open access

Vol 77, No 2 (2018)
Original article
Submitted: 2018-04-17
Accepted: 2018-04-23
Published online: 2018-05-09
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A computational simulation of long-term synaptic potentiation inducing protocol processes with model of CA3 hippocampal microcircuit

D. Świetlik1, J. Białowąs, A. Kusiak, D. Cichońska2
·
Pubmed: 29802713
·
Folia Morphol 2018;77(2):210-220.
Affiliations
  1. Intrafaculty College of Medical Informatics and Biostatistics, Medical University of Gdańsk, 1 Debinki St., 80-211 Gdańsk, Poland
  2. Department of Periodontology and Oral Mucosa Diseases, Medical Univerity of Gdańsk, Poland

open access

Vol 77, No 2 (2018)
ORIGINAL ARTICLES
Submitted: 2018-04-17
Accepted: 2018-04-23
Published online: 2018-05-09

Abstract

An experimental study of computational model of the CA3 region presents cog­nitive and behavioural functions the hippocampus. The main property of the CA3 region is plastic recurrent connectivity, where the connections allow it to behave as an auto-associative memory. The computer simulations showed that CA3 model performs efficient long-term synaptic potentiation (LTP) induction and high rate of sub-millisecond coincidence detection. Average frequency of the CA3 pyramidal cells model was substantially higher in simulations with LTP induction protocol than without the LTP. The entropy of pyramidal cells with LTP seemed to be significantly higher than without LTP induction protocol (p = 0.0001). There was depression of entropy, which was caused by an increase of forgetting coefficient in pyramidal cells simulations without LTP (R = –0.88, p = 0.0008), whereas such correlation did not appear in LTP simulation (p = 0.4458). Our model of CA3 hippocampal formation microcircuit biologically inspired lets you understand neurophysiologic data. (Folia Morphol 2018; 77, 2: 210–220)

Abstract

An experimental study of computational model of the CA3 region presents cog­nitive and behavioural functions the hippocampus. The main property of the CA3 region is plastic recurrent connectivity, where the connections allow it to behave as an auto-associative memory. The computer simulations showed that CA3 model performs efficient long-term synaptic potentiation (LTP) induction and high rate of sub-millisecond coincidence detection. Average frequency of the CA3 pyramidal cells model was substantially higher in simulations with LTP induction protocol than without the LTP. The entropy of pyramidal cells with LTP seemed to be significantly higher than without LTP induction protocol (p = 0.0001). There was depression of entropy, which was caused by an increase of forgetting coefficient in pyramidal cells simulations without LTP (R = –0.88, p = 0.0008), whereas such correlation did not appear in LTP simulation (p = 0.4458). Our model of CA3 hippocampal formation microcircuit biologically inspired lets you understand neurophysiologic data. (Folia Morphol 2018; 77, 2: 210–220)

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Keywords

learning and memory, hippocampus, long-term synaptic potentiation, forgetting, theta rhythm, computer simulation

About this article
Title

A computational simulation of long-term synaptic potentiation inducing protocol processes with model of CA3 hippocampal microcircuit

Journal

Folia Morphologica

Issue

Vol 77, No 2 (2018)

Article type

Original article

Pages

210-220

Published online

2018-05-09

Page views

1475

Article views/downloads

1250

DOI

10.5603/FM.a2018.0042

Pubmed

29802713

Bibliographic record

Folia Morphol 2018;77(2):210-220.

Keywords

learning and memory
hippocampus
long-term synaptic potentiation
forgetting
theta rhythm
computer simulation

