptic density is reflected in the altered functional connectivity of intrinsic brain networks (aka large-scale networks), including the parietal memory, default mode, and salience networks. This narrative review discusses recent critical issues related to detecting AD-associated early cognitive decline with brain synaptic structural and functional markers in high-risk or neuropsychologically diagnosed patients with subjective cognitive impairment or mild cognitive impairment.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3390/biomedicines11020355

Cites

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Synapse dysfunction/loss is one of the earliest pathological hallmarks in the brain.

    “synapse dysfunction/loss is (1) one of the earliest pathological hallmarks in the brain”

    From PLCG2 downregulation impairs synaptic function and increases Alzheimer’s disease hallmarks in neuronal cultures (2026) · cites this paper as [15]

    Section 2.2 identifies synaptic loss as an early brain pathological change in Alzheimer’s disease and says reduced synaptic plasticity precedes neuronal death. The source supports the claim for Alzheimer’s disease, but not as an unqualified statement about brain pathology generally. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

  • Synapse dysfunction/loss is the strongest marker of cognitive decline.

    “and (2) the strongest marker of cognitive decline13–15”

    From PLCG2 downregulation impairs synaptic function and increases Alzheimer’s disease hallmarks in neuronal cultures (2026) · cites this paper as [15]

    Section 1.1 (Brain Synapses) links synaptic loss to measured cognitive decline in patients with Alzheimer’s disease, and Section 2.2 calls it an early cause of AD-related cognitive decline. The paper does not establish that synaptic dysfunction or loss is the strongest marker relative to other markers, or extend that ranking beyond AD. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

No citation lists for this paper

No citation lists for this paper yet — checked again daily.

