Cited by 39Alzheimer's disease research and treatmentsNeuroscience and Neuropharmacology ResearchNeural dynamics and brain function

Synaptic Plasticity and Oscillations in Alzheimer’s Disease: A Complex Picture of a Multifaceted Disease

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Andrade-Talavera, Yuniesky, Rodríguez-Moreno, Antonio·2021·Frontiers in Molecular Neuroscience

Abstract

Brain plasticity is widely accepted as the core neurophysiological basis of memory and is generally defined by activity-dependent changes in synaptic efficacy, such as long-term potentiation (LTP) and long-term depression (LTD). By using diverse induction protocols like high-frequency stimulation (HFS) or spike-timing dependent plasticity (STDP), such crucial cognition-relevant plastic processes are shown to be impaired in Alzheimer’s disease (AD). In AD, the severity of the cognitive impairment also correlates with the level of disruption of neuronal network dynamics. Currently under debate, the named amyloid hypothesis points to amyloid-beta peptide 1–42 (Aβ42) as the trigger of the functional deviations underlying cognitive impairment in AD. However, there are missing functional mechanistic data that comprehensively dissect the early subtle changes that lead to synaptic dysfunction and subsequent neuronal network collapse in AD. The convergence of the study of both, mechanisms underlying brain plasticity, and neuronal network dynamics, may represent the most efficient approach to address the early triggering and aberrant mechanisms underlying the progressive clinical cognitive impairment in AD. Here we comment on the emerging integrative roles of brain plasticity and network oscillations in AD research and on the future perspectives of research in this field.

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  • Early alterations in connectivity and plasticity, detectable through functional imaging or electrophysiological biomarkers, may precede clinical symptoms and represent a window of opportunity for intervention.

    “Moreover, early alterations in connectivity and plasticity, detectable through functional imaging or electrophysiological biomarkers, may precede clinical symptoms and represent a window of opportunity for intervention [86, 87].”

    From Toward a Unified Framework in Molecular Neurobiology of Alzheimer’s Disease: Revisiting the Pathophysiological Hypotheses (2026) · cites this paper as [87]

    The Introduction (page unavailable) says functional and network changes can precede cognitive deficits and argues for earlier intervention. The Discussion (page unavailable) describes EEG and TMS–EEG as ways to assess connectivity and plasticity, but the retrieved passages do not support detection through functional imaging. The Introduction also cautions that some forms of plasticity appear affected only at later stages. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

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  1. Andrade-Talavera Y. Arroyo-García L. E. Chen G. Johansson J. Fisahn A. (2020). Modulation of Kv3.1/Kv3.2 promotes gamma oscillations by rescuing Aβ-induced desynchronization of fast-spiking interneuron firing in an AD mouse model in vitro. J. Physiol. 598 3711– 3725. 10.1113/JP279718 32638407 · DOI
  2. Andrade-Talavera Y. Balleza-Tapia H. Dolz-Gaitón P. Chen G. Johansson J. Fisahn A. (2021). Ablation of p75NTR signaling strengthens gamma–theta rhythm interaction and counteracts Aβ-induced degradation of neuronal dynamics in mouse hippocampus in vitro. Transl. Psychiatry 11: 212. 10.1038/s41398-021-01332-8 33837176 PMC8035168 · DOI