Authors

D. Świetlik
J. Białowąs
A. Kusiak
D. Cichońska

References (57)
  1. Andersen P, Morris R, Amaral R, et al. The Hippocampus Book. 2009.
  2. Aradi I, Holmes WR. Role of multiple calcium and calcium-dependent conductances in regulation of hippocampal dentate granule cell excitability. J Comput Neurosci. 1999; 6(3): 215–235.
  3. Arleo A, Gerstner W. Spatial cognition and neuro-mimetic navigation: a model of hippocampal place cell activity. Biol Cybern. 2000; 83(3): 287–299.
  4. Babinec P, Kučera M, Babincová M. Global characterization of time series using fractal dimension of corresponding recurrence plots: from dynamical systems to heart physiology. Harmon Fractal Image Anal. 2005; 1: 87–93.
  5. Bienenstock EL, Cooper LN, Munro PW. Theory for the development of neuron selectivity: orientation specificity and binocular interaction in visual cortex. J Neurosci. 1982; 2(1): 32–48.
  6. Bliss T, Lømo T. Long-lasting potentiation of synaptic transmission in the dentate area of the anaesthetized rabbit following stimulation of the perforant path. J Physiol. 1973; 232(2): 331–356.
  7. Boss B, Turlejski K, Stanfield B, et al. On the numbers of neurons on fields CA1 and CA3 of the hippocampus of Sprague-Dawley and Wistar rats. Brain Research. 1987; 406(1-2): 280–287.
  8. Bragin A, Jandó G, Nádasdy Z, et al. Gamma (40-100 Hz) oscillation in the hippocampus of the behaving rat. J Neurosci. 1995; 15(1 Pt 1): 47–60.
  9. Brunel N, Trullier O. Plasticity of directional place fields in a model of rodent CA3. Hippocampus. 1998; 8(6): 651–665.
  10. Buzsáki G, Leung LW, Vanderwolf CH. Cellular bases of hippocampal EEG in the behaving rat. Brain Res Rev. 1983; 287(2): 139–171.
  11. Buzsáki G. Two-stage model of memory trace formation: A role for “noisy” brain states. Neuroscience. 1989; 31(3): 551–570.
  12. Buzsáki G. Theta Oscillations in the Hippocampus. Neuron. 2002; 33(3): 325–340.
  13. Cannon R, Hasselmo M, Koene R. From Biophysics to Behavior Catacomb2 and the Design of Biologically-Plausible Models for Spatial Navigation. Neuroinformatics. 2003; 1(1): 003–042.
  14. Cutsuridis V, Graham B, Cobb SR, et al. Hippocampal Microcircuits: A Computational Modelers’ Resource Book. 2010.
  15. Hasselmo ME, Schnell E, Barkai E. Dynamics of learning and recall at excitatory recurrent synapses and cholinergic modulation in rat hippocampal region CA3. J Neurosci. 1995; 15(7 Pt 2): 5249–5262.
  16. Huerta PT, Lisman JE. Heightened synaptic plasticity of hippocampal CA1 neurons during a cholinergically induced rhythmic state. Nature. 1993; 364(6439): 723–725.
  17. Jackson MB. Recall of spatial patterns stored in a hippocampal slice by long-term potentiation. J Neurophysiol. 2013; 110(11): 2511–2519.
  18. Káli S, Dayan P. The involvement of recurrent connections in area CA3 in establishing the properties of place fields: a model. J Neurosci. 2000; 20(19): 7463–7477.
  19. Klausberger T, Magill PJ, Márton LF, et al. Brain-state- and cell-type-specific firing of hippocampal interneurons in vivo. Nature. 2003; 421(6925): 844–848.
  20. Klausberger T, Somogyi P. Neuronal diversity and temporal dynamics: the unity of hippocampal circuit operations. Science. 2008; 321(5885): 53–57.
  21. Llorens-Martín M, Blazquez-Llorca L, Benavides-Piccione R, et al. Selective alterations of neurons and circuits related to early memory loss in Alzheimer’s disease. Frontiers Neuroanat. 2014; 8.
  22. Lynch MA. Long-term potentiation and memory. Physiol Rev. 2004; 84(1): 87–136.
  23. Marr D. Simple Memory: A Theory for Archicortex. Philos Trans R Soc B Biol Sci. 1971; 262(841): 23–81.
  24. McClelland JL, Goddard NH. Considerations arising from a complementary learning systems perspective on hippocampus and neocortex. Hippocampus. 1996; 6(6): 654–665.
  25. Migliore M, Cook EP, Jaffe DB, et al. Computer simulations of morphologically reconstructed CA3 hippocampal neurons. J Neurophysiol. 1995; 73(3): 1157–1168.
  26. Misják F, Lengyel M, Érdi P. Episodic Memory and Cognitive Map in a Rate Model Network of the Rat Hippocampus. Lecture Notes in Computer Science. 2001: 1135–1140.
  27. Mizuseki K, Sirota A, Pastalkova E, et al. Theta oscillations provide temporal windows for local circuit computation in the entorhinal-hippocampal loop. Neuron. 2009; 64(2): 267–280.
  28. Morris RGM. Does synaptic plasticity play a role in information storage in the vertebrate brain? In R. G. M. Morris (Ed.), Parallel distributed processing: Implications for psychology and neurobiology. New York, NY, US: Clarendon Press/Oxford University Press. 1989: 248–285.
