Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Hostname: page-component-78c5997874-4rdpn Total loading time: 0 Render date: 2024-11-19T12:15:45.077Z Has data issue: false hasContentIssue false

Chapter 5 - Personalized Network Modeling in Epilepsy

Published online by Cambridge University Press:  06 January 2023

By
Yujiang Wang ,
Gabrielle Marie Schroeder ,
Nishant Sinha  and
Peter Neal Taylor
Edited by
Rod C. Scott  and
J. Matthew Mahoney
Rod C. Scott
Affiliation:
University of Vermont
J. Matthew Mahoney
Affiliation:
University of Vermont
Get access

Summary

Epilepsy is a family of neurological disorders in which patients experience unprovoked spontaneous seizures. Unfortunately, there is currently no cure for epilepsy, and seizure management is the target of most therapies. The first-line treatment of epilepsy is usually antiepileptic drugs. However, depending on the subtype of epilepsy and the individual, drug treatments fail to control the seizures in around one-third of patients. One challenge in the treatment of epilepsy is its heterogeneity. In each patient, seizures are thought to be generated by different mechanisms, processes, and parameters, and treatment outcomes will also depend on these.

Type
Chapter
Information
A Complex Systems Approach to Epilepsy
Concept, Practice, and Therapy
 , pp. 61 - 71
Publisher: Cambridge University Press
Print publication year: 2023

