Analysis of a Model for Epilepsy : Application of a Max-Type Difference Equation to Mesial Temporal Lobe Epilepsy (Chapman & Hall/crc Monographs and Research Notes in Mathematics)

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Analysis of a Model for Epilepsy : Application of a Max-Type Difference Equation to Mesial Temporal Lobe Epilepsy (Chapman & Hall/crc Monographs and Research Notes in Mathematics)

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  • Chapman & Hall/CRC（2022/06発売）
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  • 製本 Hardcover:ハードカバー版／ページ数 160 p.
  • 言語 ENG
  • 商品コード 9781032255385
  • DDC分類 616.853

Full Description

In the 1960s and 1970s, mathematical biologists Sir Robert M. May, E.C. Pielou, and others utilized difference equations as models of ecological and epidemiological phenomena. Since then, with or without applications, the mathematics of difference equations has evolved into a field unto itself. Difference equations with the maximum (or the minimum or the "rank-type") function were rigorously investigated from the mid-1990s into the 2000s, without any applications in mind. These equations often involved arguments varying from reciprocal terms with parameters in the numerators to other special functions.

Recently, the authors of Analysis of a Model for Epilepsy: Application of a Max-Type Difference Equation to Mesial Temporal Lobe Epilepsy and their colleagues investigated the first known application of a "max-type" difference equation. Their equation is a phenomenological model of epileptic seizures. In this book, the authors expand on that research and present a more comprehensive development of mathematical, numerical, and biological results. Additionally, they describe the first documented instance of a novel dynamical behavior that they call rippled almost periodic behavior, which can be described as an unpredictable pseudo-periodic behavior.

Features:




Suitable for researchers in mathematical neuroscience and potentially as supplementary reading for postgraduate students



Thoroughly researched and replete with references

Contents

1. Introduction: Epilepsy. 1.1. Brief Overview. 1.2. Mesial Temporal Lobe Epilepsy and Other Examples. 2. The Model. 2.1. Model Description. 2.2. Connection to a Simpler Model. 2.3. Connection Between the Model and Epileptic Seizures. 2.4. Open Problem: Seizure Threshold as a Function of Time. 3. Eventual Periodicity of the Model. 3.1. Bounded and Persistent Solutions. 3.2. Eventually Periodic Solutions with Periods Multiples of Six. 3.3. Eventually Periodic Solutions with Period 4. 3.4. Partially and Completely Seizure-Free States. 4. Rippled Almost Periodic Solutions. 4.1. Rippled Behaviour. 4.2. Rippled Almost Periodic Solutions. 4.3. Lyapunov Exponent. 4.4. The State of Status Epilepticus. 4.5. On Termination of Repetition. 5. Numerical Results and Biological Conclusions. 5.1. Bifurcation Diagrams. 5.2. Variability in Seizure Characteristics. 5.3. A Case of Variability in Region 1. 5.4. The Hyperexcitable State. 5.5. Impact of Individual Historical Differences. 6. Epilogue