  29. Morris RGM, Moser EI, Riedel G, et al. Elements of a neurobiological theory of the hippocampus: the role of activity-dependent synaptic plasticity in memory. Philos Trans R Soc Lond B Biol Sci. 2003; 358(1432): 773–786.
  30. Morris RGM. Long-term potentiation and memory. Philos Trans R Soc Lond B Biol Sci. 2003; 358(1432): 643–647.
  31. Nakazawa K, Quirk MC, Chitwood RA, et al. Requirement for hippocampal CA3 NMDA receptors in associative memory recall. Science. 2002; 297(5579): 211–218.
  32. Nakazawa K, Sun L, Quirk M, et al. Hippocampal CA3 NMDA Receptors Are Crucial for Memory Acquisition of One-Time Experience. Neuron. 2003; 38(2): 305–315.
  33. Nakazawa K, McHugh TJ, Wilson MA, et al. NMDA receptors, place cells and hippocampal spatial memory. Nat Rev Neurosci. 2004; 5(5): 361–372.
  34. O'Keefe J, Recce ML. Phase relationship between hippocampal place units and the EEG theta rhythm. Hippocampus. 1993; 3(3): 317–330.
  35. O'Reilly RC, McClelland JL. Hippocampal conjunctive encoding, storage, and recall: avoiding a trade-off. Hippocampus. 1994; 4(6): 661–682.
  36. Poirazi P, Brannon T, Mel B. Arithmetic of subthreshold synaptic summation in a model CA1 pyramidal cell. Neuron. 2003; 37(6): 977–987.
  37. Poirazi P, Brannon T, Mel BW. Pyramidal neuron as two-layer neural network. Neuron. 2003; 37(6): 989–999.
  38. Rolls ET, Stringer SM, Trappenberg TP. A unified model of spatial and episodic memory. Proc Biol Sci. 2002; 269(1496): 1087–1093.
  39. Rolls E. Cerebral Cortex. Principles of Operation. Oxford University Press, Oxford. 2016.
  40. Rolls ET. Pattern separation, completion, and categorisation in the hippocampus and neocortex. Neurobiol Learn Mem. 2016; 129: 4–28.
  41. Samsonovich AV. A simple neural network model of the hippocampus suggesting its pathfinding role in episodic memory retrieval. Learn Mem. 2005; 12(2): 193–208.
  42. Santhakumar V, Aradi I, Soltesz I. Role of mossy fiber sprouting and mossy cell loss in hyperexcitability: a network model of the dentate gyrus incorporating cell types and axonal topography. J Neurophysiol. 2005; 93(1): 437–453.
  43. Saraga F, Wu CP, Zhang L, et al. Active dendrites and spike propagation in multicompartment models of oriens-lacunosum/moleculare hippocampal interneurons. J Physiol. 2004; 552(3): 673–689.
  44. Shastri L. Episodic memory and cortico–hippocampal interactions. Trends Cogn Sci. 2002; 6(4): 162–168.
  45. Sikora MA, Gottesman J, Miller RF. A computational model of the ribbon synapse. J Neurosci Methods. 2005; 145(1-2): 47–61.
  46. Skaggs W, McNaughton B, Wilson M, et al. Theta phase precession in hippocampal neuronal populations and the compression of temporal sequences. Hippocampus. 1996; 6(2): 149–172, doi: 10.1002/(sici)1098-1063(1996)6:2<149::aid-hipo6>3.0.co;2-k.
  47. Squire L. Memory and the hippocampus: A synthesis from findings with rats, monkeys, and humans. Psychol Rev. 1992; 99(2): 195–231.
  48. Somogyi P, Klausberger T. Defined types of cortical interneurone structure space and spike timing in the hippocampus. J Physiol. 2004; 562(1): 9–26.
  49. Somogyi P, Katona L, Klausberger T, et al. Temporal redistribution of inhibition over neuronal subcellular domains underlies state-dependent rhythmic change of excitability in the hippocampus. Philos Trans R Soc Lond B Biol Sci. 2014; 369(1635): 20120518.
  50. Stewart M, Fox S. Do septal neurons pace the hippocampal theta rhythm? Trends Neurosci. 1990; 13(5): 163–169.
  51. Swanson LW, Cowan WM. An autoradiographic study of the organization of the efferent connections of the hippocampal formation in the rat. J Comp Neurol. 1977; 172(1): 49–84.
  52. Treves A, Rolls ET. Computational analysis of the role of the hippocampus in memory. Hippocampus. 1994; 4(3): 374–391.
  53. Tukker JJ, Lasztoczi B, Katona L, et al. Distinct Dendritic Arborization and In Vivo Firing Patterns of Parvalbumin-Expressing Basket Cells in the Hippocampal Area CA3. J Neurosci. 2013; 33(16): 6809–6825.
  54. Urban NN, Henze DA, Barrionuevo G. Revisiting the role of the hippocampal mossy fiber synapse. Hippocampus. 2001; 11(4): 408–417.
  55. Viney TJ, Lasztoczi B, Katona L, et al. Network state-dependent inhibition of identified hippocampal CA3 axo-axonic cells in vivo. Nat Neurosci. 2013; 16(12): 1802–1811.
  56. Wang SH, Morris R. Hippocampal-Neocortical Interactions in Memory Formation, Consolidation, and Reconsolidation. Annu Rev Psychol. 2010; 61(1): 49–79.
  57. Willshaw DJ, Buneman OP, Longuet-Higgins HC. Non-holographic associative memory. Nature. 1969; 222(5197): 960–962.

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