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Truccolo, W., Donoghue, J.A., Hochberg, L.R., et al. Single-neuron dynamics in human focal epilepsy. Nat. neurosci., 14(5), 635 (2011).Google Scholar
Merricks, E.M., Smith, E.H., McKhann, G.M., et al. Single unit action potentials in humans and the effect of seizure activity. Brain, 138(10), 2891–2906 (2015).Google Scholar
Cook, M. J., O’Brien, T. J., Berkovic, S. F., et al. Prediction of seizure likelihood with a long-term, implanted seizure advisory system in patients with drug-resistant epilepsy: a first-in-man study. Lancet Neurol., 12(6), 563–571 (2013).Google Scholar
Coan, AC, Chaudhary, UJ, Grouiller, F., et al. EEG-fMRI in the presurgical evaluation of temporal lobe epilepsy. J. Neurol. Neurosurg. Psychiatry, 87(6), 642–9, ( 2016).Google Scholar
Moeller, F., Siebner, H. R., Wolff, S., et al. Simultaneous EEG-fMRI in drug-naive children with newly diagnosed absence epilepsy. Epilepsia, 49(9), 1510–9 (2008).Google Scholar
Duncan, John S., Winston, Gavin P., Koepp, Matthias J., and Ourselin, Sebastien. Brain imaging in the assessment for epilepsy surgery. Lancet Neurol., 15(4), 420–33 (2016).Google Scholar
Lossius, M. I., Hessen, E., Mowinckel, P., et al. Consequences of antiepileptic drug withdrawal: a randomized, double‐blind study (Akershus Study). Epilepsia, 49(3), 455–63 (2008).CrossRefGoogle ScholarPubMed
Wilson, H. R., and Cowan, J. D. Excitatory and inhibitory interactions in localized populations of model neurons. Biophys. J., 12(1), 1–24 (1972).Google Scholar
Jansen, B. H., and Rit, V. G. Electroencephalogram and visual evoked potential generation in a mathematical model of coupled cortical columns. Biol. Cybern., 73(4), 357–66 (1995).Google Scholar
da Silva, F. L., Blanes, W., Kalitzin, S.N., et al. Epilepsies as dynamical diseases of brain systems: basic models of the transition between normal and epileptic activity. Epilepsia, 44, 72–83 (2003).Google Scholar
Baier, G., Goodfellow, M., Taylor, P. N., Wang, Y., and Garry, D. J. The importance of modeling epileptic seizure dynamics as spatio-temporal patterns. Front. Physiol., 3, 281 (2012).Google Scholar
Wang, Y., Goodfellow, M., Taylor, P. N., and Baier, G. Phase space approach for modeling of epileptic dynamics. Phys. Rev. E Stat. Nonlin. Soft Matter Phys., 85(6 Pt 1), 061918 (2012).Google Scholar
Hutchings, F., Han, C. E., Keller, S. S., et al. Predicting Surgery Targets in Temporal Lobe Epilepsy through Structural Connectome Based Simulations. PLoS Comput. Biol., 11(12), 1–24 (2015).Google Scholar
Taylor, P. N., Kaiser, M., and Dauwels, J. Structural connectivity based whole brain modelling in epilepsy. J. Neurosci. Methods, 236, 51–7 (2014).CrossRefGoogle ScholarPubMed
Richardson, M. P. Large scale brain models of epilepsy: dynamics meets connectomics. J. Neurol. Neurosurg. Psychiatry, 83, 1238–48 (2012).Google Scholar
Taylor, P. N., Thomas, J., Sinha, N., et al. Optimal control based seizure abatement using patient derived connectivity. Front. Neurosci., 9, 1–10 (2015).Google Scholar
Sinha, N., Dauwels, J., Kaiser, M., et al. Predicting neurosurgical outcomes in focal epilepsy patients using computational modelling. Brain, 140(2), 319–32 (2017).Google Scholar
Hagmann, P., Cammoun, L., Gigandet, X., et al. Mapping the structural core of human cerebral cortex. PLoS biol., 6(7), e159 (2008).Google Scholar
Winston, G. P., Yogarajah, M., Symms, M. R., et al. Diffusion tensor imaging tractography to visualize the relationship of the optic radiation to epileptogenic lesions prior to neurosurgery. Epilepsia, 52(8), 1430-8 (2011).Google Scholar
Winston, G. P., Daga, P., Stretton, J., et al. Optic radiation tractography and vision in anterior temporal lobe resection. Ann. Neurol., 71(3), 334–41 (2012).CrossRefGoogle ScholarPubMed
Taylor, P. N., Sinha, N., Wang, Y., et al. The impact of epilepsy surgery on the structural connectome and its relation to outcome. Neuroimage Clin., 18, 202–14 (2018).CrossRefGoogle ScholarPubMed
Ahmadi, M. E., Hagler, D.J., McDonald, C. R., et al. Side matters: diffusion tensor imaging tractography in left and right temporal lobe epilepsy. Am. J. Neuroradiol., 30(9), 1740–7 (2009).Google Scholar
Concha, L., Beaulieu, C., and Gross, D. W. Bilateral limbic diffusion abnormalities in unilateral temporal lobe epilepsy. Ann. Neurol., 57(2), 188–96 (2005).CrossRefGoogle ScholarPubMed
