MODELING THE CA2+CAMKII NETWORK OF LTP IN THE JIGCELL ENVIRONMENT

Abstract

Since their initial discovery, long-term potentiation (LTP), and long-term depression (LTD) are accepted as the main biomolecular mechanism that controls memory acquisition. In doing this, both mechanisms are fairly complex and involve specific triggers and many cascades reactions that cross-talk and communicate with others. Thus, they are very complex. To reveal how these mechanisms operate and instruct the brain to remember and forget, one judicious approach is developing the mathematical models of processes. However, this notion requires some basic knowledge regarding ordinary differential equations and writing codes. To this respect, it can be postulated that tools, which can be utilized rather by everyone, would certainly expedite and facilitate the formulation of such models. With this rationale in mind, we demonstrate that JigCell offers the perfect platform to develop such models for LTP. Our choice for this tool stems from the fact that it is designed to simulate complex biological systems with ease. Thus, this manuscript is crafted to illustrate how Ca2+/CaMKII network in LTP was constructed in the JigCell environment and to give an idea of how this tool works

Keywords

• Memory formation
• Long-term potentiation
• Mathematical model
• JigCell
• Calcium
• CaMKII

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