References 308 · Cited by 66

Research works printed but not linked: 282

  1. [2]Alzheimer′s Association 2020 Alzheimer’s disease facts and figures Alzheimers Dement. 2020 16 391 460 10.1002/alz.12068 32157811 · DOI · Paper page
  2. [3]Koike H. Iguchi Y. Sahashi K. Katsuno M. Significance of oligomeric and fibrillar species in amyloidosis: Insights into pathophysiology and treatment Molecules 2021 26 5091 10.3390/molecules26165091 34443678 PMC8401015 · DOI
  3. [5]Garcia-Morales V. Gonzalez-Acedo A. Melguizo-Rodriguez L. Pardo-Moreno T. Costela-Ruiz V.J. Montiel-Troya M. Ramos-Rodriguez J.J. Current understanding of the physiopathology, diagnosis and therapeutic approach to Alzheimer’s disease Biomedicines 2021 9 1910 10.3390/biomedicines9121910 34944723 PMC8698840 · DOI · Paper page
  4. [8]Yu T.W. Lane H.Y. Lin C.H. Novel therapeutic approaches for Alzheimer’s disease: An updated review Int. J. Mol. Sci. 2021 22 8208 10.3390/ijms22158208 34360973 PMC8348485 · DOI
  5. [9]Cummings J.L. Tong G. Ballard C. Treatment combinations for Alzheimer’s disease: Current and future pharmacotherapy options J. Alzheimers Dis. 2019 67 779 794 10.3233/JAD-180766 30689575 PMC6398562 · DOI · Paper page
  6. [10]van Dyck C.H. Swanson C.J. Aisen P. Bateman R.J. Chen C. Gee M. Kanekiyo M. Li D. Reyderman L. Cohen S. Lecanemab in early Alzheimer’s disease N. Engl. J. Med. 2023 388 9 21 10.1056/NEJMoa2212948 36449413 · DOI · Paper page
  7. [11]Serrano M.E. Kim E. Petrinovic M.M. Turkheimer F. Cash D. Imaging synaptic density: The next holy grail of neuroscience? Front. Neurosci. 2022 16 796129 10.3389/fnins.2022.796129 35401097 PMC8990757 · DOI · Paper page
  8. [12]Hawkins J. Ahmad S. Why neurons have thousands of synapses, a theory of sequence memory in neocortex Front. Neural. Circuits 2016 10 23 10.3389/fncir.2016.00023 27065813 PMC4811948 · DOI
  9. [13]Caire M.J. Reddy V. Varacallo M. Physiology, Synapse Statpearls Treasure Island, FL, USA 2022 30252303
  10. [14]Schiapparelli L.M. Sharma P. He H.Y. Li J. Shah S.H. McClatchy D.B. Ma Y. Liu H.H. Goldberg J.L. Yates J.R. 3rd Proteomic screen reveals diverse protein transport between connected neurons in the visual system Cell Rep. 2022 38 110287 10.1016/j.celrep.2021.110287 35081342 PMC8906846 · DOI
  11. [16]Tang Y. Nyengaard J.R. De Groot D.M. Gundersen H.J. Total regional and global number of synapses in the human brain neocortex Synapse 2001 41 258 273 10.1002/syn.1083 11418939 · DOI
  12. [17]Colom-Cadena M. Spires-Jones T. Zetterberg H. Blennow K. Caggiano A. DeKosky S.T. Fillit H. Harrison J.E. Schneider L.S. Scheltens P. The clinical promise of biomarkers of synapse damage or loss in Alzheimer’s disease Alzheimers Res. Ther. 2020 12 21 10.1186/s13195-020-00588-4 32122400 PMC7053087 · DOI · Paper page
  13. [18]John A. Reddy P.H. Synaptic basis of Alzheimer’s disease: Focus on synaptic amyloid β, p-tau and mitochondria Ageing Res. Rev. 2021 65 101208 10.1016/j.arr.2020.101208 33157321 PMC7770124 · DOI · Paper page
  14. [19]Stampanoni Bassi M. Iezzi E. Gilio L. Centonze D. Buttari F. Synaptic plasticity shapes brain connectivity: Implications for network topology Int. J. Mol. Sci. 2019 20 6193 10.3390/ijms20246193 31817968 PMC6940892 · DOI
  15. [21]Oberheim N.A. Takano T. Han X. He W. Lin J.H. Wang F. Xu Q. Wyatt J.D. Pilcher W. Ojemann J.G. Uniquely hominid features of adult human astrocytes J. Neurosci. 2009 29 3276 3287 10.1523/JNEUROSCI.4707-08.2009 19279265 PMC2819812 · DOI · Paper page
  16. [22]Farhy-Tselnicker I. Allen N.J. Astrocytes, neurons, synapses: A tripartite view on cortical circuit development Neural. Dev. 2018 13 7 10.1186/s13064-018-0104-y 29712572 PMC5928581 · DOI
  17. [23]Arizono M. Inavalli V. Panatier A. Pfeiffer T. Angibaud J. Levet F. Ter Veer M.J.T. Stobart J. Bellocchio L. Mikoshiba K. Structural basis of astrocytic ca(2+) signals at tripartite synapses Nat. Commun. 2020 11 1906 10.1038/s41467-020-15648-4 32312988 PMC7170846 · DOI
  18. [26]Jackson N.A. Guerrero-Munoz M.J. Castillo-Carranza D.L. The prion-like transmission of tau oligomers via exosomes Front. Aging Neurosci. 2022 14 974414 10.3389/fnagi.2022.974414 36062141 PMC9434014 · DOI
  19. [27]Martin E.A. Lasseigne A.M. Miller A.C. Understanding the molecular and cell biological mechanisms of electrical synapse formation Front. Neuroanat. 2020 14 12 10.3389/fnana.2020.00012 32372919 PMC7179694 · DOI
  20. [28]Pereda A.E. Faber D.S. Activity-dependent short-term enhancement of intercellular coupling J. Neurosci. 1996 16 983 992 10.1523/JNEUROSCI.16-03-00983.1996 8558267 PMC6578804 · DOI
  21. [29]Yang X.D. Korn H. Faber D.S. Long-term potentiation of electrotonic coupling at mixed synapses Nature 1990 348 542 545 10.1038/348542a0 2174130 · DOI
  22. [30]Kopell N. Ermentrout B. Chemical and electrical synapses perform complementary roles in the synchronization of interneuronal networks Proc. Natl. Acad. Sci. USA 2004 101 15482 15487 10.1073/pnas.0406343101 15489269 PMC524455 · DOI
  23. [31]Alcami P. Pereda A.E. Beyond plasticity: The dynamic impact of electrical synapses on neural circuits Nat. Rev. Neurosci. 2019 20 253 271 10.1038/s41583-019-0133-5 30824857 · DOI
  24. [32]Pereda A.E. Electrical synapses and their functional interactions with chemical synapses Nat. Rev. Neurosci. 2014 15 250 263 10.1038/nrn3708 24619342 PMC4091911 · DOI
  25. [33]Pereda A.E. Curti S. Hoge G. Cachope R. Flores C.E. Rash J.E. Gap junction-mediated electrical transmission: Regulatory mechanisms and plasticity Biochim. Biophys. Acta 2013 1828 134 146 10.1016/j.bbamem.2012.05.026 22659675 PMC3437247 · DOI
  26. [34]Bloomfield S.A. Volgyi B. The diverse functional roles and regulation of neuronal gap junctions in the retina Nat. Rev. Neurosci. 2009 10 495 506 10.1038/nrn2636 19491906 PMC3381350 · DOI
  27. [35]Pham T. Haas J.S. Electrical synapses regulate both subthreshold integration and population activity of principal cells in response to transient inputs within canonical feedforward circuits PLoS Comput. Biol. 2019 15 e1006440 10.1371/journal.pcbi.1006440 30802238 PMC6405166 · DOI
  28. [36]Deans M.R. Gibson J.R. Sellitto C. Connors B.W. Paul D.L. Synchronous activity of inhibitory networks in neocortex requires electrical synapses containing connexin36 Neuron 2001 31 477 485 10.1016/S0896-6273(01)00373-7 11516403 · DOI
  29. [38]Steriade M. Synchronized activities of coupled oscillators in the cerebral cortex and thalamus at different levels of vigilance Cereb. Cortex 1997 7 583 604 10.1093/cercor/7.6.583 9276182 · DOI · Paper page
  30. [39]Bautista W. McCrea D.A. Nagy J.I. Connexin36 identified at morphologically mixed chemical/electrical synapses on trigeminal motoneurons and at primary afferent terminals on spinal cord neurons in adult mouse and rat Neuroscience 2014 263 159 180 10.1016/j.neuroscience.2013.12.057 24406437 PMC3951135 · DOI
  31. [40]Nagy J.I. Dudek F.E. Rash J.E. Update on connexins and gap junctions in neurons and glia in the mammalian nervous system Brain Res. Brain Res. Rev. 2004 47 191 215 10.1016/j.brainresrev.2004.05.005 15572172 · DOI · Paper page
  32. [41]Bautista W. Nagy J.I. Dai Y. McCrea D.A. Requirement of neuronal connexin36 in pathways mediating presynaptic inhibition of primary afferents in functionally mature mouse spinal cord J. Physiol. 2012 590 3821 3839 10.1113/jphysiol.2011.225987 22615430 PMC3476635 · DOI