  3. Andrade-Talavera Y. Duque-Feria P. Paulsen O. Rodríguez-Moreno A. (2016). Presynaptic spike timing-dependent long-term depression in the mouse hippocampus. Cereb. Cortex 26 3637– 3654. 10.1093/cercor/bhw172 27282393 PMC4961031 · DOI
  4. Bachiller S. Jiménez-Ferrer I. Paulus A. Yang Y. Swanberg M. Deierborg T. (2018). Microglia in neurological diseases: a road map to brain-disease dependent-inflammatory response. Front. Cell. Neurosci. 12: 488. 10.3389/fncel.2018.00488 30618635 PMC6305407 · DOI
  5. Bach-y-Rita P. (2003). Theoretical basis for brain plasticity after a TBI. Brain Inj. 17 643– 651. 10.1080/0269905031000107133 12850949 · DOI
  6. Bailey C. H. Kandel E. R. Harris K. M. (2015). Structural components of synaptic plasticity and memory consolidation. Cold Spring Harb. Perspect. Biol. 7: a021758. 10.1101/cshperspect.a021758 26134321 PMC4484970 · DOI
  7. Balleza-Tapia H. Crux S. Andrade-Talavera Y. Dolz-Gaiton P. Papadia D. Chen G. (2018). TrpV1 receptor activation rescues neuronal function and network gamma oscillations from Aβ-induced impairment in mouse hippocampus in vitro. Elife 7: e37703. 10.7554/elife.37703 30417826 PMC6281315 · DOI
  8. Banerjee A. González-Rueda A. Sampaio-Baptista C. Paulsen O. Rodríguez-Moreno A. (2014). Distinct mechanisms of spike timing-dependent LTD at vertical and horizontal inputs onto L2/3 pyramidal neurons in mouse barrel cortex. Physiol. Rep. 2: e00271. 10.1002/phy2.271 24760524 PMC4002250 · DOI
  9. Banerjee A. Meredith R. M. Rodríguez-Moreno A. Mierau S. B. Auberson Y. P. Paulsen O. (2009). Double dissociation of spike timing-dependent potentiation and depression by subunit-preferring NMDA receptor antagonists in mouse barrel cortex. Cereb. Cortex 19 2959– 2969. 10.1093/cercor/bhp067 19363149 PMC2774397 · DOI
  10. Başar E. (2013). A review of gamma oscillations in healthy subjects and in cognitive impairment. Int. J. Psychophysiol. 90 99– 117. 10.1016/j.ijpsycho.2013.07.005 23892065 · DOI
  11. Bender V. A. Bender K. J. Brasier D. J. Feldman D. E. (2006). Two coincidence detectors for spike timing-dependent plasticity in somatosensory cortex. J. Neurosci. 26 4166– 4177. 10.1523/JNEUROSCI.0176-06.2006 16624937 PMC3071735 · DOI
  12. Bliss T. V. P. Collingridge G. L. (1993). A synaptic model of memory: long-term potentiation in the hippocampus. Nature 361 31– 39. 10.1038/361031a0 8421494 · DOI · Paper page
  13. Bouvier G. Larsen R. S. Rodríguez-Moreno A. Paulsen O. Sjöström P. J. (2018). Towards resolving the presynaptic NMDA receptor debate. Curr. Opin. Neurobiol. 51 1– 7. 10.1016/j.conb.2017.12.020 29454833 · DOI
  14. Brasier D. J. Feldman D. E. (2008). Synapse-Specific expression of functional presynaptic NMDA receptors in rat somatosensory cortex. J. Neurosci. 28 2199– 2211. 10.1523/JNEUROSCI.3915-07.2008 18305253 PMC3071744 · DOI
  15. Buzsáki G. (2002). Theta oscillations in the hippocampus. Neuron 33 325– 340. 10.1016/S0896-6273(02)00586-X 11832222 · DOI · Paper page
  16. Buzsáki G. (2010). Neural syntax: cell assemblies, synapsembles, and readers. Neuron 68 362– 385. 10.1016/j.neuron.2010.09.023 21040841 PMC3005627 · DOI · Paper page
  17. Buzsáki G. (2011). Rythms of the Brain. New York, NY: Oxford University Press.
  18. Cajal S. R. (1894). The Croonian lecture.—La fine structure des centres nerveux. Proc. R. Soc. London 55 444– 468. 10.1098/rspl.1894.0063 · DOI
  19. Cardin J. A. Carlén M. Meletis K. Knoblich U. Zhang F. Deisseroth K. (2009). Driving fast-spiking cells induces gamma rhythm and controls sensory responses. Nature 459 663– 667. 10.1038/nature08002 19396156 PMC3655711 · DOI · Paper page
