The role of high-quality EEG databases in the improvement and assessment of seizure prediction methods

Epilepsy and Behavior

Volumn 22, Issue SUPPL. 1, 2011, Pages

  Schulze Bonhage, Andreas ^a,b   Feldwisch Drentrup, Hinnerk ^a,b   Ihle, Matthias ^a,b  

^a UNIVERSITY OF FREIBURG   (Germany)

^b UNIVERSITY OF FREIBURG   (Germany)

Author keywords

Database; Electroencephalography; Epilepsy; Long term recordings; Seizure prediction

Indexed keywords

CLINICAL ASSESSMENT; DATA BASE; ELECTROENCEPHALOGRAM; EUROPEAN UNION; HUMAN; MEDICAL RESEARCH; METHODOLOGY; PREDICTION; REVIEW; SEIZURE; SENSITIVITY ANALYSIS;

ALGORITHMS; DATABASES, FACTUAL; ELECTROENCEPHALOGRAPHY; FALSE POSITIVE REACTIONS; HUMANS; PREDICTIVE VALUE OF TESTS; SEIZURES; SENSITIVITY AND SPECIFICITY;

EID: 83455258126     PISSN: 15255050     EISSN: 15255069     Source Type: Journal    
DOI: 10.1016/j.yebeh.2011.08.030     Document Type: Review

References (48)