  33. [42]Getting P.A. Modification of neuron properties by electrotonic synapses. I. Input resistance, time constant, and integration J. Neurophysiol. 1974 37 846 857 10.1152/jn.1974.37.5.846 4370202 · DOI
  34. [43]Getting P.A. Willows A.O. Modification of neuron properties by electrotonic synapses. II. Burst formation by electrotonic synapses J. Neurophysiol. 1974 37 858 868 10.1152/jn.1974.37.5.858 4370203 · DOI
  35. [44]Galarreta M. Hestrin S. Spike transmission and synchrony detection in networks of GABAergic interneurons Science 2001 292 2295 2299 10.1126/science.1061395 11423653 · DOI
  36. [45]Veruki M.L. Hartveit E. AII (rod) amacrine cells form a network of electrically coupled interneurons in the mammalian retina Neuron 2002 33 935 946 10.1016/S0896-6273(02)00609-8 11906699 · DOI
  37. [46]Curti S. Hoge G. Nagy J.I. Pereda A.E. Synergy between electrical coupling and membrane properties promotes strong synchronization of neurons of the mesencephalic trigeminal nucleus J. Neurosci. 2012 32 4341 4359 10.1523/JNEUROSCI.6216-11.2012 22457486 PMC3339267 · DOI
  38. [47]Nagy J.I. Pereda A.E. Rash J.E. Electrical synapses in mammalian CNS: Past eras, present focus and future directions Biochim. Biophys. Acta Biomembr. 2018 1860 102 123 10.1016/j.bbamem.2017.05.019 28577972 PMC5705454 · DOI
  39. [48]Galarreta M. Hestrin S. A network of fast-spiking cells in the neocortex connected by electrical synapses Nature 1999 402 72 75 10.1038/47029 10573418 · DOI · Paper page
  40. [49]Gibson J.R. Beierlein M. Connors B.W. Two networks of electrically coupled inhibitory neurons in neocortex Nature 1999 402 75 79 10.1038/47035 10573419 · DOI · Paper page
  41. [50]Fukuda T. Kosaka T. Singer W. Galuske R.A. Gap junctions among dendrites of cortical GABAergic neurons establish a dense and widespread intercolumnar network J. Neurosci. 2006 26 3434 3443 10.1523/JNEUROSCI.4076-05.2006 16571750 PMC6673861 · DOI · Paper page
  42. [51]Blatow M. Rozov A. Katona I. Hormuzdi S.G. Meyer A.H. Whittington M.A. Caputi A. Monyer H. A novel network of multipolar bursting interneurons generates theta frequency oscillations in neocortex Neuron 2003 38 805 817 10.1016/S0896-6273(03)00300-3 12797964 · DOI · Paper page
  43. [52]Diesmann M. Gewaltig M.O. Aertsen A. Stable propagation of synchronous spiking in cortical neural networks Nature 1999 402 529 533 10.1038/990101 10591212 · DOI
  44. [53]Hestrin S. Galarreta M. Electrical synapses define networks of neocortical GABAergic neurons Trends Neurosci. 2005 28 304 309 10.1016/j.tins.2005.04.001 15927686 · DOI · Paper page
  45. [54]Fukuda T. Kosaka T. Gap junctions linking the dendritic network of GABAergic interneurons in the hippocampus J. Neurosci. 2000 20 1519 1528 10.1523/JNEUROSCI.20-04-01519.2000 10662841 PMC6772381 · DOI · Paper page
  46. [55]Buhl D.L. Harris K.D. Hormuzdi S.G. Monyer H. Buzsaki G. Selective impairment of hippocampal gamma oscillations in connexin-36 knock-out mouse in vivo J. Neurosci. 2003 23 1013 1018 10.1523/JNEUROSCI.23-03-01013.2003 12574431 PMC6741916 · DOI
  47. [56]Maier N. Guldenagel M. Sohl G. Siegmund H. Willecke K. Draguhn A. Reduction of high-frequency network oscillations (ripples) and pathological network discharges in hippocampal slices from connexin 36-deficient mice J. Physiol. 2002 541 521 528 10.1113/jphysiol.2002.017624 12042356 PMC2290340 · DOI
  48. [57]Skinner F.K. Zhang L. Velazquez J.L. Carlen P.L. Bursting in inhibitory interneuronal networks: A role for gap-junctional coupling J. Neurophysiol. 1999 81 1274 1283 10.1152/jn.1999.81.3.1274 10085354 · DOI
  49. [58]Traub R.D. Kopell N. Bibbig A. Buhl E.H. LeBeau F.E. Whittington M.A. Gap junctions between interneuron dendrites can enhance synchrony of gamma oscillations in distributed networks J. Neurosci. 2001 21 9478 9486 10.1523/JNEUROSCI.21-23-09478.2001 11717382 PMC6763900 · DOI
  50. [59]Zsiros V. Maccaferri G. Electrical coupling between interneurons with different excitable properties in the stratum lacunosum-moleculare of the juvenile ca1 rat hippocampus J. Neurosci. 2005 25 8686 8695 10.1523/JNEUROSCI.2810-05.2005 16177037 PMC6725508 · DOI · Paper page
  51. [60]Luo L. Architectures of neuronal circuits Science 2021 373 eabg7285 10.1126/science.abg7285 34516844 PMC8916593 · DOI · Paper page
  52. [61]Gunes S. Aizawa Y. Sugashi T. Sugimoto M. Rodrigues P.P. Biomarkers for Alzheimer’s disease in the current state: A narrative review Int. J. Mol. Sci. 2022 23 4962 10.3390/ijms23094962 35563350 PMC9102515 · DOI
  53. [62]Scheltens P. De Strooper B. Kivipelto M. Holstege H. Chetelat G. Teunissen C.E. Cummings J. van der Flier W.M. Alzheimer’s disease Lancet 2021 397 1577 1590 10.1016/S0140-6736(20)32205-4 33667416 PMC8354300 · DOI · Paper page
  54. [63]He F. Zhang Y. Wu X. Li Y. Zhao J. Fang P. Fan L. Li C. Liu T. Wang J. Early microstructure changes of white matter fiber bundles in patients with amnestic mild cognitive impairment predicts progression of mild cognitive impairment to Alzheimer’s disease J. Alzheimers Dis. 2021 84 179 192 10.3233/JAD-210495 34487042 · DOI
  55. [64]Agosta F. Rocca M.A. Pagani E. Absinta M. Magnani G. Marcone A. Falautano M. Comi G. Gorno-Tempini M.L. Filippi M. Sensorimotor network rewiring in mild cognitive impairment and Alzheimer’s disease Hum. Brain Mapp. 2010 31 515 525 10.1002/hbm.20883 19777557 PMC6871105 · DOI
  56. [65]Shao W. Li X. Zhang J. Yang C. Tao W. Zhang S. Zhang Z. Peng D. White matter integrity disruption in the pre-dementia stages of Alzheimer’s disease: From subjective memory impairment to amnestic mild cognitive impairment Eur. J. Neurol. 2019 26 800 807 10.1111/ene.13892 30584694 · DOI
  57. [66]Mahaman Y.A.R. Embaye K.S. Huang F. Li L. Zhu F. Wang J.Z. Liu R. Feng J. Wang X. Biomarkers used in Alzheimer’s disease diagnosis, treatment, and prevention Ageing Res. Rev. 2022 74 101544 10.1016/j.arr.2021.101544 34933129 · DOI · Paper page
  58. [67]Mostany R. Anstey J.E. Crump K.L. Maco B. Knott G. Portera-Cailliau C. Altered synaptic dynamics during normal brain aging J. Neurosci. 2013 33 4094 4104 10.1523/JNEUROSCI.4825-12.2013 23447617 PMC6619332 · DOI · Paper page
  59. [68]Kashyap G. Bapat D. Das D. Gowaikar R. Amritkar R.E. Rangarajan G. Ravindranath V. Ambika G. Synapse loss and progress of Alzheimer’s disease—A network model Sci. Rep. 2019 9 6555 10.1038/s41598-019-43076-y 31024073 PMC6484103 · DOI
  60. [69]Dominguez-Alvaro M. Montero-Crespo M. Blazquez-Llorca L. DeFelipe J. Alonso-Nanclares L. 3d electron microscopy study of synaptic organization of the normal human transentorhinal cortex and its possible alterations in Alzheimer’s disease eNeuro 2019 6 10.1523/ENEURO.0140-19.2019 31217195 PMC6620390 · DOI
  61. [70]Rajmohan R. Reddy P.H. Amyloid-β and phosphorylated tau accumulations cause abnormalities at synapses of Alzheimer’s disease neurons J. Alzheimers Dis. 2017 57 975 999 10.3233/JAD-160612 27567878 PMC5793225 · DOI
  62. [71]Gylys K.H. Fein J.A. Yang F. Wiley D.J. Miller C.A. Cole G.M. Synaptic changes in Alzheimer’s disease: Increased amyloid-β and gliosis in surviving terminals is accompanied by decreased psd-95 fluorescence Am. J. Pathol. 2004 165 1809 1817 10.1016/S0002-9440(10)63436-0 15509549 PMC1618663 · DOI · Paper page
  63. [72]Sturchio A. Dwivedi A.K. Young C.B. Malm T. Marsili L. Sharma J.S. Mahajan A. Hill E.J. Andaloussi S.E. Poston K.L. High cerebrospinal amyloid-β 42 is associated with normal cognition in individuals with brain amyloidosis EClinicalMedicine 2021 38 100988 10.1016/j.eclinm.2021.100988 34505023 PMC8413261 · DOI
