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Journals / Journal of Neurological Sciences (Turkish) / 2015 / Cilt: 32 - Sayı: 2

Interhemisferik Korelasyon ve Epileptik Nöbetler Arasında Bir İlişki Var mı? Retrospektif Ön Çalışma

Interhemispheric Correlation and Epileptic Seizures: Are They Related? A Preliminary Retrospective Study

Onur BAYAZIT
Sabiha TÜRE
Galip AKHAN
Sibel ATLI KOCAASLAN
Pages
361–371
Publication Date
2022-10-19
DOI
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Thevariability of the correlation coefficients between windows was analyzed with RepeatedMeasures of ANOVA.Results: Pearson correlation coefficients decreased significantly from the 1st window to the10th window in the following electrode pairs: F7T1-F8T2; T1T3-T2T4; FP1F3- FP2F4;C3P3-C4P4 (p

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Objective & Hypothesis:Objectives: For the purpose of predicting seizure activities in focal temporal lobe epilepsy weexamined interhemispheric correlation coefficients in pre-ictal EEG data.Materials and Methods: We used video-EEG data obtained from the İzmir Katip ÇelebiUniversity Atatürk Training and Research Hospital Neurology Department database toconduct preliminary retrospective analyses. 31 patients (mean age 32.3 ± 7.6; 17 female)diagnosed with focal temporal lobe epilepsy in 2010-2013 were randomly selected and a totalof 52 seizures were analyzed. 20 sec pre-ictal EEG data were studied for each seizure.
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Key Findings & Data:Inorder to observe the change in the correlation coefficients 20 sec pre-ictal EEG data weredivided into 10 windows (each 2 sec).
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Conclusion & Impact:Thevariability of the correlation coefficients between windows was analyzed with RepeatedMeasures of ANOVA.Results: Pearson correlation coefficients decreased significantly from the 1st window to the10th window in the following electrode pairs: F7T1-F8T2; T1T3-T2T4; FP1F3- FP2F4;C3P3-C4P4 (p
🔬Design:Research Article
📍Scope:2010-2013 Verileri
⚙️Variables:Domain Parameters

Abstract

Objectives: For the purpose of predicting seizure activities in focal temporal lobe epilepsy weexamined interhemispheric correlation coefficients in pre-ictal EEG data.Materials and Methods: We used video-EEG data obtained from the İzmir Katip ÇelebiUniversity Atatürk Training and Research Hospital Neurology Department database toconduct preliminary retrospective analyses. 31 patients (mean age 32.3 ± 7.6; 17 female)diagnosed with focal temporal lobe epilepsy in 2010-2013 were randomly selected and a totalof 52 seizures were analyzed. 20 sec pre-ictal EEG data were studied for each seizure. Inorder to observe the change in the correlation coefficients 20 sec pre-ictal EEG data weredivided into 10 windows (each 2 sec). The furthest window to the seizure was labeled as 1st window, the closest window to the seizure was labeled as 10th window. InterhemisphericPearson correlation coefficients were computed for each window in 9 electrode pairs. Thevariability of the correlation coefficients between windows was analyzed with RepeatedMeasures of ANOVA.Results: Pearson correlation coefficients decreased significantly from the 1st window to the10th window in the following electrode pairs: F7T1-F8T2; T1T3-T2T4; FP1F3- FP2F4;C3P3-C4P4 (p

Özet

Amaç: Fokal temporal lob epilepsisinde, nöbet aktivitesinin önceden kestirimini yapabilmekamacıyla nöbet öncesi EEG verisinde interhemisferik korelasyon katsayılarının incelenmesiamaçlanmıştır.Gereç ve Yöntem: Bu retrospektif ön çalışmada İzmir Katip Çelebi Üniversitesi TıpFakültesi Atatürk Eğitim ve Araştırma Hastanesi Nöroloji Anabilim Dalı video-EEGveritabanından alınan veriler kullanılmıştır. 2010 -2013 yılları arasında fokal temporal lobepilepsi tanısı almış hastalardan 31 tanesi rastgele seçilmiş (ortalama yaş 32.3 ± 7.6; 17 kadın)ve toplam 52 nöbet verisi analiz edilmiştir. Herbir nöbet için nöbet öncesi 20 s'lik EEG verisianaliz edilmiştir. Korelasyon katsayılarındaki değişimi gözlemek için nöbet öncesi 20 s'likEEG verisi herbiri 2s olan 10 pencereye bölünerek incelenmiştir. Nöbete en uzak olan pencere1. pencere , nöbete en yakın pencere ise 10. pencere olarak işaretlenmiştir. Herbir pencereiçin, 9 elektot çiftinde interhemisferik Pearson korelasyon katsayıları hesaplanmıştır.Pencereler arasında korelasyon katsayılarının değişkenliği tekrarlayan ölçümlerde ANOVAyöntemi ile analiz edilmiştir.Bulgular: F7T1-F8T2; T1T3-T2T4; FP1F3- FP2F4; C3P3-C4P4 elektrot çiftlerinde Pearsonkorelasyon katsayıları 1. pencereden 10. pencereye doğru anlamlı düşme göstermiştir(p

