Chapter 5 - Organization and control of epileptic circuits in temporal lobe epilepsy

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Abstract

When studying the pathological mechanisms of epilepsy, there are a seemingly endless number of approaches from the ultrastructural level—receptor expression by EM—to the behavioral level—comorbid depression in behaving animals. Epilepsy is characterized as a disorder of recurrent seizures, which are defined as “a transient occurrence of signs and/or symptoms due to abnormal excessive or synchronous neuronal activity in the brain” (Fisher et al., 2005). Such abnormal activity typically does not occur in a single isolated neuron; rather, it results from pathological activity in large groups—or circuits—of neurons. Here we choose to focus on two aspects of aberrant circuits in temporal lobe epilepsy: their organization and potential mechanisms to control these pathological circuits. We also look at two scales: microcircuits, ie, the relationship between individual neurons or small groups of similar neurons, and macrocircuits, ie, the organization of large-scale brain regions. We begin by summarizing the large body of literature that describes the stereotypical anatomical changes in the temporal lobe—ie, the anatomical basis of alterations in microcircuitry. We then offer a brief introduction to graph theory and describe how this type of mathematical analysis, in combination with computational neuroscience techniques and using parameters obtained from experimental data, can be used to postulate how microcircuit alterations may lead to seizures. We then zoom out and look at the changes which are seen over large whole-brain networks in patients and animal models, and finally we look to the future.

Section snippets

Organization and Reorganization of Microcircuits: Anatomical Changes in Temporal Lobe Epilepsy

Temporal lobe epilepsy (TLE) is the most common subtype of epilepsy in human patients (Wiebe, 2000). Unlike many other forms of human epilepsies, TLE results in stereotyped pathological changes that can be examined not only in human tissue but in an array of animal models of this disease (Kandratavicius et al., 2014, Levesque et al., 2015). To understand a network pathology such as epilepsy, a good starting point is to attempt to understand any anatomical microcircuit alterations that may occur

From Organization to Control of Neuronal Circuits: Introduction to Graph Theory

Before we discuss how the above anatomical changes might lead to hyperexcitability or seizures, we pause for a brief background on graph theory. Pioneered by Euler in the 18th century, it has gained a recent resurgence in popularity, in large part due to the important work of Watts and Strogatz who demonstrated its usefulness in describing systems as diverse as neural networks of Caenorhabditis elegans, power grids, and the interconnectedness of film actors (Watts and Strogatz, 1998).

Graph

Beginning to Control Microcircuits: Using Graph Theory to Control Circuits In Silico

We will now focus our attention on studies that use computational techniques to apply graph theory as a technique in understanding how experimentally demonstrated changes in microcircuitry contribute to network hyperexcitability. TLE development is most often characterized by three different stages: (1) an initial precipitating event, (2) a period of epileptogenesis, and (3) recurrent spontaneous seizures. Most of the anatomical and physiological changes occur during the period of

Further Control of Microcircuits: Can We Learn to Control a Pathological Circuit in Order to Treat Epilepsy?

Ultimately, the goal of all research into epileptic circuits is to understand this pathology in order to develop better treatments for patients with TLE. Once details of epileptic circuits are known at small and large scales, controlling the circuit may become possible. There are a wide variety of techniques other than anatomy or electrophysiology which may be useful for continuing to helping to map out these circuits including an innovative type of high-resolution microscopy called STORM (Dani

Network Organization at the Macrocircuit Level: Applications of Graph Theory at a Larger Scale

Although most of the pathological changes in TLE occur in the hippocampus and adjacent structures, this disease affects extratemporal structures as well, as evidenced by the facts that many patients with TLE do not have a complete remission of their seizures after TLE and also that many patients with TLE suffer from psychiatric comorbidities (Kandratavicius et al., 2014, Wiebe and England, 2001). Therefore, graph theory analysis has been proposed as a way to understand the changing circuitry of

Conclusions

In summary, computational science and experimental techniques offer complementary techniques to allow researchers to understand brain dynamics in normal and pathological conditions. Many anatomical details about circuit reorganization in epilepsy have already been demonstrated, and these predictions can offer the possibility of expanding this knowledge further. As computational models grow in size, accuracy, and complexity, they will produce more reliable predictions as to what variables are

Acknowledgments

The work was funded by the US National Institutes of Health grants NS35915 and NS94668 (to I.S.), R25NS065741-04S1 (to A.A.), and the National Aeronautics and Space Administration grant NSCOR NNX10AD59G (to I.S.).

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