  64. [73]Thal D.R. Walter J. Saido T.C. Fandrich M. Neuropathology and biochemistry of aβ and its aggregates in Alzheimer’s disease Acta Neuropathol. 2015 129 167 182 10.1007/s00401-014-1375-y 25534025 · DOI · Paper page
  65. [74]Pickett E.K. Koffie R.M. Wegmann S. Henstridge C.M. Herrmann A.G. Colom-Cadena M. Lleo A. Kay K.R. Vaught M. Soberman R. Non-fibrillar oligomeric amyloid-β within synapses J. Alzheimers Dis. 2016 53 787 800 10.3233/JAD-160007 27258414 · DOI
  66. [75]Bishop M.F. Ferrone F.A. Kinetics of nucleation-controlled polymerization. A perturbation treatment for use with a secondary pathway Biophys. J. 1984 46 631 644 10.1016/S0006-3495(84)84062-X 6498276 PMC1435060 · DOI
  67. [76]Cohen S.I. Vendruscolo M. Dobson C.M. Knowles T.P. Nucleated polymerization with secondary pathways. III. Equilibrium behavior and oligomer populations J. Chem. Phys. 2011 135 065107 10.1063/1.3608918 21842956 PMC5017531 · DOI
  68. [78]Shankar G.M. Li S. Mehta T.H. Garcia-Munoz A. Shepardson N.E. Smith I. Brett F.M. Farrell M.A. Rowan M.J. Lemere C.A. Amyloid-β protein dimers isolated directly from Alzheimer’s brains impair synaptic plasticity and memory Nat. Med. 2008 14 837 842 10.1038/nm1782 18568035 PMC2772133 · DOI · Paper page
  69. [80]Wang Z. Jackson R.J. Hong W. Taylor W.M. Corbett G.T. Moreno A. Liu W. Li S. Frosch M.P. Slutsky I. Human brain-derived Aβ oligomers bind to synapses and disrupt synaptic activity in a manner that requires app J. Neurosci. 2017 37 11947 11966 10.1523/JNEUROSCI.2009-17.2017 29101243 PMC5719975 · DOI
  70. [81]Calabrese B. Shaked G.M. Tabarean I.V. Braga J. Koo E.H. Halpain S. Rapid, concurrent alterations in pre- and postsynaptic structure induced by naturally-secreted amyloid-β protein Mol. Cell Neurosci. 2007 35 183 193 10.1016/j.mcn.2007.02.006 17368908 PMC2268524 · DOI
  71. [82]Lue L.F. Kuo Y.M. Roher A.E. Brachova L. Shen Y. Sue L. Beach T. Kurth J.H. Rydel R.E. Rogers J. Soluble amyloid β peptide concentration as a predictor of synaptic change in Alzheimer’s disease Am. J. Pathol. 1999 155 853 862 10.1016/S0002-9440(10)65184-X 10487842 PMC1866907 · DOI · Paper page
  72. [83]Bao F. Wicklund L. Lacor P.N. Klein W.L. Nordberg A. Marutle A. Different β-amyloid oligomer assemblies in Alzheimer brains correlate with age of disease onset and impaired cholinergic activity Neurobiol. Aging 2012 33 825-e1 10.1016/j.neurobiolaging.2011.05.003 21683475 · DOI
  73. [85]Haas L.T. Salazar S.V. Kostylev M.A. Um J.W. Kaufman A.C. Strittmatter S.M. Metabotropic glutamate receptor 5 couples cellular prion protein to intracellular signalling in Alzheimer’s disease Brain 2016 139 526 546 10.1093/brain/awv356 26667279 PMC4840505 · DOI
  74. [86]Alon A. Schmidt H.R. Wood M.D. Sahn J.J. Martin S.F. Kruse A.C. Identification of the gene that codes for the sigma2 receptor Proc. Natl. Acad. Sci. USA 2017 114 7160 7165 10.1073/pnas.1705154114 28559337 PMC5502638 · DOI
  75. [87]Xu J. Zeng C. Chu W. Pan F. Rothfuss J.M. Zhang F. Tu Z. Zhou D. Zeng D. Vangveravong S. Identification of the pgrmc1 protein complex as the putative sigma-2 receptor binding site Nat. Commun. 2011 2 380 10.1038/ncomms1386 21730960 PMC3624020 · DOI
  76. [88]Riad A. Zeng C. Weng C.C. Winters H. Xu K. Makvandi M. Metz T. Carlin S. Mach R.H. Sigma-2 receptor/tmem97 and pgrmc-1 increase the rate of internalization of LDL by LDL receptor through the formation of a ternary complex Sci. Rep. 2018 8 16845 10.1038/s41598-018-35430-3 30443021 PMC6238005 · DOI
  77. [89]Smith L.M. Strittmatter S.M. Binding sites for amyloid-β oligomers and synaptic toxicity Cold Spring Harb. Perspect. Med. 2017 7 a024075 10.1101/cshperspect.a024075 27940601 PMC5411685 · DOI
  78. [90]Cisse M. Halabisky B. Harris J. Devidze N. Dubal D.B. Sun B. Orr A. Lotz G. Kim D.H. Hamto P. Reversing EphB2 depletion rescues cognitive functions in Alzheimer model Nature 2011 469 47 52 10.1038/nature09635 21113149 PMC3030448 · DOI · Paper page
  79. [91]Spires-Jones T.L. Hyman B.T. The intersection of amyloid beta and tau at synapses in Alzheimer’s disease Neuron 2014 82 756 771 10.1016/j.neuron.2014.05.004 24853936 PMC4135182 · DOI · Paper page
  80. [92]Kuchibhotla K.V. Lattarulo C.R. Hyman B.T. Bacskai B.J. Synchronous hyperactivity and intercellular calcium waves in astrocytes in Alzheimer mice Science 2009 323 1211 1215 10.1126/science.1169096 19251629 PMC2884172 · DOI · Paper page
  81. [93]Busche M.A. Eichhoff G. Adelsberger H. Abramowski D. Wiederhold K.H. Haass C. Staufenbiel M. Konnerth A. Garaschuk O. Clusters of hyperactive neurons near amyloid plaques in a mouse model of Alzheimer’s disease Science 2008 321 1686 1689 10.1126/science.1162844 18802001 · DOI · Paper page
  82. [94]Bilousova T. Miller C.A. Poon W.W. Vinters H.V. Corrada M. Kawas C. Hayden E.Y. Teplow D.B. Glabe C. Albay R. 3rd Synaptic amyloid-β oligomers precede p-Tau and differentiate high pathology control cases Am. J. Pathol. 2016 186 185 198 10.1016/j.ajpath.2015.09.018 26718979 PMC4715217 · DOI
  83. [95]Bakota L. Brandt R. Tau biology and tau-directed therapies for Alzheimer’s disease Drugs 2016 76 301 313 10.1007/s40265-015-0529-0 26729186 PMC4757605 · DOI
  84. [97]Taylor H.B.C. Emptage N.J. Jeans A.F. Long-term depression links amyloid-β to the pathological hyperphosphorylation of tau Cell Rep. 2021 36 109638 10.1016/j.celrep.2021.109638 34469725 PMC8424646 · DOI
  85. [98]Lyu D. Jia J. Cryptotanshinone Attenuates Amyloid-β42-induced Tau Phosphorylation by Regulating PI3K/Akt/GSK3β Pathway in HT22 Cells Mol. Neurobiol. 2022 59 4488 4500 10.1007/s12035-022-02850-2 35575872 · DOI
  86. [99]Han S. Jeong Y.Y. Sheshadri P. Su X. Cai Q. Mitophagy regulates integrity of mitochondria at synapses and is critical for synaptic maintenance EMBO Rep. 2020 21 e49801 10.15252/embr.201949801 32627320 PMC7507095 · DOI
  87. [100]Pradeepkiran J.A. Reddy P.H. Defective mitophagy in Alzheimer’s disease Ageing Res. Rev. 2020 64 101191 10.1016/j.arr.2020.101191 33022416 PMC7710581 · DOI · Paper page
  88. [101]Fang E.F. Hou Y. Palikaras K. Adriaanse B.A. Kerr J.S. Yang B. Lautrup S. Hasan-Olive M.M. Caponio D. Dan X. Mitophagy inhibits amyloid-β and tau pathology and reverses cognitive deficits in models of Alzheimer’s disease Nat. Neurosci. 2019 22 401 412 10.1038/s41593-018-0332-9 30742114 PMC6693625 · DOI · Paper page
  89. [102]Reddy P.H. Yin X. Manczak M. Kumar S. Pradeepkiran J.A. Vijayan M. Reddy A.P. Mutant app and amyloid β -induced defective autophagy, mitophagy, mitochondrial structural and functional changes and synaptic damage in hippocampal neurons from Alzheimer’s disease Hum. Mol. Genet. 2018 27 2502 2516 10.1093/hmg/ddy154 29701781 PMC6031001 · DOI
  90. [103]Manczak M. Kandimalla R. Yin X. Reddy P.H. Hippocampal mutant app and amyloid β-induced cognitive decline, dendritic spine loss, defective autophagy, mitophagy and mitochondrial abnormalities in a mouse model of Alzheimer’s disease Hum. Mol. Genet. 2018 27 1332 1342 10.1093/hmg/ddy042 29408999 PMC6455948 · DOI
  91. [105]Xie J. Wang H. Lin T. Bi B. Microglia-synapse pathways: Promising therapeutic strategy for Alzheimer’s disease Biomed. Res. Int. 2017 2017 2986460 10.1155/2017/2986460 28473983 PMC5394358 · DOI
  92. [107]Werneburg S. Feinberg P.A. Johnson K.M. Schafer D.P. A microglia-cytokine axis to modulate synaptic connectivity and function Curr. Opin. Neurobiol. 2017 47 138 145 10.1016/j.conb.2017.10.002 29096242 PMC5797987 · DOI