Bonilha, L., Nesland, T., Martz, G. U., et al. Medial temporal lobe epilepsy is associated with neuronal fibre loss and paradoxical increase in structural connectivity of limbic structures. J. Neurol. Neurosurg. Psychiatry, 83(9), 903–9 (2012).Google Scholar
Besson, P., Dinkelacker, V., Valabregue, R., et al. Structural connectivity differences in left and right temporal lobe epilepsy. Neuroimage, 100, 135–44 (2014).Google Scholar
DeSalvo, M. N., Douw, L., Tanaka, N., Reinsberger, C., and Stufflebeam, S. M. Altered structural connectome in temporal lobe epilepsy. Radiology, 270(3), 842–8 (2014).Google Scholar
Honey, C. J., and Sporns, O. Dynamical consequences of lesions in cortical networks. Hum. Brain Mapp., 29(7), 802–9 (2008).CrossRefGoogle ScholarPubMed
de Tisi, J., Bell, G. S., Peacock, J. L., et al. The long-term outcome of adult epilepsy surgery, patterns of seizure remission, and relapse: A cohort study. Lancet, 378(9800), 1388–95 (2011).Google Scholar
Jirsa, V. K., Proix, T., Perdikis, D., et al. The virtual epileptic patient: individualized whole-brain models of epilepsy spread. Neuroimage, 145, 377–88 (2017).Google Scholar
Jirsa, V. K., Stacey, W. C., Quilichini, P. P., Ivanov, A. I., and Bernard, C. On the nature of seizure dynamics. Brain, 137(8), 2210–30 (2014).CrossRefGoogle ScholarPubMed
Proix, T., Bartolomei, F., Guye, M., and Jirsa, V. K. Individual brain structure and modelling predict seizure propagation. Brain, 140(3), 641–54 (2017).CrossRefGoogle ScholarPubMed
Proix, T., Jirsa, V. K., Bartolomei, F., Guye, M., and Truccolo, W. Predicting the spatiotemporal diversity of seizure propagation and termination in human focal epilepsy. Nat. Commun., 9(1), 1088 (2018).CrossRefGoogle ScholarPubMed
Yan, B., and Li, P. The emergence of abnormal hypersynchronization in the anatomical structural network of human brain. Neuroimage, 65, 34–51 (2013).Google Scholar
Taylor, P. N., Goodfellow, M., Wang, Y., and Baier, G. Towards a large-scale model of patient- specific epileptic spike-wave discharges. Biol. Cybern., 107, 83–94 (2013).CrossRefGoogle ScholarPubMed
Lu, J., Guo, S., Chen, M., Wang, W., Yang, H., Guo, D., & Yao, D. (2018). Generate the scale-free brain music from BOLD signals. Medicine, 97(2).Google ScholarPubMed
Abdelnour, F., Mueller, S., and Raj, A. Relating cortical atrophy in temporal lobe epilepsy with graph diffusion-based network models. PLoS Comput. Biol., 11(10), e1004564 (2015).Google Scholar
Javidan, Manouchehr. Electroencephalography in mesial temporal lobe epilepsy: A review. Epilepsy Res. Treat., 2012, 637430 (2012).Google Scholar
Taussig, D., Montavont, A., and Isnard, J. Invasive EEG explorations. Neurophysiologie Clinique/Clinical Neurophysiology, 45(1), 113–9 (2015).Google ScholarPubMed
Sinha, N., Dauwels, J., Wang, Y., Cash, S. S., and Taylor, P. An in silico approach for pre-surgical evaluation of an epileptic cortex. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc., 2014, 4884–7 (2014).Google Scholar
Goodfellow, M., Rummel, C., Abela, E., et al. Estimation of brain network ictogenicity predicts outcome from epilepsy surgery. Scientific reports, 6, 29215 (2016).Google Scholar
Lopes, M. A., Richardson, M. P., Abela, E. An optimal strategy for epilepsy surgery: Disruption of the rich-club? PLoS Comput. Biol., 13(8), e1005637 (2017).Google Scholar
Yang, C., Luan, G., Wang, Q., et al. localization of epileptogenic zone with the correction of pathological networks. Front. Neurol., 9, 143 (2018).CrossRefGoogle ScholarPubMed
Khambhati, A. N., Davis, K. A., Lucas, T. H., Litt, B., and Bassett, D. S. Virtual cortical resection reveals push-pull network control preceding seizure evolution. Neuron, 91(5), 1170–82 (2016).CrossRefGoogle ScholarPubMed
Burns, S.P., Santaniello, S., Yaffe, R.B., et al. Network dynamics of the brain and influence of the epileptic seizure onset zone. Proc. Nat. Acad. Sci., 111(49), E5321–30 (2014).Google Scholar
Kramer, M. A., Eden, U.T., Kolaczyk, E.D., et al. Coalescence and fragmentation of cortical networks during focal seizures. J. Neurosci., 30(30), 10076–85 (2010).Google Scholar
Benjamin, O., Fitzgerald, T. H., Ashwin, P., et al. A phenomenological model of seizure initiation suggests network structure may explain seizure frequency in idiopathic generalised epilepsy. J. Math. Neurosci., 2(1), 1 (2012).Google Scholar
Schmidt, H., Petkov, G., Richardson, M. P., and Terry, J. R. Dynamics on networks: The role of local dynamics and global networks on the emergence of hypersynchronous neural activity. PLoS Comput. Biol., 10(11), e1003947 (2014).CrossRefGoogle ScholarPubMed