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Cite This Article

BAYAZIT, O., TÜRE, S., AKHAN, G., KOCAASLAN, S. A. (2022). Interhemisferik Korelasyon ve Epileptik Nöbetler Arasında Bir İlişki Var mı? Retrospektif Ön Çalışma. Journal of Neurological Sciences (Turkish), Cilt: 32 - Sayı: 2, 361–371. https://ajindex.com/articles/564953

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References (1)

  1. Abdelhalim K, Smolyakov V, Genov R. Phase- synchronization early ep ilep tic seizure detector VLSI architecture. IEEE Trans Biomed Circuits Syst 2011; 5(5): 430- 8 2. Biçer Gömceli Y. Patient selection f or ep ilepsy surgery. Türkiye Klinikleri J Surg Med Sci 2007; 3(16): 1- 5 3. Bilir E, Leventoğlu A. Tedaviye dirençli ep ilepsiler. In: Ep ilepsi. Ed's, Bora İ, Yeni SN, Gürses C, Nobel Tıp Kitabevleri, 2008, pp: 397- 408 4. Çine N, Sargin G, Bebek N, et al. Association of MDR1 gene p olymorp hism in p atients with temp oral lobe ep ilepsy. J Neurol Sci-Turk 2013; 30(1): 4-11 5. Feldwisch-Drentrup H, Staniek M, Schulze-Bonhage A, et al. Identif ication of p reseizure states in ep ilepsy: a data-driven app roach f or multichannel EEG recordings. Front Comp ut Neurosci 2011; 5: 32 7. Fisher RS, Scharf man HE, deCurtis M. How can we identify ictal and interictal abnormal activity ? Adv Exp Med Biol 2014; 813: 3-23 8. Grasse D W, Karunakaran S, Moxon KA. Neuronal synchrony and the transition to sp ontaneous seizures. Exp Neurol 2013; 248: 72-84 9. Güldiken B, Baykan B, Süt N, Bebek N, Gürses C, Gökyiğit A. The evaluation of the agreements of diff erent ep ilepsy classif ications in seizures recorded with video EEG monitoring. J Neurol Sci- Turk 2012; 29: 201- 11 10. Hauser WA, Annegers JF, and Rocca WA. Descrip tive ep idemiology of ep ilepsy: contributions of p op ulation-based studies f rom Rochester, Minnesota. Mayo Clin Proc 1996; 71: 576- 86 11. Hively LM. Detecting dynamical change in nonlinear time series. Phys Lett 1999; 258: 103- 14 12. Kaya M. Nöronal uyarılabilirliğin kontrolü. In: Ep ilepsi. Ed's, Bora İ, Yeni SN, Gürses C, Nobel Tıp Kitabevleri, 2008, pp: 15- 27 13. Kutlu G. Skalp uzun süreli video-EEG monitorizasyon. Türkiye Klinikleri J Surg Med Sci 2007; 3(16): 6-9 14. Lerner DE. Monitoring changing dynamics with correlation integrals: Case study of an ep ilep tic seizure. Physica D 1996; 97: 563-76 15. Litt B, Esteller R, Echauz J, et al. Ep ilep tic seizures may begin hours in advance of clinical onset: a rep ort of f ive p atients. Neuron 2001; 30: 51- 64 16. Luders HO. Textbook of Ep ilepsy Surgery. CRC Press, 2008, pp:232 17. Martinerie JJ, Adam C, Quyen ML V, et al. Ep ilep tic seizures can be anticip ated by non-linear analysis. Nat Med 1998; 4(10): 1173- 6 18. McSharry PE, Smith LA, and Tarassenko L. Comp arison of p redictability of ep ilep tic seizures by a linear and a nonlinear method. IEEE Trans Biomed Eng 2003; 50(5)