  20. Chen H. Epstein J. Stern E. (2010). Neural plasticity after acquired brain injury: evidence from functional neuroimaging. PM R 2 S306– S312. 10.1016/j.pmrj.2010.10.006 21172692 · DOI
  21. Crimins J. L. Rocher A. B. Luebke J. I. (2012). Electrophysiological changes precede morphological changes to frontal cortical pyramidal neurons in the rTg4510 mouse model of progressive tauopathy. Acta Neuropathol. 124 777– 795. 10.1007/s00401-012-1038-9 22976049 PMC3509230 · DOI
  22. Crouzin N. Baranger K. Cavalier M. Marchalant Y. Cohen-Solal C. Roman F. S. (2013). Area-Specific alterations of synaptic plasticity in the 5XFAD mouse model of Alzheimer’s disease: dissociation between somatosensory cortex and hippocampus. PLoS One 8: e74667. 10.1371/journal.pone.0074667 24069328 PMC3775744 · DOI
  23. Di Lorenzo F. Motta C. Bonnì S. Mercuri N. B. Caltagirone C. Martorana A. (2019). LTP-like cortical plasticity is associated with verbal memory impairment in Alzheimer’s disease patients. Brain Stimul. 12 148– 151. 10.1016/j.brs.2018.10.009 30352737 · DOI
  24. Di Lorenzo F. Motta C. Casula E. P. Bonnì S. Assogna M. Caltagirone C. (2020). LTP-like cortical plasticity predicts conversion to dementia in patients with memory impairment. Brain Stimul. 13 1175– 1182. 10.1016/j.brs.2020.05.013 32485235 · DOI
  25. Di Lorenzo F. Ponzo V. Bonnì S. Motta C. Negrão Serra P. C. Bozzali M. (2016). Long-term potentiation-like cortical plasticity is disrupted in Alzheimer’s disease patients independently from age of onset. Ann. Neurol. 80 202– 210. 10.1002/ana.24695 27255833 · DOI
  26. Di Lorenzo F. Ponzo V. Motta C. Bonnì S. Picazio S. Caltagirone C. (2018). Impaired spike timing dependent cortico-cortical plasticity in Alzheimer’s disease patients. J. Alzheimers Dis. 66 983– 991. 10.3233/JAD-180503 30372679 · DOI
  27. Etter G. van der Veldt S. Manseau F. Zarrinkoub I. Trillaud-Doppia E. Williams S. (2019). Optogenetic gamma stimulation rescues memory impairments in an Alzheimer’s disease mouse model. Nat. Commun. 10: 5322. 10.1038/s41467-019-13260-9 31757962 PMC6876640 · DOI
  28. Falcón-Moya R. Pérez-Rodríguez M. Prius-Mengual J. Andrade-Talavera Y. Arroyo-García L. E. Pérez-Artés R. (2020). Astrocyte-mediated switch in spike timing-dependent plasticity during hippocampal development. Nat. Commun. 11: 4388. 10.1038/s41467-020-18024-4 32873805 PMC7463247 · DOI
  29. Feldman D. E. (2012). The spike-timing dependence of plasticity. Neuron 75 556– 571. 10.1016/j.neuron.2012.08.001 22920249 PMC3431193 · DOI · Paper page
  30. Fisahn A. Pike F. G. Buhl E. H. Paulsen O. (1998). Cholinergic induction of network oscillations at 40 Hz in the hippocampus in vitro. Nature 394 186– 189. 10.1038/28179 9671302 · DOI · Paper page
  31. Frere S. Slutsky I. (2018). Alzheimer’s disease: from firing instability to homeostasis network collapse. Neuron 97 32– 58. 10.1016/j.neuron.2017.11.028 29301104 · DOI
  32. Fries P. Nikolić D. Singer W. (2007). The gamma cycle. Trends Neurosci. 30 309– 316. 10.1016/j.tins.2007.05.005 17555828 · DOI · Paper page
  33. Garad M. Edelmann E. Leßmann V. (2021). Impairment of spike-timing-dependent plasticity at schaffer collateral-CA1 synapses in adult APP/PS1 mice depends on proximity of Aβ plaques. Int. J. Mol. Sci. 22: 1378. 10.3390/ijms22031378 33573114 PMC7866519 · DOI
  34. Görtz P. Opatz J. Siebler M. Funke S. A. Willbold D. Lange-Asschenfeldt C. (2009). Transient reduction of spontaneous neuronal network activity by sublethal amyloid β (1–42) peptide concentrations. J. Neural Transm. 116 351– 355. 10.1007/s00702-009-0188-y 19214376 · DOI
