Skip to main content
Log in

The “Memory” Effect in a Chain of Biochemical Reactions with a Positive Feedback is Enhanced by Substrate Saturation Described by Michaelis–Menten Kinetics

  • Published:
Bulletin of Mathematical Biology Aims and scope Submit manuscript

Abstract

Information in the brain is stored in a form of an altered synaptic strength between neurons. The long-term potentiation (LTP), a phenomenon when a short-term increase in neural activity is transformed into a long-lasting increase in strengths of synaptic connectivity, provides an experimental substrate of memory. Using reaction–diffusion equations, we established an LTP model, describing the dynamics of glutamate (Glu), calcium (Ca2+) and nitric oxide (NO) in response to the stimulus—a presynaptic action potential. NO can diffuse to the presynaptic terminal and facilitate the Glu release forming a positive feedback loop. Therefore, the LTP can be considered as a chain of biochemical reactions with a positive feedback loop. In this study, we investigated numerically the role of interactions in a chain of biochemical reactions with a positive feedback on the bistable behavior or memory. We conclude that the positive feedback system with the linear interaction between substances does not exhibit a bistable behavior. However, introduction of substrate saturation described by Michaelis–Menten kinetics for NO decay can lead to an increase in synaptic strength lasting for dozens or even hundreds of seconds. Our finding extends a possible role of NO in LTP: a short high intensity stimulus is “memorized” as a long-lasting elevation of NO concentration.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • Baronas R, Ivanauskas F, Kulys J (2010) The difference schemes for the reaction–diffusion equations. Mathematical modeling of biosensors. Springer, Dordrecht, pp 293–315

    MATH  Google Scholar 

  • Blitzer RD (2005) Long-term potentiation: mechanisms of induction and maintenance. Sci Signal 2005:tr26

    Google Scholar 

  • Bon CL, Garthwaite J (2001) Nitric oxide-induced potentiation of CA1 hippocampal synaptic transmission during baseline stimulation is strictly frequency-dependent. Neuropharmacology 40:501–507

    Google Scholar 

  • Bradley SA, Steinert JR (2016) Nitric oxide-mediated posttranslational modifications: impacts at the synapse. Oxid Med Cell Longev 2016:5681036

    Google Scholar 

  • Bronner F (2001) Extracellular and intracellular regulation of calcium homeostasis. Sci World J 1:919–925

    Google Scholar 

  • Castillo PE (2012) Presynaptic LTP and LTD of excitatory and inhibitory synapses. Cold Spring Harb Perspect Biol 4(2):a005728

    Google Scholar 

  • Chater TE, Goda Y (2014) The role of AMPA receptors in postsynaptic mechanisms of synaptic plasticity. Front Cell Neurosci 8:401

    Google Scholar 

  • Clements JD, Lester RA, Tong G, Jahr CE, Westbrook GL (1992) The time course of glutamate in the synaptic cleft. Science 258:1498–1501

    Google Scholar 

  • Frade JG, Barbosa RM, Laranjinha J (2009) Stimulation of NMDA and AMPA glutamate receptors elicits distinct concentration dynamics of nitric oxide in rat hippocampal slices. Hippocampus 19:603–611

    Google Scholar 

  • Garthwaite J (2008) Concepts of neural nitric oxide-mediated transmission. Eur J Neurosci 27:2783–2802

    Google Scholar 

  • Garthwaite J (2016) From synaptically localized to volume transmission by nitric oxide. J Physiol 594:9–18

    Google Scholar 

  • Garthwaite J, Charles SL, Chess-Williams R (1988) Endothelium-derived relaxing factor release on activation of NMDA receptors suggests role as intercellular messenger in the brain. Nature 336:385–388

    Google Scholar 

  • Haley JE, Wilcox GL, Chapman PF (1992) The role of nitric oxide in hippocampal long-term potentiation. Neuron 8:211–216

    Google Scholar 

  • Hall CN, Garthwaite J (2009) What is the real physiological NO concentration in vivo? Nitric Oxide 21:92–103

    Google Scholar 

  • Hardingham N, Dachtler J, Fox K (2013) The role of nitric oxide in pre-synaptic plasticity and homeostasis. Front Cell Neurosci 7:190

    Google Scholar 

  • Herring BE, Nicoll RA (2016) Long-term potentiation: from CaMKII to AMPA receptor trafficking. Annu Rev Physiol 78:351–365

    Google Scholar 

  • Hopper RA, Garthwaite J (2006) Tonic and phasic nitric oxide signals in hippocampal long-term potentiation. J Neurosci 26:11513–11521

    Google Scholar 

  • Huang EP (1997) Synaptic plasticity: a role for nitric oxide in LTP. Curr Biol 7:R141–R143

    Google Scholar 

  • Izaki Y, Takita M, Nomura M, Akema T (2003) Differences between paired-pulse facilitation and long-term potentiation in the dorsal and ventral hippocampal CA1-prefrontal pathways of rats. Brain Res 992:142–145

    Google Scholar 

  • Kim HY, Jun J, Wang J, Bittar A, Chung K, Chung JM (2015) Induction of long-term potentiation and long-term depression is cell-type specific in the spinal cord. Pain 156:618–625

