In this chapter we present a review of computational models for studying the dynamic mechanisms that describe the function of the human brain, with a specific focus on epilepsy. Epilepsy is a neurological disorder characterised by an increased likelihood of recurrent seizures, which in turn are characterised by transient, pathological episodes of hypersynchronised neural activity resulting in a variety of behavioural symptoms. Our chapter introduces some of the key concepts of epilepsy from a clinical perspective, before describing some of the classical approaches to modelling brain activity across multiple levels of description. We then focus on how these models have been used to explain and predict experimental and clinical phenomena within the field of epilepsy research. Here we focus on techniques that seek to integrate computational modelling with experimental and clinical measures, as we believe this “systems approach” to epilepsy research is from where the most significant new advances, particularly with regards model validation, will occur. We highlight some of the key studies, as well as emphasising more recent breakthroughs to provide a useful entry point into this rapidly expanding field of research.
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Wessel Woldman was supported by a PhD studentship awarded by the College of Engineering Mathematics and Computer Science. Financial support of the Medical Research Council of the United Kingdom via grant MR/K013996/1 and Epilepsy Research UK via grant P1203 is acknowledged. We thank Simon Todd for useful comments on an earlier version of the manuscript.
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Woldman, W., Terry, J. (2015). Multilevel Computational Modelling in Epilepsy: Classical Studies and Recent Advances. In: Bhattacharya, B., Chowdhury, F. (eds) Validating Neuro-Computational Models of Neurological and Psychiatric Disorders. Springer Series in Computational Neuroscience, vol 14. Springer, Cham. https://doi.org/10.1007/978-3-319-20037-8_7
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