  35. Goutagny R. Gu N. Cavanagh C. Jackson J. Chabot J. G. Quirion R. (2013). Alterations in hippocampal network oscillations and theta-gamma coupling arise before Aβ overproduction in a mouse model of Alzheimer’s disease. Eur. J. Neurosci. 37 1896– 1902. 10.1111/ejn.12233 23773058 · DOI
  36. Goutagny R. Jackson J. Williams S. (2009). Self-generated theta oscillations in the hippocampus. Nat. Neurosci. 12 1491– 1493. 10.1038/nn.2440 19881503 · DOI · Paper page
  37. Gu Z. Yakel J. L. (2011). Timing-dependent septal cholinergic induction of dynamic hippocampal synaptic plasticity. Neuron 71 155– 165. 10.1016/j.neuron.2011.04.026 21745645 PMC3134790 · DOI
  38. Guillon J. Attal Y. Colliot O. La Corte V. Dubois B. Schwartz D. (2017). Loss of brain inter-frequency hubs in Alzheimer’s disease. Sci. Rep. 7: 10879. 10.1038/s41598-017-07846-w 28883408 PMC5589939 · DOI
  39. Hamilton H. K. Roach B. J. Cavus I. Teyler T. J. Clapp W. C. Ford J. M. (2020). Impaired potentiation of theta oscillations during a visual cortical plasticity paradigm in individuals with schizophrenia. Front. Psychiatry 11: 590567. 10.3389/fpsyt.2020.590567 33391054 PMC7772351 · DOI
  40. Hanson J. E. Ma K. Elstrott J. Weber M. Saillet S. Khan A. S. (2020). GluN2A NMDA receptor enhancement improves brain oscillations, synchrony, and cognitive functions in dravet syndrome and Alzheimer’s disease models. Cell Rep. 30 381– 396.e4. 10.1016/j.celrep.2019.12.030 31940483 PMC7017907 · DOI
  41. Hebb D. (1949). The Organization of Behavior. A Neuropsychological Theory. New York, NY: John Wiley.
  42. Hill N. L. Kolanowski A. M. Gill D. J. (2011). Plasticity in early Alzheimer’s disease: an opportunity for intervention. Top. Geriatr. Rehabil. 27 257– 267. 10.1097/tgr.0b013e31821e588e 22904596 PMC3419487 · DOI
  43. Holtzman D. M. Carrillo M. C. Hendrix J. A. Bain L. J. Catafau A. M. Gault L. M. (2016). Tau: from research to clinical development. Alzheimers Dement. 12 1033– 1039. 10.1016/j.jalz.2016.03.018 27154059 · DOI · Paper page
  44. Hoover B. R. Reed M. N. Su J. Penrod R. D. Kotilinek L. A. Grant M. K. (2010). Tau mislocalization to dendritic spines mediates synaptic dysfunction independently of neurodegeneration. Neuron 68 1067– 1081. 10.1016/j.neuron.2010.11.030 21172610 PMC3026458 · DOI · Paper page
  45. Hyman B. T. (2011). Amyloid-Dependent and amyloid-independent stages of Alzheimer disease. Arch. Neurol. 68: 1062. 10.1001/archneurol.2011.70 21482918 · DOI
  46. Isla A. G. Balleza-Tapia H. Fisahn A. (2021). Efficacy of preclinical pharmacological interventions against alterations of neuronal network oscillations in Alzheimer’s disease: a systematic review. Exp. Neurol. 113743. 10.1016/j.expneurol.2021.113743 34000250 · DOI
  47. Joseph D. J. Liu C. Peng J. Liang G. Wei H. (2019). Isoflurane mediated neuropathological and cognitive impairments in the triple transgenic Alzheimer’s mouse model are associated with hippocampal synaptic deficits in an age-dependent manner. PLoS One 14: e0223509. 10.1371/journal.pone.0223509 31600350 PMC6786564 · DOI
  48. Kalweit A. N. Yang H. Colitti-Klausnitzer J. Fülöp L. Bozsó Z. Penke B. (2015). Acute intracerebral treatment with amyloid-beta (1–42) alters the profile of neuronal oscillations that accompany LTP induction and results in impaired LTP in freely behaving rats. Front. Behav. Neurosci. 9: 103. 10.3389/fnbeh.2015.00103 25999827 PMC4422036 · DOI
  49. Karran E. De Strooper B. (2016). The amyloid cascade hypothesis: are we poised for success or failure? J. Neurochem. 139 237– 252. 10.1111/jnc.13632 27255958 · DOI · Paper page