  93. [108]Badimon A. Strasburger H.J. Ayata P. Chen X. Nair A. Ikegami A. Hwang P. Chan A.T. Graves S.M. Uweru J.O. Negative feedback control of neuronal activity by microglia Nature 2020 586 417 423 10.1038/s41586-020-2777-8 32999463 PMC7577179 · DOI · Paper page
  94. [109]Cheyne J.E. Montgomery J.M. The cellular and molecular basis of in vivo synaptic plasticity in rodents Am. J. Physiol. Cell Physiol. 2020 318 C1264 C1283 10.1152/ajpcell.00416.2019 32320288 · DOI
  95. [110]Stent G.S. A physiological mechanism for Hebb’s postulate of learning Proc. Natl. Acad. Sci. USA 1973 70 997 1001 10.1073/pnas.70.4.997 4352227 PMC433410 · DOI
  96. [111]Montgomery J.M. Pavlidis P. Madison D.V. Pair recordings reveal all-silent synaptic connections and the postsynaptic expression of long-term potentiation Neuron 2001 29 691 701 10.1016/S0896-6273(01)00244-6 11301028 · DOI
  97. [112]Montgomery J.M. Selcher J.C. Hanson J.E. Madison D.V. Dynamin-dependent NMDAR endocytosis during LTD and its dependence on synaptic state BMC Neurosci. 2005 6 48 10.1186/1471-2202-6-48 16042781 PMC1187896 · DOI
  98. [113]Nabavi S. Kessels H.W. Alfonso S. Aow J. Fox R. Malinow R. Metabotropic NMDA receptor function is required for NMDA receptor-dependent long-term depression Proc. Natl. Acad. Sci. USA 2013 110 4027 4032 10.1073/pnas.1219454110 23431133 PMC3593861 · DOI
  99. [114]Carroll R.C. Beattie E.C. Xia H. Luscher C. Altschuler Y. Nicoll R.A. Malenka R.C. von Zastrow M. Dynamin-dependent endocytosis of ionotropic glutamate receptors Proc. Natl. Acad. Sci. USA 1999 96 14112 14117 10.1073/pnas.96.24.14112 10570207 PMC24199 · DOI
  100. [115]Tan H.L. Roth R.H. Graves A.R. Cudmore R.H. Huganir R.L. Lamina-specific AMPA receptor dynamics following visual deprivation in vivo Elife 2020 9 e52420 10.7554/eLife.52420 32125273 PMC7053996 · DOI
  101. [116]Cuestas Torres D.M. Cardenas F.P. Synaptic plasticity in Alzheimer’s disease and healthy aging Rev. Neurosci. 2020 31 245 268 10.1515/revneuro-2019-0058 32250284 · DOI
  102. [117]Spires T.L. Hyman B.T. Transgenic models of Alzheimer’s disease: Learning from animals NeuroRx 2005 2 423 437 10.1602/neurorx.2.3.423 16389306 PMC1144486 · DOI
  103. [118]Moolman D.L. Vitolo O.V. Vonsattel J.P. Shelanski M.L. Dendrite and dendritic spine alterations in Alzheimer models J. Neurocytol. 2004 33 377 387 10.1023/B:NEUR.0000044197.83514.64 15475691 · DOI · Paper page
  104. [119]Dong H. Martin M.V. Chambers S. Csernansky J.G. Spatial relationship between synapse loss and β-amyloid deposition in tg2576 mice J. Comp. Neurol. 2007 500 311 321 10.1002/cne.21176 17111375 PMC1661843 · DOI
  105. [120]Rocher A.B. Crimins J.L. Amatrudo J.M. Kinson M.S. Todd-Brown M.A. Lewis J. Luebke J.I. Structural and functional changes in tau mutant mice neurons are not linked to the presence of NFTs Exp. Neurol. 2010 223 385 393 10.1016/j.expneurol.2009.07.029 19665462 PMC2864360 · DOI · Paper page
  106. [121]Eckermann K. Mocanu M.M. Khlistunova I. Biernat J. Nissen A. Hofmann A. Schonig K. Bujard H. Haemisch A. Mandelkow E. The β-propensity of tau determines aggregation and synaptic loss in inducible mouse models of tauopathy J. Biol. Chem. 2007 282 31755 31765 10.1074/jbc.M705282200 17716969 · DOI · Paper page
  107. [122]Boekhoorn K. Terwel D. Biemans B. Borghgraef P. Wiegert O. Ramakers G.J. de Vos K. Krugers H. Tomiyama T. Mori H. Improved long-term potentiation and memory in young tau-P301L transgenic mice before onset of hyperphosphorylation and tauopathy J. Neurosci. 2006 26 3514 3523 10.1523/JNEUROSCI.5425-05.2006 16571759 PMC6673867 · DOI
  108. [123]Thies E. Mandelkow E.M. Missorting of tau in neurons causes degeneration of synapses that can be rescued by the kinase MARK2/Par-1 J. Neurosci. 2007 27 2896 2907 10.1523/JNEUROSCI.4674-06.2007 17360912 PMC6672561 · DOI · Paper page
  109. [124]Counts S.E. Alldred M.J. Che S. Ginsberg S.D. Mufson E.J. Synaptic gene dysregulation within hippocampal ca1 pyramidal neurons in mild cognitive impairment Neuropharmacology 2014 79 172 179 10.1016/j.neuropharm.2013.10.018 24445080 PMC3951099 · DOI
  110. [125]Liu Y. Xu Y. Zhang L. Huang L. Yu P. Zhu H. Deng W. Qin C. Down-regulated drebrin aggravates cognitive impairments in a mouse model of Alzheimer’s disease Int. J. Mol. Sci. 2017 18 800 10.3390/ijms18040800 28398234 PMC5412384 · DOI
  111. [126]Koffie R.M. Hyman B.T. Spires-Jones T.L. Alzheimer’s disease: Synapses gone cold Mol. Neurodegener. 2011 6 63 10.1186/1750-1326-6-63 21871088 PMC3178498 · DOI
  112. [127]Pozueta J. Lefort R. Shelanski M.L. Synaptic changes in Alzheimer’s disease and its models Neuroscience 2013 251 51 65 10.1016/j.neuroscience.2012.05.050 22687952 · DOI
  113. [128]Targa Dias Anastacio H. Matosin N. Ooi L. Neuronal hyperexcitability in Alzheimer’s disease: What are the drivers behind this aberrant phenotype? Transl. Psychiatry 2022 12 257 10.1038/s41398-022-02024-7 35732622 PMC9217953 · DOI · Paper page
  114. [129]Lazarevic V. Fienko S. Andres-Alonso M. Anni D. Ivanova D. Montenegro-Venegas C. Gundelfinger E.D. Cousin M.A. Fejtova A. Physiological concentrations of amyloid beta regulate recycling of synaptic vesicles via alpha7 acetylcholine receptor and CDK5/calcineurin signaling Front. Mol. Neurosci. 2017 10 221 10.3389/fnmol.2017.00221 28785201 PMC5520466 · DOI
  115. [130]Busche M.A. Chen X. Henning H.A. Reichwald J. Staufenbiel M. Sakmann B. Konnerth A. Critical role of soluble amyloid-β for early hippocampal hyperactivity in a mouse model of Alzheimer’s disease Proc. Natl. Acad. Sci. USA 2012 109 8740 8745 10.1073/pnas.1206171109 22592800 PMC3365221 · DOI · Paper page
  116. [132]Horvath A.A. Papp A. Zsuffa J. Szucs A. Luckl J. Radai F. Nagy F. Hidasi Z. Csukly G. Barcs G. Subclinical epileptiform activity accelerates the progression of Alzheimer’s disease: A long-term EEG study Clin. Neurophysiol. 2021 132 1982 1989 10.1016/j.clinph.2021.03.050 34034963 · DOI · Paper page
  117. [133]Vossel K.A. Beagle A.J. Rabinovici G.D. Shu H. Lee S.E. Naasan G. Hegde M. Cornes S.B. Henry M.L. Nelson A.B. Seizures and epileptiform activity in the early stages of Alzheimer disease JAMA Neurol. 2013 70 1158 1166 10.1001/jamaneurol.2013.136 23835471 PMC4013391 · DOI
  118. [134]Wiesman A.I. Murman D.L. Losh R.A. Schantell M. Christopher-Hayes N.J. Johnson H.J. Willett M.P. Wolfson S.L. Losh K.L. Johnson C.M. Spatially resolved neural slowing predicts impairment and amyloid burden in Alzheimer’s disease Brain 2022 145 2177 2189 10.1093/brain/awab430 35088842 PMC9246709 · DOI
  119. [135]Huijbers W. Mormino E.C. Schultz A.P. Wigman S. Ward A.M. Larvie M. Amariglio R.E. Marshall G.A. Rentz D.M. Johnson K.A. Amyloid-β deposition in mild cognitive impairment is associated with increased hippocampal activity, atrophy and clinical progression Brain 2015 138 1023 1035 10.1093/brain/awv007 25678559 PMC4438387 · DOI
  120. [136]Quiroz Y.T. Budson A.E. Celone K. Ruiz A. Newmark R. Castrillon G. Lopera F. Stern C.E. Hippocampal hyperactivation in presymptomatic familial Alzheimer’s disease Ann. Neurol. 2010 68 865 875 10.1002/ana.22105 21194156 PMC3175143 · DOI
  121. [137]Reiman E.M. Quiroz Y.T. Fleisher A.S. Chen K. Velez-Pardo C. Jimenez-Del-Rio M. Fagan A.M. Shah A.R. Alvarez S. Arbelaez A. Brain imaging and fluid biomarker analysis in young adults at genetic risk for autosomal dominant Alzheimer’s disease in the presenilin 1 E280A kindred: A case-control study Lancet Neurol. 2012 11 1048 1056 10.1016/S1474-4422(12)70228-4 23137948 PMC4181671 · DOI · Paper page