Taylor, P., Baier, G., Cash, S., et al. A model of stimulus induced epileptic spike-wave discharges. 2013 IEEE Symposium Computational Intelligence, Cognitive Algorithms, Mind and Brain. 53–59 (2013). doi:10.1109/ccmb.2013.6609165.Google Scholar
Zheng, T. W., O’Brien, T. J., Morris, M. J., et al. Rhythmic neuronal activity in S2 somatosensory and insular cortices contribute to the initiation of absence-related spike-and-wave discharges. Epilepsia, 53(11), 1–11 (2012).Google Scholar
Wendling, F., Bartolomei, F., Bellanger, J. J., and Chauvel, P. Epileptic fast activity can be explained by a model of impaired GABAergic dendritic inhibition. Eur. J. Neurosci., 15, 1499–1508 (2002).Google Scholar
Hebbink, J., Meijer, H., Huiskamp, G., van Gils, S., and Leijten, F. Phenomenological network models: Lessons for epilepsy surgery. Epilepsia, 58, e147–51 (2017).Google Scholar
Smith, E. H., and Schevon, C. A. Toward a mechanistic understanding of epileptic networks. Curr. Neurol. Neurosci. Rep., 16(11), 97 (2016).Google Scholar
Ridley, B., Wirsich, J., Bettus, G., et al. Simultaneous intracranial EEG-fMRI shows inter-modality correlation in time-resolved connectivity within normal areas but not within epileptic regions. Brain Topogr., 30(5), 639–55 (2017).Google Scholar
Papadopoulou, M., Leite, M., van Mierlo, P., et al. Tracking slow modulations in synaptic gain using dynamic causal modelling: Validation in epilepsy. Neuroimage, 107, 117–26 (2015).CrossRefGoogle ScholarPubMed
Papadopoulou, M., Cooray, G., Rosch, R., et al. Dynamic causal modelling of seizure activity in a rat model. Neuroimage, 146, 518–32 (2017).CrossRefGoogle ScholarPubMed
Rosch, R. E., Wright, S., Cooray, G., et al. NMDA-receptor antibodies alter cortical microcircuit dynamics. Proc. Nat. Acad. Sci., 115(42), E9916–25 (2018).CrossRefGoogle ScholarPubMed
Karoly, P.J., Kuhlmann, L., Soudry, D., et al. Seizure pathways: A model-based investigation. PLoS Comput. Biol., 14(10), e1006403. (2018).Google Scholar
Aarabi, A., and He, B. Seizure prediction in hippocampal and neocortical epilepsy using a model-based approach. Clin. Neurophysiol., 125(5), 930–40 (2014).Google Scholar
Wendling, F., Hernandez, A., Bellanger, J. J., Chauvel, P., and Bartolomei, F. Interictal to ictal transition in human temporal lobe epilepsy: insights from a computational model of intracerebral EEG. J. Clin. Neurophysiol., 22(5), 343–56 (2005).Google Scholar
Freestone, D. R., Karoly, P. J., Nešić, D., et al. Estimation of effective connectivity via data-driven neural modeling. Front. Neurosci., 8, 383 (2014).CrossRefGoogle ScholarPubMed
Stephan, K. E., Tittgemeyer, M., Knösche, T. R., Moran, R. J., and Friston, K. J. Tractography-based priors for dynamic causal models. Neuroimage, 47(4), 1628–38 (2009).Google Scholar
Raj, A., Kuceyeski, A., and Weiner, M. A network diffusion model of disease progression in dementia. Neuron, 73(6), 1204–15 (2012).CrossRefGoogle ScholarPubMed
Young, A.L., Oxtoby, N.P., Daga, P., et al. A data-driven model of biomarker changes in sporadic Alzheimer’s disease. Brain, 137(9), 2564–77 (2014).CrossRefGoogle ScholarPubMed
Wu, X., and Ma, J. J. Sodium valproate: Quantitative EEG and serum levels in volunteers and epileptics. Clin. Electroencephalogr., 24(2), 93–9 (1993).Google Scholar
Pardoe, Heath R., Berg, Anne T., and Jackson, Graeme D. Sodium valproate use is associated with reduced parietal lobe thickness and brain volume. Neurology, 80(20), 1895–1900 (2013).Google Scholar
Alberti, P., and Cavaletti, G. Management of side effects in the personalized medicine era: chemotherapy-induced peripheral neuropathy. In Pharmacogenomics in Drug Discovery and Development. New York, NY: Humana Press. 2014. pp. 301–22.Google Scholar
Cook, M. J., Karoly, P. J., Freestone, D. R., et al. Human focal seizures are characterized by populations of fixed duration and interval. Epilepsia, 57(3), 359–68 (2016).Google Scholar
Bazil, C. W., and Walczak, T.S. Effects of sleep and sleep stage on epileptic and nonepileptic seizures. Epilepsia, 38(1), 56–62 (1997).Google Scholar
Karoly, Philippa J., Nurse, Ewan S., Freestone, Dean R., et al. Bursts of seizures in long‐term recordings of human focal epilepsy. Epilepsia 58(3), 363–72 (2017).Google Scholar
Ewell, L.A., Liang, L., Armstrong, C., et al. Brain state is a major factor in preseizure hippocampal network activity and influences success of seizure intervention. J. Neurosci., 35(47), 15635–48 (2015).Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×