  50. Kimura R. Devi L. Ohno M. (2010). Partial reduction of BACE1 improves synaptic plasticity, recent and remote memories in Alzheimer’s disease transgenic mice. J. Neurochem. 113 248– 261. 10.1111/j.1471-4159.2010.06608.x 20089133 PMC2921968 · DOI
  51. Koch G. Esposito Z. Kusayanagi H. Monteleone F. Codecá C. Di Lorenzo F. (2011). CSF Tau levels influence cortical plasticity in Alzheimer’s disease patients. J. Alzheimers Dis. 26 181– 186. 10.3233/JAD-2011-110116 21606570 · DOI
  52. Kumar A. (2011). Long-Term potentiation at CA3-CA1 hippocampal synapses with special emphasis on aging, disease, and stress. Front. Aging Neurosci. 3: 7. 10.3389/fnagi.2011.00007 21647396 PMC3102214 · DOI
  53. Kurudenkandy F. R. R. Zilberter M. Biverstal H. Presto J. Honcharenko D. Stromberg R. (2014). Amyloid-beta -Induced action potential desynchronization and degradation of hippocampal gamma oscillations is prevented by interference with peptide conformation change and aggregation. J. Neurosci. 34 11416– 11425. 10.1523/jneurosci.1195-14.2014 25143621 PMC6615507 · DOI
  54. Kwag J. Paulsen O. (2009). The timing of external input controls the sign of plasticity at local synapses. Nat. Neurosci. 12 1219– 1221. 10.1038/nn.2388 19734896 · DOI
  55. Larson J. Lynch G. (1989). Theta pattern stimulation and the induction of LTP: the sequence in which synapses are stimulated determines the degree to which they potentiate. Brain Res. 489 49– 58. 10.1016/0006-8993(89)90007-3 2743153 · DOI
  56. Latif-Hernandez A. Sabanov V. Ahmed T. Craessaerts K. Saito T. Saido T. (2020). The two faces of synaptic failure in AppNL-G-F knock-in mice. Alzheimers Res. Ther. 12: 100. 10.1186/s13195-020-00667-6 32838792 PMC7445922 · DOI
  57. Law C. S. H. Leung L. S. (2018). Long-Term potentiation and excitability in the hippocampus are modulated differently by θ rhythm. eNeuro 5: ENEURO.0236-18.2018. PMC6325566 30627662
  58. Leão R. N. Colom L. V. Borgius L. Kiehn O. Fisahn A. (2012). Medial septal dysfunction by Aβ-induced KCNQ channel-block in glutamatergic neurons. Neurobiol. Aging 33 2046– 2061. 10.1016/j.neurobiolaging.2011.07.013 21907458 · DOI
  59. Li S. Jin M. Koeglsperger T. Shepardson N. E. Shankar G. M. Selkoe D. J. (2011). Soluble a oligomers inhibit long-term potentiation through a mechanism involving excessive activation of extrasynaptic NR2B-Containing NMDA receptors. J. Neurosci. 31 6627– 6638. 10.1523/JNEUROSCI.0203-11.2011 21543591 PMC3100898 · DOI
  60. Lourenço J. De Stasi A. M. Deleuze C. Bigot M. Pazienti A. Aguirre A. (2020). Modulation of coordinated activity across cortical layers by plasticity of inhibitory synapses. Cell Rep. 30 630– 641.e5. 31968242 PMC6988114
  61. Luo Y. Sun Y. Tian X. Zheng X. Wang X. Li W. (2021). Deep brain stimulation for Alzheimer’s disease: stimulation parameters and potential mechanisms of action. Front. Aging Neurosci. 13: 619543. 10.3389/fnagi.2021.619543 33776742 PMC7990787 · DOI
  62. Markram H. Gerstner W. Sjöström P. J. (2012). Spike-Timing-Dependent plasticity: a comprehensive overview. Front. Synaptic Neurosci. 4: 2. 10.3389/fnsyn.2012.00002 22807913 PMC3395004 · DOI
  63. McBain C. J. Fisahn A. (2001). Interneurons unbound. Nat. Rev. Neurosci. 2 11– 23. 10.1038/35049047 11253355 · DOI · Paper page
  64. Mederos S. González-Arias C. Perea G. (2018). Astrocyte–Neuron networks: a multilane highway of signaling for homeostatic brain function. Front. Synaptic Neurosci. 10: 45. 10.3389/fnsyn.2018.00045 30542276 PMC6277918 · DOI
  65. Mondragón-Rodríguez S. Gu N. Fasano C. Peña-Ortega F. Williams S. (2019). Functional connectivity between hippocampus and lateral septum is affected in very young Alzheimer’s transgenic mouse model. Neuroscience 401 96– 105. 10.1016/j.neuroscience.2018.12.042 30599271 · DOI
