Computational Fuzzy Modelling Approach to Analyze Neuronal Calcium Dynamics With Intracellular Fluxes

Mathematical neuroscience investigates how calcium distribution in nerve cells affects the neurological system. The interaction of numerous systems is necessary for the operation of several cellular processes in neuron cells, such as calcium, buffer, ER etc. The dynamics of interacting parameters gi...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Cell biochemistry and biophysics 2024-10
Hauptverfasser: Bhattacharyya, Rituparna, Jha, Brajesh Kumar
Format: Artikel
Sprache:eng
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Mathematical neuroscience investigates how calcium distribution in nerve cells affects the neurological system. The interaction of numerous systems is necessary for the operation of several cellular processes in neuron cells, such as calcium, buffer, ER etc. The dynamics of interacting parameters give useful information on neural cell function. This work uses a mathematical model to analyze the dynamic interactions of buffer and ER inside neurons, considering their spatial properties. While buffers bind to calcium ions and lower their concentration, the endoplasmic reticulum (ER) serves as a reservoir, holding a significant number of free calcium ions. The uncertainty of initial values of calcium concentration poses challenges for researchers to develop calcium signaling models. In this article, we examined the exact solution and approximate solution of the mathematical model that was analyzed using the fuzzy undetermined coefficient approach. MATLAB is being used to perform the simulation. Endoplasmic reticulum and buffer have been found to have a substantial impact on calcium signaling. Fuzzy differential equation Provides a useful tool for evaluating complicated processes with imprecise values when ordinary differential equations perform not precisely. They allow for the examination of dynamic processes under fuzzy settings, which contributes to advances research.
ISSN:1085-9195
1559-0283
1559-0283
DOI:10.1007/s12013-024-01541-0