Onset of poly-spike complexes in a mean-field model of human EEG and its application to absence epilepsy

Onset of poly-spike complexes in a mean-field model of human EEG and its application to absence epilepsy. General rights This document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: Explore Bristol Research is a digital archive and the intention is that deposited content should not be removed. However, if you believe that this version of the work breaches copyright law please contact open-access@bristol.ac.uk and include the following information in your message: • Your contact details • Bibliographic details for the item, including a URL • An outline of the nature of the complaint On receipt of your message the Open Access Team will immediately investigate your claim, make an initial judgement of the validity of the claim and, where appropriate, withdraw the item in question from public view. Onset of poly-spike complexes in a mean-field model of human EEG and its application to absence epilepsy. In this paper we introduce a modification of a mean-field model used to describe the brain's electrical activity as recorded via Electroencephalography (EEG). The focus of the present study is to understand the mechanisms giving rise to dynamics observed during absence epilepsy, one of the classical generalized syndromes. A systematic study of data from a number of different subjects with absence epilepsy demonstrates a wide variety of dynamical phenomena in the recorded EEG. In addition to the classical spike and wave activity, there may be poly-spike and wave, wave-spike or even no discernible spike-wave onset during seizure events. The model we introduce is able to capture all of these different phenomena and we describe the bifurcations giving rise to these different types of seizure activity. We argue that such a model may provide a useful clinical tool for classifying different sub-classes of absence epilepsy.

[1]  H. Haken,et al.  Field Theory of Electromagnetic Brain Activity. , 1996, Physical review letters.

[2]  R. Hays,et al.  Development of the Quality of Life in Epilepsy Inventory , 1995, Epilepsia.

[3]  P. Robinson,et al.  Dynamics of large-scale brain activity in normal arousal states and epileptic seizures. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[4]  W. Freeman.  Mass action in the nervous system : examination of the neurophysiological basis of adaptive behavior through the EEG , 1975 .

[5]  A. Kraskov,et al.  On the predictability of epileptic seizures , 2005, Clinical Neurophysiology.

[6]  J. W. A. S. Sander,et al.  Mortality from epilepsy: results from a prospective population-based study , 1994, The Lancet.

[7]  E. Trinka.  Absences in adult seizure disorders , 2005, Acta neurologica Scandinavica. Supplementum.

[8]  David F. Smith,et al.  Patients' Experiences of Injury as a Result of Epilepsy , 1997, Epilepsia.

[9]  J. Frost,et al.  The EEG in Selected Generalized Seizures , 2006, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[10]  John R. Terry,et al.  A unifying explanation of primary generalized seizures through nonlinear brain modeling and bifurcation analysis. , 2006, Cerebral cortex.

[11]  Serafim Rodrigues,et al.  Existence and stability of limit cycles in a macroscopic neuronal population model , 2007 .

[12]  J. Bellanger,et al.  Epileptic fast activity can be explained by a model of impaired GABAergic dendritic inhibition , 2002, The European journal of neuroscience.

[13]  John R. Terry,et al.  On the genesis of spike-wave oscillations in a mean-field model of human thalamic and corticothalamic dynamics , 2006 .

[14]  R. Jindra.  Mass action in the nervous system W. J. Freeman, Academic Press, New York (1975), 489 pp., (hard covers). $34.50 , 1976, Neuroscience.

[15]  M. T. Medina,et al.  Seizures of Idiopathic Generalized Epilepsies , 2005, Epilepsia.

[16]  V. Crunelli,et al.  Childhood absence epilepsy: Genes, channels, neurons and networks , 2002, Nature Reviews Neuroscience.

[17]  Christopher T. H. Baker,et al.  Issues in the numerical solution of evolutionary delay differential equations , 1995, Adv. Comput. Math..

[18]  G. Lord,et al.  Waves and bumps in neuronal networks with axo-dendritic synaptic interactions , 2003 .

[19]  James J. Wright,et al.  Propagation and stability of waves of electrical activity in the cerebral cortex , 1997 .

[20]  J. Parra,et al.  Epileptic Transitions: Model Predictions and Experimental Validation , 2005, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[21]  G. Samaey,et al.  DDE-BIFTOOL v. 2.00: a Matlab package for bifurcation analysis of delay differential equations , 2001 .

[22]  David Barton,et al.  Transitions to spike-wave oscillations and epileptic dynamics in a human cortico-thalamic mean-field model , 2009, Journal of Computational Neuroscience.

[23]  F. H. Lopes da Silva,et al.  Model of brain rhythmic activity , 1974, Kybernetik.