Abstract
Depressed \( Na^{ + } \)/\( K^{ + } \) ATParse amount and diminished glutamate agreement in Alzheimer’s disease brain is coupled through Alzheimer’s disease. Cellular ion disparity might be its outcome. As soon as the cell is energized by some inner or exterior spur then action potential in the shape of very small pulses arises. It overreaches the decisive threshold of the membrane. The action potential initiation observed in cortical neurons is not capable to be explained by HH type models. This paper reviews HH model and shows the difference between a HH model with its sodium and potassium ion currents and the ionic concentrations of sodium and potassium of a person with Alzheimer’s disease in it. Results are generated in form of graphs. This model is implemented in Matlab software to fairly accurate the differential equations. By using HH model, further parameters are created, \( Na^{ + } \) and \( K^{ + } \). The new parameters need to be carefully considered and analyzed.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Vitvitsky, V.M., Garg, S.K., Keep, R.F., Albin, R.L., Banerjee, R.: Na+ and K+ ion imbalances in Alzheimer’s disease. Biochim. Biophys. Acta 1822(11), 1671–1681 (2012)
Bagheri, S., Squitti, R., Haertlé, T., Siotto, M., Saboury, A.A.: Role of copper in the onset of Alzheimer’s disease compared to other metals. Front. Aging Neurosci. 9, article 446 (2018)
Emin Tagluk, M., Tekin, R.: The influence of ion concentrations on the dynamic behavior of the Hodgkin–Huxley model-based cortical network. Cogn. Neurodyn. 8(4), 287–298 (2014). https://doi.org/10.1007/s11571-014-9281-5
Kager, H., Wadman, W.J., Somjen, G.G.: Simulated seizures and spreading depression in a neuron model incorporating interstitial space and ion concentrations. Am. Physiol. Soc. 84(1), 495–512 (2000)
Stankevich, N.: A rare and hidden attractor with noise in a biophysical Hodgkin–Huxley-type of model. Nonlinear Sciences, Chaotic Dynamics (2017)
Cisternas, P., et al.: The increased potassium intake improves cognitive performance and attenuates histopathological markers in a model of Alzheimer’s disease. Biochem. Biophys. Acta 1852, 2630–2644 (2015)
Levi, T., Khoyratee, F., Saïghi, S., Ikeuchi, Y.: Digital implementation of Hodgkin–Huxley neuron model for neurological diseases studies. Artif. Life Robot. 23(1), 10–14 (2017). https://doi.org/10.1007/s10015-017-0397-7
Vermeer, S.E., Prins, N.D., den Heijer, T., Hofman, A., Koudstaal, P.J., Breteler, M.M.: Silent brain infarcts and the risk of dementia and cognitive decline. N. Engl. J. Med. 348(13), 1215–1222 (2003)
Ozer, M., Perc, M., Uzuntarla, M.: Controlling the spontaneous spiking regularity via channel blocking on Newman-Watts networks of Hodgkin–Huxley neurons. Front. Phys. 86(4), 40008 (2009)
Brookmeyer, R., Johnson, E., Ziegler-Graham, K., Michael Arrighi, H.: Forecasting the global burden of Alzheimer’s disease. Alzheimer’s Dementia 3, 186–191 (2007)
Ozer, M., Uzuntarla, M., Perc, M., Graham, L.J.: Spike latency and jitter of neuronal membrane patches with stochastic Hodgkin-Huxley channels. J. Theor. Biol. 261(1), 83–92 (2009)
Bazsó, F., Zalányi, L., Csárdi, G.: Channel noise in Hodgkin–Huxley model neurons. Phys. Lett. A 311(1), 13–20 (2003)
Hill, B., Schubert, E., Nokes, M., Michelson, R.: Laser interferometer measurement of changes in crayfish axon diameter concurrent with action potential. Science 196(4288), 426–428 (1977)
Kalnay, E.: Atmospheric Modeling, Data Assimilation, and Predictability. Cambridge University Press, New York (2003)
Roper, S., Obenaus, A., Dudek, F.: Osmolality and nonsynaptic epileptiform bursts in rat CA1 and dentate gyrus. Ann. Neurol. 31(1), 81–85 (1992)
Rosen, A., Andrew, R.: Osmotic effects upon excitability in rat neocortical slices. Neuroscience 38(3), 579–590 (1990)
Rudolph, M., Piwkowska, Z., Badoual, M., Bal, T., Destexhe, A.: A method to estimate synaptic conductances from membrane potential fluctuations. J. Neurophysiol. 91(6), 2884–2896 (2004)
Ullah, G., Schiff, S.: Assimilating seizure dynamics. PLoS Comput. Biol. 6(5), e1000776 (2010)
Sun, X., Perc, M., Lu, Q., Kurths, J.: Spatial coherence resonance on diffusive and small-world networks of Hodgkin–Huxley neurons. Interdiscip. J. Nonlinear Sci. 18(2), 023102 (2008)
Roberts, B.R., et al.: Rubidium and potassium levels are altered in Alzheimer’s disease brain and blood but not in cerebrospinal fluid. Acta Neuropathol. Commun. 4(1), 119 (2016)
Gupta, S., Singh, J.: Investigating correlation properties of Hodgkin–Huxley model with leaky ıntegrate – and-fire model. In: Proceedings of International Conference on Advances in Computer Science, AETACS (2013)
Fuller, S., Steele, M., Münch, G.: Activated astroglia during chronic inflammation in Alzheimer’s disease—do they neglect their neurosupportive roles? Mutat. Res. 690, 40–49 (2010)
Gupta, S., Singh, J.: Spiking patterns of Hodgkin-Huxley model in Alzheimer’s disease: effects caused by noise current. Int. J. Comput. Appl. (0975-8887) 94(11), 1–6 (2014)
Kneller, J., Ramirez, R.J., Chartier, D., Courtemanche, M., Nattel, S.: Time dependent transients in an ionically based mathematical model of the canine atrial action potential. Am. J. Physiol. Heart Circ. Physiol. 282, H1437–H1451 (2002)
Ziburkus, J., Cressman, J., Barreto, E., Schiff, S.: Interneuron and pyramidal cell interplay during in vitro seizure-like events. J. Neurophysiol. 95(6), 3948–3954 (2006)
Allaman, I., et al.: Amyloid-β aggregates cause alterations of astrocytic metabolic phenotype: impact on neuronal viability. J. Neurosci. 30(9), 3326–3338 (2010). https://doi.org/10.1523/jneurosci.5098-09.2010
Ullah, G., Schiff, S.J.: Personality and Alzheimer’s disease: an integrative review. Pers. Disord. 10(1), 4–12 (2019)
Scheffer, M., et al.: Anticipating critical transition. Science 338, 344–348 (2012)
Barreto, E., Cressman, J.R.: Ion concentration dynamics as a mechanism for neuronal bursting. J. Biol. Phys. 37, 361–373 (2011)
Supnet, C., Bezprozvanny, I.: The dysregulation of intracellular calcium in Alzheimer disease. Cell Calcium 47, 183–189 (2010)
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Gupta, S., Singh, J., Kumar, K. (2020). Ionic Concentration and Action Potential Differences Between a Healthy and Alzheimer’s Disease Person. In: Batra, U., Roy, N., Panda, B. (eds) Data Science and Analytics. REDSET 2019. Communications in Computer and Information Science, vol 1229. Springer, Singapore. https://doi.org/10.1007/978-981-15-5827-6_23
Download citation
DOI: https://doi.org/10.1007/978-981-15-5827-6_23
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-5826-9
Online ISBN: 978-981-15-5827-6
eBook Packages: Computer ScienceComputer Science (R0)