  122. [138]Van Nifterick A.M. Gouw A.A. van Kesteren R.E. Scheltens P. Stam C.J. de Haan W. A multiscale brain network model links Alzheimer’s disease-mediated neuronal hyperactivity to large-scale oscillatory slowing Alzheimers Res. Ther. 2022 14 101 10.1186/s13195-022-01041-4 35879779 PMC9310500 · DOI
  123. [139]Mohamed S.M.H. Butzbach M. Fuermaier A.B.M. Weisbrod M. Aschenbrenner S. Tucha L. Tucha O. Basic and complex cognitive functions in adult adhd PLoS ONE 2021 16 e0256228 10.1371/journal.pone.0256228 34473722 PMC8412315 · DOI
  124. [140]Roberts B.M. Libby L.A. Inhoff M.C. Ranganath C. Brain activity related to working memory for temporal order and object information Behav. Brain Res. 2018 354 55 63 10.1016/j.bbr.2017.05.068 28602963 · DOI
  125. [141]Mesulam M.M. Human brain cholinergic pathways Prog. Brain Res. 1990 84 231 241 2267300
  126. [142]Mesulam M.M. Large-scale neurocognitive networks and distributed processing for attention, language, and memory Ann. Neurol. 1990 28 597 613 10.1002/ana.410280502 2260847 · DOI · Paper page
  127. [143]Alves P.N. Foulon C. Karolis V. Bzdok D. Margulies D.S. Volle E. Thiebaut de Schotten M. An improved neuroanatomical model of the default-mode network reconciles previous neuroimaging and neuropathological findings Commun. Biol. 2019 2 370 10.1038/s42003-019-0611-3 31633061 PMC6787009 · DOI · Paper page
  128. [144]Guo Q. Hu Y. Zeng B. Tang Y. Li G. Zhang T. Wang J. Northoff G. Li C. Goff D. Parietal memory network and default mode network in first-episode drug-naive schizophrenia: Associations with auditory hallucination Hum. Brain Mapp. 2020 41 1973 1984 10.1002/hbm.24923 32112506 PMC7267906 · DOI
  129. [145]Chand G.B. Thakuri D.S. Soni B. Salience network anatomical and molecular markers are linked with cognitive dysfunction in mild cognitive impairment J. Neuroimaging 2022 32 728 734 10.1111/jon.12980 35165968 · DOI
  130. [146]Ptak R. Schnider A. Fellrath J. The dorsal frontoparietal network: A core system for emulated action Trends Cogn. Sci. 2017 21 589 599 10.1016/j.tics.2017.05.002 28578977 · DOI
  131. [147]Vendetti M.S. Bunge S.A. Evolutionary and developmental changes in the lateral frontoparietal network: A little goes a long way for higher-level cognition Neuron 2014 84 906 917 10.1016/j.neuron.2014.09.035 25475185 PMC4527542 · DOI
  132. [148]Wei W. Zhu T. Wang X. Li L. Zou Q. Lv Y. Altered topological organization in the sensorimotor network after application of different frequency RTMS Front. Neurosci. 2019 13 1377 10.3389/fnins.2019.01377 31920525 PMC6930905 · DOI
  133. [149]Shen W. Tu Y. Gollub R.L. Ortiz A. Napadow V. Yu S. Wilson G. Park J. Lang C. Jung M. Visual network alterations in brain functional connectivity in chronic low back pain: A resting state functional connectivity and machine learning study Neuroimage Clin. 2019 22 101775 10.1016/j.nicl.2019.101775 30927604 PMC6444301 · DOI
  134. [150]Uddin L.Q. Yeo B.T.T. Spreng R.N. Towards a universal taxonomy of macro-scale functional human brain networks Brain Topogr. 2019 32 926 942 10.1007/s10548-019-00744-6 31707621 PMC7325607 · DOI · Paper page
  135. [151]Arnulfo G. Wang S.H. Myrov V. Toselli B. Hirvonen J. Fato M.M. Nobili L. Cardinale F. Rubino A. Zhigalov A. Long-range phase synchronization of high-frequency oscillations in human cortex Nat. Commun. 2020 11 5363 10.1038/s41467-020-18975-8 33097714 PMC7584610 · DOI
  136. [152]Sun F.W. Stepanovic M.R. Andreano J. Barrett L.F. Touroutoglou A. Dickerson B.C. Youthful brains in older adults: Preserved neuroanatomy in the default mode and salience networks contributes to youthful memory in superaging J. Neurosci. 2016 36 9659 9668 10.1523/JNEUROSCI.1492-16.2016 27629716 PMC5039247 · DOI · Paper page
  137. [153]Zhang J. Andreano J.M. Dickerson B.C. Touroutoglou A. Barrett L.F. Stronger functional connectivity in the default mode and salience networks is associated with youthful memory in superaging Cereb. Cortex 2020 30 72 84 10.1093/cercor/bhz071 31058917 PMC7029690 · DOI
  138. [154]Alm K.H. Soldan A. Pettigrew C. Faria A.V. Hou X. Lu H. Moghekar A. Mori S. Albert M. Bakker A. Structural and functional brain connectivity uniquely contribute to episodic memory performance in older adults Front. Aging Neurosci. 2022 14 951076 10.3389/fnagi.2022.951076 35903538 PMC9315224 · DOI
  139. [155]Hu Y. Du W. Zhang Y. Li N. Han Y. Yang Z. Loss of parietal memory network integrity in Alzheimer’s disease Front. Aging Neurosci. 2019 11 67 10.3389/fnagi.2019.00067 30971912 PMC6446948 · DOI
  140. [156]Chan M.Y. Han L. Carreno C.A. Zhang Z. Rodriguez R.M. LaRose M. Hassenstab J. Wig G.S. Long-term prognosis and educational determinants of brain network decline in older adult individuals Nat. Aging 2021 1 1053 1067 10.1038/s43587-021-00125-4 35382259 PMC8979545 · DOI
  141. [157]Dai Z. Lin Q. Li T. Wang X. Yuan H. Yu X. He Y. Wang H. Disrupted structural and functional brain networks in Alzheimer’s disease Neurobiol. Aging 2019 75 71 82 10.1016/j.neurobiolaging.2018.11.005 30553155 · DOI
  142. [158]Zhang M. Guan Z. Zhang Y. Sun W. Li W. Hu J. Li B. Ye G. Meng H. Huang X. Disrupted coupling between salience network segregation and glucose metabolism is associated with cognitive decline in Alzheimer’s disease—A simultaneous resting-state FDG-PET/fMRI study Neuroimage Clin. 2022 34 102977 10.1016/j.nicl.2022.102977 35259618 PMC8904621 · DOI
  143. [159]Ng A.S.L. Wang J. Ng K.K. Chong J.S.X. Qian X. Lim J.K.W. Tan Y.J. Yong A.C.W. Chander R.J. Hameed S. Distinct network topology in Alzheimer’s disease and behavioral variant frontotemporal dementia Alzheimers Res. Ther. 2021 13 13 10.1186/s13195-020-00752-w 33407913 PMC7786961 · DOI
  144. [160]Terry R.D. Masliah E. Salmon D.P. Butters N. DeTeresa R. Hill R. Hansen L.A. Katzman R. Physical basis of cognitive alterations in Alzheimer’s disease: Synapse loss is the major correlate of cognitive impairment Ann. Neurol. 1991 30 572 580 10.1002/ana.410300410 1789684 · DOI · Paper page
  145. [161]Yuan Y. Gu Z.X. Wei W.S. Fluorodeoxyglucose-positron-emission tomography, single-photon emission tomography, and structural MR imaging for prediction of rapid conversion to Alzheimer disease in patients with mild cognitive impairment: A meta-analysis AJNR Am. J. Neuroradiol. 2009 30 404 410 10.3174/ajnr.A1357 19001534 PMC7051416 · DOI
  146. [162]Mahmmoud R.R. Sase S. Aher Y.D. Sase A. Groger M. Mokhtar M. Hoger H. Lubec G. Spatial and working memory is linked to spine density and mushroom spines PLoS ONE 2015 10 e0139739 10.1371/journal.pone.0139739 26469788 PMC4607435 · DOI
  147. [163]Ma S. Zuo Y. Synaptic modifications in learning and memory—A dendritic spine story Semin. Cell Dev. Biol. 2022 125 84 90 10.1016/j.semcdb.2021.05.015 34020876 PMC9547722 · DOI
  148. [164]Lordkipanidze T. Bikashvili T. Japaridze N. Zhvania M. The effect of kainic acid on hippocampal dendritic spine motility at the early and late stages of brain development Micron 2013 49 28 32 10.1016/j.micron.2013.02.009 23548670 · DOI
  149. [165]Obashi K. Taraska J.W. Okabe S. The role of molecular diffusion within dendritic spines in synaptic function J. Gen. Physiol. 2021 153 e202012814 10.1085/jgp.202012814 33720306 PMC7967910 · DOI
  150. [166]Hotulainen P. Hoogenraad C.C. Actin in dendritic spines: Connecting dynamics to function J. Cell Biol. 2010 189 619 629 10.1083/jcb.201003008 20457765 PMC2872912 · DOI · Paper page