    Google Scholar 

  • Kovalchuk Y, Eilers J, Lisman J, Konnerth A (2000) NMDA receptor-mediated subthreshold Ca2+ signals in spines of hippocampal neurons. J Neurosci 20:1791–1799

    Google Scholar 

  • Laranjinha J, Santos RM, Lourenço CF, Ledo A, Barbosa RM (2012) Nitric oxide signaling in the brain: translation of dynamics into respiration control and neurovascular coupling. Ann NY Acad Sci 1259:10–18

    Google Scholar 

  • Lomo T (1966) Frequency potentiation of excitatory synaptic activity in the dentate area of the hippocampal formation. Acta Physiol Scand 68(277):128

    Google Scholar 

  • Lüscher C, Malenka RC (2012) NMDA receptor-dependent long-term potentiation and long-term depression (LTP/LTD). Cold Spring Harb Perspect Biol 4(6):a005710

    Google Scholar 

  • Manninen T, Hituri K, Kotaleski JH, Blackwell KT, Linne ML (2010) Postsynaptic signal transduction models for long-term potentiation and depression. Front Comput Neurosci 4:152

    Google Scholar 

  • Mayford M, Siegelbaum SA, Kandel ER (2012) Synapses and memory storage. Cold Spring Harb Perspect Biol 4(6):a005751

    Google Scholar 

  • Mazzoni A, Broccard FD, Garcia-Perez E, Bonifazi P, Ruaro ME, Torre V (2007) On the dynamics of the spontaneous activity in neuronal networks. PLoS ONE 2:e439

    Google Scholar 

  • McCormick DA (2005) Neuronal networks: flip-flops in the brain. Curr Biol 15:R294–R296

    Google Scholar 

  • Mincheva M, Craciun G (2008) Multigraph conditions for multistability, oscillations and pattern formation in biochemical reaction networks. Proc IEEE 96:1281–1291

    Google Scholar 

  • Muñoz FJ, Godoy JA, Cerpa W, Poblete IM, Huidobro-Toro JP, Inestrosa NC (2014) Wnt-5a increases NO and modulates NMDA receptor in rat hippocampal neurons. Biochem Biophys Res Commun 444:189–194

    Google Scholar 

  • Neitz A, Mergia E, Imbrosci B, Petrasch-Parwez E, Eysel UT, Koesling D, Mittmann T (2014) Postsynaptic NO/cGMP increases NMDA receptor currents via hyperpolarization-activated cyclic nucleotide-gated channels in the hippocampus. Cereb Cortex 24(7):1923–1936

    Google Scholar 

  • Parodi J, Montecinos-Oliva C, Varas R, Alfaro IE, Serrano FG, Varas-Godoy M, Muñoz FJ, Cerpa W, Godoy JA, Inestrosa NC (2015) Wnt5a inhibits K(+) currents in hippocampal synapses through nitric oxide production. Mol Cell Neurosci 68:314–322

    Google Scholar 

  • Penn Y, Segal M, Moses E (2016) Network synchronization in hippocampal neurons. Proc Natl Acad Sci USA 113:3341–3346

    Google Scholar 

  • Pigott BM, Garthwaite J (2016) Nitric oxide is required for L-Type Ca(2+) channel-dependent long-term potentiation in the hippocampus. Front Synaptic Neurosci 8:17

    Google Scholar 

  • Prinz AA, Bucher D, Marder E (2004) Similar network activity from disparate circuit parameters. Nat Neurosci 7(12):1345–1352

    Google Scholar 

  • Sala F, Hernández-Cruz A (1990) Calcium diffusion modeling in a spherical neuron. Relevance of buffering properties. Biophys J 57:313–324

    Google Scholar 

  • Samarskii AA (2001) The theory of difference schemes. CRC Press, New York

    MATH  Google Scholar 

  • Susswein AJ, Katzoff A, Miller N, Hurwitz I (2004) Nitric oxide and memory. The Neuroscientist 10:153–162

    Google Scholar 

  • Ventriglia F, Di Maio V (2000) A Brownian model of glutamate diffusion in excitatory synapses of hippocampus. Biosystems 58:67–74

    Google Scholar 

  • Volgushev M, Balaban P, Chistiakova M, Eysel UT (2000) Retrograde signalling with nitric oxide at neocortical synapses. Eur J Neurosci 12:4255–4267

    Google Scholar 

  • Wang Q, Mergia E, Koesling D, Mittmann T (2017) Nitric oxide/cGMP signaling via guanylyl cyclase isoform 1 modulates glutamate and GABA release in somatosensory cortex of mice. Neuroscience 360:180–189

    Google Scholar 

  • Zacharia IG, Deen WM (2005) Diffusivity and solubility of nitric oxide in water and saline. Ann Biomed Eng 33:214–222

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Aidas Alaburda.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Katauskis, P., Ivanauskas, F. & Alaburda, A. The “Memory” Effect in a Chain of Biochemical Reactions with a Positive Feedback is Enhanced by Substrate Saturation Described by Michaelis–Menten Kinetics. Bull Math Biol 81, 919–935 (2019). https://doi.org/10.1007/s11538-018-00541-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11538-018-00541-5

Keywords

Navigation