  66. Mondragón-Rodríguez S. Gu N. Manseau F. Williams S. (2018). Alzheimer’s transgenic model is characterized by very early brain network alterations and β-CTF fragment accumulation: reversal by β-Secretase inhibition. Front. Cell. Neurosci. 12: 121. 10.3389/fncel.2018.00121 29867356 PMC5952042 · DOI
  67. Mondragón-Rodríguez S. Perry G. Pena-Ortega F. Williams S. (2016). Tau, amyloid beta and deep brain stimulation: aiming to restore cognitive deficit in Alzheimer’s disease. Curr. Alzheimer Res. 14 40– 46. 10.2174/1567205013666160819131336 27539594 · DOI
  68. Mucke L. Selkoe D. J. (2012). Neurotoxicity of amyloid β-protein: synaptic and network dysfunction. Cold Spring Harb. Perspect. Med. 2: a006338. 10.1101/cshperspect.a006338 22762015 PMC3385944 · DOI · Paper page
  69. Nardone R. Sebastianelli L. Versace V. Ferrazzoli D. Saltuari L. Trinka E. (2021). TMS–EEG co-registration in patients with mild cognitive impairment, Alzheimer’s disease and other dementias: a systematic review. Brain Sci. 11: 303. 10.3390/brainsci11030303 33673709 PMC7997266 · DOI
  70. Navarrete M. Cuartero M. I. Palenzuela R. Draffin J. E. Konomi A. Serra I. (2019). Astrocytic p38α MAPK drives NMDA receptor-dependent long-term depression and modulates long-term memory. Nat. Commun. 10: 2968. 10.1038/s41467-019-10830-9 31273206 PMC6609681 · DOI
  71. Palmeri A. Ricciarelli R. Gulisano W. Rivera D. Rebosio C. Calcagno E. (2017). Amyloid-β peptide is needed for cGMP-Induced long-term potentiation and memory. J. Neurosci. 37 6926– 6937. 10.1523/JNEUROSCI.3607-16.2017 28626017 PMC5518421 · DOI
  72. Palop J. J. Chin J. Roberson E. D. Wang J. Thwin M. T. Bien-Ly N. (2007). Aberrant excitatory neuronal activity and compensatory remodeling of inhibitory hippocampal circuits in mouse models of Alzheimer’s disease. Neuron 55 697– 711. 10.1016/j.neuron.2007.07.025 17785178 PMC8055171 · DOI · Paper page
  73. Park K. Lee J. Jang H. J. Richards B. A. Kohl M. M. Kwag J. (2020). Optogenetic activation of parvalbumin and somatostatin interneurons selectively restores theta-nested gamma oscillations and oscillation-induced spike timing-dependent long-term potentiation impaired by amyloid β oligomers. BMC Biol. 18: 7. 10.1186/s12915-019-0732-7 31937327 PMC6961381 · DOI
  74. Peña-Ortega F. (2013). Amyloid beta-protein and neural network dysfunction. J. Neurodegener. Dis. 2013 657470. 10.1155/2013/657470 26316994 PMC4437331 · DOI
  75. Pena-Ortega F. Solis-Cisneros A. Ordaz B. Balleza-Tapia H. Javier Lopez-Guerrero J. (2012). Amyloid Beta 1-42 inhibits entorhinal cortex activity in the beta-gamma range: role of GSK-3. Curr. Alzheimer Res. 9 857– 863. 10.2174/156720512802455403 22631612 · DOI
  76. Perea G. Gómez R. Mederos S. Covelo A. Ballesteros J. J. Schlosser L. (2016). Activity-dependent switch of GABAergic inhibition into glutamatergic excitation in astrocyte-neuron networks. Elife 5: e20362. 10.7554/eLife.20362 28012274 PMC5231406 · DOI · Paper page
  77. Pérez-Otaño I. Rodríguez-Moreno A. (2019). Presynaptic NMDARs and astrocytes ally to control circuit-specific information flow. Proc. Natl. Acad. Sci. U.S.A. 116 13166– 13168. 10.1073/pnas.1908293116 31201220 PMC6613104 · DOI
  78. Pérez-Rodríguez M. Arroyo-García L. E. Prius-Mengual J. Andrade-Talavera Y. Armengol J. A. Pérez-Villegas E. M. (2019). Adenosine receptor-mediated developmental loss of spike timing-dependent depression in the hippocampus. Cereb. Cortex 29 3266– 3281. 10.1093/cercor/bhy194 30169759 PMC6644873 · DOI