  151. [167]Fortin D.A. Srivastava T. Soderling T.R. Structural modulation of dendritic spines during synaptic plasticity Neuroscientist 2012 18 326 341 10.1177/1073858411407206 21670426 · DOI
  152. [168]Lauterborn J.C. Scaduto P. Cox C.D. Schulmann A. Lynch G. Gall C.M. Keene C.D. Limon A. Increased excitatory to inhibitory synaptic ratio in parietal cortex samples from individuals with Alzheimer’s disease Nat. Commun. 2021 12 2603 10.1038/s41467-021-22742-8 33972518 PMC8110554 · DOI
  153. [170]Sheng M. Kim E. The postsynaptic organization of synapses Cold Spring Harb. Perspect. Biol. 2011 3 a005678 10.1101/cshperspect.a005678 22046028 PMC3225953 · DOI · Paper page
  154. [171]McLeod F. Marzo A. Podpolny M. Galli S. Salinas P. Evaluation of synapse density in hippocampal rodent brain slices J. Vis. Exp. 2017 128 e56153 PMC5752395 29053699
  155. [172]Favuzzi E. Rico B. Molecular diversity underlying cortical excitatory and inhibitory synapse development Curr. Opin. Neurobiol. 2018 53 8 15 10.1016/j.conb.2018.03.011 29704699 · DOI
  156. [174]Shihan M.H. Novo S.G. Le Marchand S.J. Wang Y. Duncan M.K. A simple method for quantitating confocal fluorescent images Biochem. Biophys. Rep. 2021 25 100916 10.1016/j.bbrep.2021.100916 33553685 PMC7856428 · DOI
  157. [175]Varghese M. Keshav N. Jacot-Descombes S. Warda T. Wicinski B. Dickstein D.L. Harony-Nicolas H. De Rubeis S. Drapeau E. Buxbaum J.D. Autism spectrum disorder: Neuropathology and animal models Acta Neuropathol. 2017 134 537 566 10.1007/s00401-017-1736-4 28584888 PMC5693718 · DOI · Paper page
  158. [176]Gu J. Firestein B.L. Zheng J.Q. Microtubules in dendritic spine development J. Neurosci. 2008 28 12120 12124 10.1523/JNEUROSCI.2509-08.2008 19005076 PMC2605155 · DOI
  159. [177]Baczynska E. Pels K.K. Basu S. Wlodarczyk J. Ruszczycki B. Quantification of dendritic spines remodeling under physiological stimuli and in pathological conditions Int. J. Mol. Sci. 2021 22 4053 10.3390/ijms22084053 33919977 PMC8070910 · DOI
  160. [178]Fernandez-Perez E.J. Gallegos S. Armijo-Weingart L. Araya A. Riffo-Lepe N.O. Cayuman F. Aguayo L.G. Changes in neuronal excitability and synaptic transmission in nucleus accumbens in a transgenic Alzheimer’s disease mouse model Sci. Rep. 2020 10 19606 10.1038/s41598-020-76456-w 33177601 PMC7659319 · DOI
  161. [179]Nieminen P. Kakela R. Makinen T. Laine O. Takalo T. Mustonen A.M. Preservation of fatty acid signatures in three vertebrate species after six months of storage at various temperatures PLoS ONE 2018 13 e0204207 10.1371/journal.pone.0204207 30222764 PMC6141075 · DOI
  162. [180]Stallings N.R. O’Neal M.A. Hu J. Kavalali E.T. Bezprozvanny I. Malter J.S. Pin1 mediates aβ42-induced dendritic spine loss Sci. Signal. 2018 11 eaap8734 10.1126/scisignal.aap8734 29559586 PMC6136423 · DOI
  163. [181]Reza-Zaldivar E.E. Hernandez-Sapiens M.A. Minjarez B. Gomez-Pinedo U. Sanchez-Gonzalez V.J. Marquez-Aguirre A.L. Canales-Aguirre A.A. Dendritic spine and synaptic plasticity in Alzheimer’s disease: A focus on microRNA Front. Cell Dev. Biol. 2020 8 255 10.3389/fcell.2020.00255 32432108 PMC7214692 · DOI
  164. [182]Jacobsen J.S. Wu C.C. Redwine J.M. Comery T.A. Arias R. Bowlby M. Martone R. Morrison J.H. Pangalos M.N. Reinhart P.H. Early-onset behavioral and synaptic deficits in a mouse model of Alzheimer’s disease Proc. Natl. Acad. Sci. USA 2006 103 5161 5166 10.1073/pnas.0600948103 16549764 PMC1405622 · DOI · Paper page
  165. [183]Vervaeke K. Lorincz A. Nusser Z. Silver R.A. Gap junctions compensate for sublinear dendritic integration in an inhibitory network Science 2012 335 1624 1628 10.1126/science.1215101 22403180 PMC3587282 · DOI
  166. [184]Mielnicka A. Michaluk P. Exocytosis in astrocytes Biomolecules 2021 11 1367 10.3390/biom11091367 34572580 PMC8471187 · DOI
  167. [185]Brioschi S. d’Errico P. Amann L.S. Janova H. Wojcik S.M. Meyer-Luehmann M. Rajendran L. Wieghofer P. Paolicelli R.C. Biber K. Detection of synaptic proteins in microglia by flow cytometry Front. Mol. Neurosci. 2020 13 149 10.3389/fnmol.2020.00149 33132837 PMC7550663 · DOI
  168. [186]Vicidomini G. Bianchini P. Diaspro A. STED super-resolved microscopy Nat. Methods 2018 15 173 182 10.1038/nmeth.4593 29377014 · DOI
  169. [187]Sahl S.J. Hell S.W. High-resolution 3d light microscopy with STED and RESOLFT High Resolution Imaging in Microscopy and Ophthalmology: New Frontiers in Biomedical Optics Bille J.F. Springer Cham, Switzerland 2019 3 32 32091851
  170. [188]Tonnesen J. Inavalli V. Nagerl U.V. Super-resolution imaging of the extracellular space in living brain tissue Cell 2018 172 1108 1121.e1115 10.1016/j.cell.2018.02.007 29474910 · DOI
  171. [189]Kvartsberg H. Lashley T. Murray C.E. Brinkmalm G. Cullen N.C. Hoglund K. Zetterberg H. Blennow K. Portelius E. The intact postsynaptic protein neurogranin is reduced in brain tissue from patients with familial and sporadic Alzheimer’s disease Acta Neuropathol. 2019 137 89 102 10.1007/s00401-018-1910-3 30244311 PMC6338696 · DOI
  172. [190]Kvartsberg H. Duits F.H. Ingelsson M. Andreasen N. Ohrfelt A. Andersson K. Brinkmalm G. Lannfelt L. Minthon L. Hansson O. Cerebrospinal fluid levels of the synaptic protein neurogranin correlates with cognitive decline in prodromal Alzheimer’s disease Alzheimers Dement. 2015 11 1180 1190 10.1016/j.jalz.2014.10.009 25533203 · DOI
  173. [191]Portelius E. Zetterberg H. Skillback T. Tornqvist U. Andreasson U. Trojanowski J.Q. Weiner M.W. Shaw L.M. Mattsson N. Blennow K. Cerebrospinal fluid neurogranin: Relation to cognition and neurodegeneration in Alzheimer’s disease Brain 2015 138 3373 3385 10.1093/brain/awv267 26373605 PMC4643642 · DOI · Paper page
  174. [192]Tarawneh R. D’Angelo G. Crimmins D. Herries E. Griest T. Fagan A.M. Zipfel G.J. Ladenson J.H. Morris J.C. Holtzman D.M. Diagnostic and prognostic utility of the synaptic marker neurogranin in Alzheimer disease JAMA Neurol. 2016 73 561 571 10.1001/jamaneurol.2016.0086 27018940 PMC4861689 · DOI
  175. [194]De Wilde M.C. Overk C.R. Sijben J.W. Masliah E. Meta-analysis of synaptic pathology in Alzheimer’s disease reveals selective molecular vesicular machinery vulnerability Alzheimers Dement. 2016 12 633 644 10.1016/j.jalz.2015.12.005 26776762 PMC5058345 · DOI
  176. [196]Canas P.M. Simoes A.P. Rodrigues R.J. Cunha R.A. Predominant loss of glutamatergic terminal markers in a β-amyloid peptide model of Alzheimer’s disease Neuropharmacology 2014 76 51 56 10.1016/j.neuropharm.2013.08.026 24029236 · DOI
  177. [197]Roselli F. Tirard M. Lu J. Hutzler P. Lamberti P. Livrea P. Morabito M. Almeida O.F. Soluble β-amyloid1-40 induces NMDA-dependent degradation of postsynaptic density-95 at glutamatergic synapses J. Neurosci. 2005 25 11061 11070 10.1523/JNEUROSCI.3034-05.2005 16319306 PMC6725651 · DOI
  178. [198]Mila-Aloma M. Brinkmalm A. Ashton N.J. Kvartsberg H. Shekari M. Operto G. Salvado G. Falcon C. Gispert J.D. Vilor-Tejedor N. CSF synaptic biomarkers in the preclinical stage of Alzheimer disease and their association with MRI and PET: A cross-sectional study Neurology 2021 97 e2065 e2078 10.1212/WNL.0000000000012853 34556565 PMC8610620 · DOI
  179. [199]Vrillon A. Mouton-Liger F. Martinet M. Cognat E. Hourregue C. Dumurgier J. Bouaziz-Amar E. Brinkmalm A. Blennow K. Zetterberg H. Plasma neuregulin 1 as a synaptic biomarker in Alzheimer’s disease: A discovery cohort study Alzheimers Res. Ther. 2022 14 71 10.1186/s13195-022-01014-7 35606871 PMC9125890 · DOI