1. Brock C. Hirnströme. Eine Kulturgeschichte der Elektroencephalographie. Reihentitel: Wissenschaftsgeschichte; 2005.
2. Gotman J., Marciani M.G. Electroencephalographic spiking activity, drug levels and seizure occurrence in epileptic patients. Ann Neurol 1985, 17:597-603.
3. Aschenbrenner-Scheibe R., Maiwald T., Winterhalder M., et al. How well can epileptic seizure be predicted? An evaluation of a nonlinear method. Brain 2003, 126:2616-2626.
4. Rogowski Z., Gath I., Bental E. On the prediction of epileptic seizures. Biol Cybern 1981, 42:9-15.
5. Salant Y., Gath I., Henriksen O. Prediction of epileptic seizures from two-channel EEG. Med Biol Eng Comput 1998, 36:549-556.
6. Iasemidis L.D., Sackellares J.C., Zaveri H.P., Williams W.J. Phase space topography and the Lyapunov exponent of electrocorticograms in partial seizures. Brain Topogr 1990, 2:187-201.
7. Le Van Quyen M., Martinerie J., Baulac M., Varela F. Anticipating epileptic seizure in real time by a nonlinear analysis of similarity between EEG recordings. Neuroreport 1999, 10:2149-2155.
8. Lehnertz K., Elger C.E. Spatio-temporal dynamics of the primary epileptogenic area in temporal lobe epilepsy characterized by neuronal complexity loss. Electroencephalogr Clin Neurophysiol 1995, 95:108-117.
9. Martinerie J., Adam C., Le Van Quyen M., et al. Epileptic seizures can be anticipated by non-linear analysis. Nat Med 1998, 4:1173-1176.
10. Mormann F., Andrzejak R.G., Elger C.E., Lehnertz K. Seizure prediction: the long and winding road. Brain 2007, 130:314-333.
11. Andrzejak R.G., Mormann F., Kreuz T., et al. Testing the null hypothesis of the nonexistence of a preseizure state. Phys Rev E 2003, 67:010901.
12. Winterhalder M., Maiwald T., Voss H.U., Aschenbrenner-Scheibe R., Timmer J., Schulze-Bonhage A. The seizure prediction characteristic: a general framework to assess and compare seizure prediction methods. Epilepsy Behav 2003, 4:318-325.
13. Katz A., Marks D.A., McCarthy C., Spencer S.S. Does interictal spiking rate change prior to seizures?. Electroencephalogr Clin Neurophysiol 1991, 79:153-156.
14. Harrison M.A., Osorio I., Frei M.G., et al. Correlation dimension and integral do not predict epileptic seizures. Chaos 2005, 15:33106.
15. Lai Y.C., Harrison M.A., Frei M.G., Osorio I. Inability of Lyapunov exponents to predict epileptic seizures. Phys Rev Lett 2003, 91:068102.
16. Maiwald T., Winterhalder M., Aschenbrenner-Scheibe R., et al. Comparison of three non-linear seizure prediction algorithms by means of the seizure prediction characteristic. Phys D 2004, 194:357-368.
17. Andrzejak R.G., Chicharro D., Elger C.E., Mormann F. Seizure prediction: any better than chance?. Clin Neurophysiol 2009, 120:1465-1478.
18. Feldwisch-Drentrup H., Staniek M., Schulze-Bonhage A., et al. Identification of preseizure states in epilepsy: a data-driven approach for multichannel EEG recordings. Front Comp Neurosci 2011, 5:32.
19. Kreuz T., Andrzejak R.G., Mormann F., et al. Measure profile surrogates: a method to validate the performance of epileptic seizure prediction algorithms. Phys Rev E 2004, 69:061915.
20. Schelter B., Winterhalder M., Maiwald T., et al. Testing statistical significance of multivariate time series analysis techniques for epileptic seizure prediction. Chaos 2006, 16:013108.
21. Snyder D.E., Echauz J., Grimes D.B., Litt B. The statistics of a practical seizure warning system. J Neural Eng 2008, 5:392-401.
22. Wong S., Gardner A.B., Krieger A.M., Litt B. A stochastic framework for evaluating seizure prediction algorithms using hidden Markov models. J Neurophysiol 2007, 97:2525-2532.
23. Mormann F., Kreuz T., Rieke C., et al. On the predictability of epileptic seizures. Clin Neurophysiol 2005, 116:569-587.
24. Chaovalitwongse W., Iasemidis L.D., Pardalos P.M., et al. Performance of a seizure warning algorithm based on the dynamics of intracranial EEGs. Epilepsy Res 2005, 64:93-113.
25. Feldwisch-Drentrup H., Schulze-Bonhage A., Timmer J., Schelter B. Statistical validation of event predictors: a comparative study based on the field of seizure prediction. Phys Rev E 2011, 83:066704.
26. Kendall M.G. Rank correlation methods 1976, Griffin, London. 4th ed.
27. Stacey W, LeVanQuyen M, Mormann F, Schulze-Bonhage A. What is the present-day EEG evidence for a preictal state? Epilepsy Res, in press.
28. Sackellares J.C., Shiau D.S., Principe J.C., et al. Predictability analysis for an automated seizure prediction algorithm. J Clin Neurophysiol 2006, 23:509-520.
29. Schelter B., Feldwisch-Drentup H., Timmer J., et al. A common strategy and database to compare the performance of seizure prediction algorithms. Epilepsy Behav 2010, 17:154-156.
30. Lehnertz K., Litt B. The first international collaborative workshop on seizure prediction: summary and data description. Clin Neuropysiol 2005, 116:493-505.
31. Chau W., McIntosh A.R. The Talairach coordinate of a point in the MNI space: how to interpret it. Neuroimage 2005, 25:408-416.
32. Quigg M., Clayburn H., Straume M., et al. Effects of circadian regulation and rest-activity state on spontaneous seizures in a rat model of limbic epilepsy. Epilepsia 2000, 41:502-509.
33. Schelter B., Winterhalder M., Maiwald T., et al. Do false predictions of seizures depend on the state of vigilance? A report from two seizure-prediction methods and proposed remedies. Epilepsia 2006, 47:2058-2070.
34. Feldwisch-Drentrup H., Schelter B., Jachan M., et al. Joining the benefits: combining epileptic seizure prediction methods. Epilepsia 2010, 51:1598-1606.
35. Mirowski P., Madhavan D., LeCun Y., Kuzniecky R. Classification of patterns of EEG synchronization for seizure prediction. Clin Neurophysiol 2009, 120:1927-1940.
36. Zandi M.S., Irani S.R., Follows G., Moody A.M., Molyneux P., Vincent A. Limbic encephalitis associated with antibodies to the NMDA receptor in Hodgkin lymphoma. Neurology 2009, 73:2039-2040.
37. Zandi M.S., Irani S.R., Lang B., et al. Disease-relevant autoantibodies in first episode schizophrenia. J Neurol 2011, 258:686-688.
38. Kuhlmann L., Freestone D., Lai A., Burkitt A.N., Fuller K., Grayden D.B., Seiderer L., Vogrin S., Mareels I.M., Cook M.J. Patient-specific bivariate-synchrony-based seizure prediction for short prediction horizons. Epilepsy Res 2010, 91:214-231.
39. Minasyan G.R., Chatten J.B., Chatten M.J., Harner R.N. Patient-specific early seizure detection from scalp electroencephalogram. J Clin Neurophysiol 2010, 27:163-178.
40. Protopopescu V.A., Hively L.M., Gailey P.C. Epileptic event forewarning from scalp EEG. J Clin Neurophysiol 2001, 18:223-245.
41. Navarro V., Martinerie J., Le Van Quyen M., et al. Seizure anticipation in human neocortical epilepsy. Brain 2002, 125:640-655.
42. Mormann F., Andrzejak R.G., Kreuz T., et al. Automated detection of a preseizure state based on a decrease in synchronization in intracranial electroencephalogram recordings from epilepsy patients. Phys Rev 2003, 67:021912.
43. Niederhauser J.J., Esteller R., Echauz J., Vachtsevanos G., Litt B. Detection of seizure precursors from depth-EEG using a sign periodogram transform. IEEE Trans Biomed Eng 2003, 50:449-458.
44. Protopopescu V.A., Hively And L.M., Gailey P.C. Epileptic event forewarning from scalp EEG. J Clin Neurophysiol 2001, 18:223-245.
45. Esteller R., Eschauz J., D'Alessandro M., et al. Continuous energy variation during the seizure cycle: towards an online accumulated energy. Clin Neurophysiol 2005, 116:517-526.
46. Iasemidis L.D., Shiau D.S., Chaowolitwongse W., et al. Adaptive epileptic seizure prediction system. IEEE Trans Biomed Eng 2003, 15:616-627.
47. Iasemidis L.D., Shiau D.S., Pardalos P.M., et al. Long-term prospective online real-time seizure prediction. Clin Neurophysiol 2005, 116:532-544.
48. D'Alessandro M., Vachtsevanos G., Esteller R., et al. A multi-feature and multi-channel univariate selection process for seizure prediction. Clin Neurophysiol 2005, 116:505-516.