  79. Pernelle G. Nicola W. Clopath C. (2018). Gap junction plasticity as a mechanism to regulate network-wide oscillations. PLoS Comput. Biol. 14: e1006025. 10.1371/journal.pcbi.1006025 29529034 PMC5864095 · DOI
  80. Rammes G. Mattusch C. Wulff M. Seeser F. Kreuzer M. Zhu K. (2017). Involvement of GluN2B subunit containing N-methyl- d -aspartate (n.d.) receptors in mediating the acute and chronic synaptotoxic effects of oligomeric amyloid-beta (Aβ) in murine models of Alzheimer’s disease (AD). Neuropharmacology 123 100– 115. 10.1016/j.neuropharm.2017.02.003 28174113 · DOI
  81. Rawji V. Latorre A. Sharma N. Rothwell J. C. Rocchi L. (2020). On the use of TMS to investigate the pathophysiology of neurodegenerative diseases. Front. Neurol. 11: 584664. 10.3389/fneur.2020.584664 33224098 PMC7669623 · DOI
  82. Rodríguez-Moreno A. Paulsen O. (2008). Spike timing-dependent long-term depression requires presynaptic NMDA receptors. Nat. Neurosci. 11 744– 745. 10.1038/nn.2125 18516036 · DOI
  83. Rodríguez-Moreno A. Banerjje A. Paulsen O. (2010). Presynaptic NMDA receptors and spike timing-dependent depression at cortical synapses. Front. Synaptic Neurosci. 2: 18. 10.3389/fnsyn.2010.00018 21423504 PMC3059699 · DOI
  84. Rodríguez-Moreno A. González-Rueda A. Banerjee A. Upton A. L. Craig M. T. Paulsen O. (2013). Presynaptic self-depression at developing neocortical synapses. Neuron 77 35– 42. 10.1016/j.neuron.2012.10.035 23312514 PMC3542421 · DOI
  85. Rodriguez-Moreno A. Kohl M. M. Reeve J. E. Eaton T. R. Collins H. A. Anderson H. L. (2011). Presynaptic induction and expression of timing-dependent long-term depression demonstrated by compartment-specific photorelease of a use-dependent NMDA receptor antagonist. J. Neurosci. 31 8564– 8569. 10.1523/JNEUROSCI.0274-11.2011 21653860 PMC4299820 · DOI
  86. Samidurai M. Ramasamy V. S. Jo J. (2018). β-amyloid inhibits hippocampal LTP through TNFR/IKK/NF-κB pathway. Neurol. Res. 40 268– 276. 10.1080/01616412.2018.1436872 29458298 · DOI
  87. Sandvig I. Augestad I. L. Håberg A. K. Sandvig A. (2018). Neuroplasticity in stroke recovery. The role of microglia in engaging and modifying synapses and networks. Eur. J. Neurosci. 47 1414– 1428. 10.1111/ejn.13959 29786167 · DOI · Paper page
  88. Sasaguri H. Nilsson P. Hashimoto S. Nagata K. Saito T. De Strooper B. (2017). APP mouse models for Alzheimer’s disease preclinical studies. EMBO J. 36 2473– 2487. 10.15252/embj.201797397 28768718 PMC5579350 · DOI · Paper page
  89. Selkoe D. J. (2002). Alzheimer’s disease is a synaptic failure. Science 298 789– 791. 10.1126/science.1074069 12399581 · DOI · Paper page
  90. Selkoe D. J. Hardy J. (2016). The amyloid hypothesis of Alzheimer’s disease at 25 years. EMBO Mol. Med. 8 595– 608. 10.15252/emmm.201606210 27025652 PMC4888851 · DOI · Paper page
  91. Shankar G. M. Li S. Mehta T. H. Garcia-Munoz A. Shepardson N. E. Smith I. (2008). Amyloid-β protein dimers isolated directly from Alzheimer’s brains impair synaptic plasticity and memory. Nat. Med. 14 837– 842. 10.1038/nm1782 18568035 PMC2772133 · DOI · Paper page
  92. Shemer I. Holmgren C. Min R. Fülöp L. Zilberter M. Sousa K. M. (2006). Non-fibrillar β-amyloid abates spike-timing-dependent synaptic potentiation at excitatory synapses in layer 2/3 of the neocortex by targeting postsynaptic AMPA receptors. Eur. J. Neurosci. 23 2035– 2047. 10.1111/j.1460-9568.2006.04733.x 16630051 · DOI
  93. Stam C. J. van Cappellen van Walsum A. M. Pijnenburg Y. A. L. Berendse H. W. de Munck J. C. Scheltens P. (2002). Generalized synchronization of MEG recordings in Alzheimer’s Disease: evidence for involvement of the gamma band. J. Clin. Neurophysiol. 19 562– 574. 10.1097/00004691-200212000-00010 12488788 · DOI