  180. [200]Jia L. Zhu M. Kong C. Pang Y. Zhang H. Qiu Q. Wei C. Tang Y. Wang Q. Li Y. Blood neuro-exosomal synaptic proteins predict Alzheimer’s disease at the asymptomatic stage Alzheimers Dement. 2021 17 49 60 10.1002/alz.12166 32776690 PMC7984076 · DOI
  181. [201]Jia L. Zhu M. Yang J. Pang Y. Wang Q. Li T. Li F. Wang Q. Li Y. Wei Y. Exosomal microRNA-based predictive model for preclinical Alzheimer’s disease: A multicenter study Biol. Psychiatry 2022 92 44 53 10.1016/j.biopsych.2021.12.015 35221095 · DOI
  182. [202]Nilsson J. Gobom J. Sjodin S. Brinkmalm G. Ashton N.J. Svensson J. Johansson P. Portelius E. Zetterberg H. Blennow K. Cerebrospinal fluid biomarker panel for synaptic dysfunction in Alzheimer’s disease Alzheimers Dement. 2021 13 e12179 10.1002/dad2.12179 PMC8087978 33969172 · DOI · Paper page
  183. [203]Li Y. Xia M. Meng S. Wu D. Ling S. Chen X. Liu C. MicroRNA-29c-3p in dual-labeled exosome is a potential diagnostic marker of subjective cognitive decline Neurobiol. Dis. 2022 171 105800 10.1016/j.nbd.2022.105800 35752392 · DOI
  184. [204]Lleo A. Nunez-Llaves R. Alcolea D. Chiva C. Balateu-Panos D. Colom-Cadena M. Gomez-Giro G. Munoz L. Querol-Vilaseca M. Pegueroles J. Changes in synaptic proteins precede neurodegeneration markers in preclinical Alzheimer’s disease cerebrospinal fluid Mol. Cell Proteom. 2019 18 546 560 10.1074/mcp.RA118.001290 30606734 PMC6398205 · DOI · Paper page
  185. [205]Chen M.K. Mecca A.P. Naganawa M. Finnema S.J. Toyonaga T. Lin S.F. Najafzadeh S. Ropchan J. Lu Y. McDonald J.W. Assessing synaptic density in Alzheimer disease with synaptic vesicle glycoprotein 2A positron emission tomographic imaging JAMA Neurol. 2018 75 1215 1224 10.1001/jamaneurol.2018.1836 30014145 PMC6233853 · DOI · Paper page
  186. [206]Robinson J.L. Molina-Porcel L. Corrada M.M. Raible K. Lee E.B. Lee V.M. Kawas C.H. Trojanowski J.Q. Perforant path synaptic loss correlates with cognitive impairment and Alzheimer’s disease in the oldest-old Brain 2014 137 2578 2587 10.1093/brain/awu190 25012223 PMC4132652 · DOI · Paper page
  187. [207]Matuskey D. Tinaz S. Wilcox K.C. Naganawa M. Toyonaga T. Dias M. Henry S. Pittman B. Ropchan J. Nabulsi N. Synaptic changes in Parkinson disease assessed with in vivo imaging Ann. Neurol. 2020 87 329 338 10.1002/ana.25682 31953875 PMC7065227 · DOI
  188. [208]Finnema S.J. Nabulsi N.B. Eid T. Detyniecki K. Lin S.F. Chen M.K. Dhaher R. Matuskey D. Baum E. Holden D. Imaging synaptic density in the living human brain Sci. Transl. Med. 2016 8 348ra396 10.1126/scitranslmed.aaf6667 27440727 · DOI · Paper page
  189. [209]Holland N. Jones P.S. Savulich G. Hong Y.T. Fryer T.D. Manavaki R. Milicevic-Sephton S. Aigbirhio F. O’Brien J. Rowe J.B. 226 Reduced synaptic density in progressive supranuclear palsy and corticobasal syndrome, revealed by [11C]UCB-J PET J Neurol Neurosurg Psychiatry. 2022 93 A78.3-A78 10.1136/jnnp-2022-ABN.255 · DOI
  190. [210]Buchhave P. Minthon L. Zetterberg H. Wallin A.K. Blennow K. Hansson O. Cerebrospinal fluid levels of β-amyloid 1-42, but not of tau, are fully changed already 5 to 10 years before the onset of Alzheimer dementia Arch. Gen. Psychiatry 2012 69 98 106 10.1001/archgenpsychiatry.2011.155 22213792 · DOI · Paper page
  191. [211]Bentahir M. Nyabi O. Verhamme J. Tolia A. Horre K. Wiltfang J. Esselmann H. De Strooper B. Presenilin clinical mutations can affect gamma-secretase activity by different mechanisms J. Neurochem. 2006 96 732 742 10.1111/j.1471-4159.2005.03578.x 16405513 · DOI
  192. [212]Baldeiras I. Santana I. Leitao M.J. Gens H. Pascoal R. Tabuas-Pereira M. Beato-Coelho J. Duro D. Almeida M.R. Oliveira C.R. Addition of the aβ42/40 ratio to the cerebrospinal fluid biomarker profile increases the predictive value for underlying Alzheimer’s disease dementia in mild cognitive impairment Alzheimers Res. Ther. 2018 10 33 10.1186/s13195-018-0362-2 29558986 PMC5861634 · DOI
  193. [214]Jia L. Qiu Q. Zhang H. Chu L. Du Y. Zhang J. Zhou C. Liang F. Shi S. Wang S. Concordance between the assessment of aβ42, T-tau, and P-T181-tau in peripheral blood neuronal-derived exosomes and cerebrospinal fluid Alzheimers Dement. 2019 15 1071 1080 10.1016/j.jalz.2019.05.002 31422798 · DOI
  194. [215]Reitz C. Mayeux R. Alzheimer disease: Epidemiology, diagnostic criteria, risk factors and biomarkers Biochem. Pharmacol. 2014 88 640 651 10.1016/j.bcp.2013.12.024 24398425 PMC3992261 · DOI
  195. [216]Blennow K. Zetterberg H. Cerebrospinal fluid biomarkers for Alzheimer’s disease J. Alzheimers Dis. 2009 18 413 417 10.3233/JAD-2009-1177 19661632 · DOI
  196. [217]Shui B. Tao D. Florea A. Cheng J. Zhao Q. Gu Y. Li W. Jaffrezic-Renault N. Mei Y. Guo Z. Biosensors for Alzheimer’s disease biomarker detection: A review Biochimie 2018 147 13 24 10.1016/j.biochi.2017.12.015 29307704 · DOI
  197. [218]Visser P.J. Verhey F. Knol D.L. Scheltens P. Wahlund L.O. Freund-Levi Y. Tsolaki M. Minthon L. Wallin A.K. Hampel H. Prevalence and prognostic value of CSF markers of Alzheimer’s disease pathology in patients with subjective cognitive impairment or mild cognitive impairment in the descripa study: A prospective cohort study Lancet Neurol. 2009 8 619 627 10.1016/S1474-4422(09)70139-5 19523877 · DOI · Paper page
  198. [219]Suarez-Calvet M. Karikari T.K. Ashton N.J. Lantero Rodriguez J. Mila-Aloma M. Gispert J.D. Salvado G. Minguillon C. Fauria K. Shekari M. Novel tau biomarkers phosphorylated at T181, T217 or T231 rise in the initial stages of the preclinical Alzheimer’s continuum when only subtle changes in Aβ pathology are detected EMBO Mol. Med. 2020 12 e12921 10.15252/emmm.202012921 33169916 PMC7721364 · DOI · Paper page
  199. [220]Krance S.H. Cogo-Moreira H. Rabin J.S. Black S.E. Swardfager W. Alzheimer’s Disease Neuroimaging Initiative Reciprocal predictive relationships between amyloid and tau biomarkers in Alzheimer’s disease progression: An empirical model J. Neurosci. 2019 39 7428 7437 10.1523/JNEUROSCI.1056-19.2019 31350262 PMC6759020 · DOI
  200. [221]Kapogiannis D. Mustapic M. Shardell M.D. Berkowitz S.T. Diehl T.C. Spangler R.D. Tran J. Lazaropoulos M.P. Chawla S. Gulyani S. Association of extracellular vesicle biomarkers with Alzheimer disease in the Baltimore longitudinal study of aging JAMA Neurol. 2019 76 1340 1351 10.1001/jamaneurol.2019.2462 31305918 PMC6632160 · DOI · Paper page

200 of 282 shown

Authors
Ribarič, S.
Affiliations
University of Ljubljana (SI)
Corresponding author
Ribarič, Samo
ORCID
Ribarič, Samo
Venue
Biomedicines
Publisher
MDPI AG
Published
2023-01-26
Volume
11
Issue
2
Pages
355
ISSN
2227-9059 (ISSN-L)
DOI
10.3390/biomedicines11020355
PMC
PMC9952956
OpenAlex
W4318207623
Cited by
66
References
308
Citations by year
2026: 18 · 2025: 31 · 2024: 13 · 2023: 4
FWCI
3.01
Type
journal article
Language
en
Open access
Licence
Locations
  • Biomedicines (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Javna Agencija za Raziskovalno Dejavnost RS (P3-0171)
Topics
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
  • Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
Keywords
Alzheimer's disease, early cognitive decline, synaptic density, hippocampus, functional connectivity, large-scale brain networks, amyloid-beta, tau protein, biomarkers, mild cognitive impairment, default mode network, salience network, quantitative EEG, neuroimaging

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review