  94. Stoiljkovic M. Kelley C. Horvath T. L. Hajós M. (2018). Neurophysiological signals as predictive translational biomarkers for Alzheimer’s disease treatment: effects of donepezil on neuronal network oscillations in TgF344-AD rats. Alzheimers Res. Ther. 10: 105. 10.1186/s13195-018-0433-4 30301466 PMC6178257 · DOI
  95. Szepesi Z. Manouchehrian O. Bachiller S. Deierborg T. (2018). Bidirectional microglia-neuron communication in health and disease. Front. Cell. Neurosci. 12: 323. 10.3389/fncel.2018.00323 30319362 PMC6170615 · DOI · Paper page
  96. Terry A. V. Buccafusco J. J. (2003). The cholinergic hypothesis of age and Alzheimer’s disease-related cognitive deficits: recent challenges and their implications for novel drug development. J. Pharmacol. Exp. Ther. 306 821– 827. 10.1124/jpet.102.041616 12805474 · DOI · Paper page
  97. Tolar M. Abushakra S. Sabbagh M. (2020). The path forward in Alzheimer’s disease therapeutics: reevaluating the amyloid cascade hypothesis. Alzheimers Dement. 16 1553– 1560. 10.1016/j.jalz.2019.09.075 31706733 · DOI · Paper page
  98. Verret L. Mann E. O. Hang G. B. Barth A. M. I. Cobos I. Ho K. (2012). Inhibitory interneuron deficit links altered network activity and cognitive dysfunction in alzheimer model. Cell 149 708– 721. 10.1016/j.cell.2012.02.046 22541439 PMC3375906 · DOI · Paper page
  99. Walsh D. M. Klyubin I. Fadeeva J. V. Cullen W. K. Anwyl R. Wolfe M. S. (2002). Naturally secreted oligomers of amyloid β protein potently inhibit hippocampal long-term potentiation in vivo. Nature 416 535– 539. 10.1038/416535a 11932745 · DOI · Paper page
  100. Wang Y. Zhang G. Zhou H. Barakat A. Querfurth H. (2009). Opposite effects of low and high doses of Aβ42 on electrical network and neuronal excitability in the rat prefrontal cortex. PLoS One 4: e8366. 10.1371/journal.pone.0008366 20027222 PMC2791225 · DOI
  101. Yener G. G. Başar E. (2013). “ Biomarkers in Alzheimer’s disease with a special emphasis on event-related oscillatory responses,” in Supplements to Clinical neurophysiology, eds Başar E. Başar-Eroglu C. Özerdem A. Rossini P. M. Yener G. G. (Amsterdam: Elsevier), 237– 273. 10.1016/B978-0-7020-5307-8.00020-X 24053044 · DOI
  102. Zhang H. Zhang L. Zhou D. He X. Wang D. Pan H. (2017). Ablating ErbB4 in PV neurons attenuates synaptic and cognitive deficits in an animal model of Alzheimer’s disease. Neurobiol. Dis. 106 171– 180. 10.1016/j.nbd.2017.07.001 28684271 · DOI

Cited by

Sorted by citations

Authors
Andrade-Talavera, Y., & Rodríguez-Moreno, A.
Venue
Frontiers in Molecular Neuroscience
Published
2021-06-17
Volume
14
Pages
696476-696476
ISSN
1662-5099 (ISSN-L)
OpenAlex
W3174400192
Cited by
39
References
9
Citations by year
2026: 6 · 2025: 10 · 2024: 11 · 2023: 4 · 2022: 7 · 2021: 1
FWCI
3.52
Type
journal article
Language
en
Open access
Locations
  • Frontiers in Molecular Neuroscience (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • RIO (Universidad Pablo de Olavide) (submittedVersion, cc-by-nc-nd)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Ministerio de Economía, Industria y Competitividad, Gobierno de España
Topics
  • Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
Keywords
Alzheimer's disease, synaptic plasticity, neuronal network oscillations, long-term potentiation, long-term depression, spike-timing-dependent plasticity, high-frequency stimulation, amyloid-beta, amyloid-beta 42, neuronal network dynamics, cognitive impairment, synaptic dysfunction

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