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간질성 뇌파의 시공간 패턴 분석

간질성 뇌파의 시공간 패턴 분석. 김 정 애 , 한 승 기 충북대학교 물리학과 임 태 규 한국전자통신연구원 , 인체정보연구부 이 상 건 , 남 현 우 서울대학교병원 신경과. 간질 (Epilepsy) ?. 신경계의 변화에 의한 강한 발화 활동 - 신경세포의 과도한 발화 - 신경계의 변화에 의한 강한 동기화 : 흥분성 영향의 증가 , 억제성 영향의 감소 - 간질성 발작 거동 뇌파의 변화 , 뇌파 분석 간질 뇌파의 특징 추출 , 간질 발현 시간 예측 , 간질 위치 추정.

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간질성 뇌파의 시공간 패턴 분석

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  1. 간질성 뇌파의 시공간 패턴 분석 김 정 애 , 한 승 기 충북대학교 물리학과 임 태 규 한국전자통신연구원, 인체정보연구부 이 상 건 , 남 현 우 서울대학교병원 신경과 .

  2. 간질(Epilepsy) ? • 신경계의 변화에 의한 강한 발화 활동 • -신경세포의 과도한 발화 • -신경계의 변화에 의한 강한 동기화: 흥분성 영향의 증가, • 억제성 영향의 감소 • -간질성 발작 거동 • 뇌파의 변화, 뇌파 분석 • 간질 뇌파의 특징 추출, 간질 발현 시간 예측, 간질 위치 추정

  3. channel 16 17 18 19 20 11 12 13 14 15 6 7 8 9 10 30 29 1 2 3 4 5 28 26 25 24 23 22 21 Time(sec) 27 Interictal ictal Invasive EEG(Epileptic seizure) • 간질뇌파(서울대병원 간질센터) • Lateral Temporal Lobe Epilepsy(L-TLE) • Depth EEG • 32 channels, 200sec recording (interictal, ictal, postictal) • -5subject EEG Electrodes

  4. Spatio-temporal Pattern • Linear analysis: power spectrum -theta(3-7Hz), alpha(8-13Hz), beta(20-30Hz) • Statistical analysis: Jensen-Shannon divergence - amplitude, peak time, variance, kurtosis • Nonlinear analysis: mutual information -correlation time, correlation dimension • Temporal changes, spatial dependence • Correlations between different measures • Robustness of pattern: inter-trials

  5. Spectrum sum Total power 3~7hz 8~13hz 20~30hz Power ratio Power spectrum analysis(1): Frequency band: theta(3~7Hz), alpha(8~13Hz), beta(20~30Hz) • spectrum sum: theta, alpha, beta is localization • power ratio : -rhythm order : beta->alpha-> theta->total power

  6. Time map of beta spectrum sgo1 sgo2 sgo3 sgo4 sgo5 Time Power spectrum analysis: inter-trial variations

  7. 분석구간 Statistical analysis: • Change in statistical properties of amplitude distribution • boundary between two distributions? Jensen-Shannon divergence

  8. Statistical measures at JS-E maximum JS-E Kurt STD Temporal mapping of JS-E Plot of JS-divergence: • Time of change in amplitude distribution • Position of most dominant changes • Statistical measures

  9. Time map of JS-E sgo1 sgo2 sgo3 sgo4 sgo5 Time Plot of JS-divergence: inter-trial variations

  10. Average mutual information Nonlinear analysis • Nonlinear dynamics underlying the bursting neural activities • Nonlinear measures characterizing the temporal behaviors Mutual information

  11. Correlation time(m sec) channel Time(sec) Temporal mapping of correlation time Plot of correlation time: • decrease in the correlation time during ital period • no specific channel dependence • Variability of the spatial mapping

  12. Temporal maping of correlation time sgo1 sgo2 sgo3 sgo4 sgo5 Time Plot of correlation time:inter-trial variations

  13. sgo1 sgo2 sgo3 sgo4 sgo5 JS-E Beta Correl. time Comparison of temporal maps of JS-E , Beta, Correlation time • Partial overlapping between the temporal maps of JS-E and beta • No similarity with the temporal map of correlation time

  14. Correlation between inter-trials and different maps of JS-E, beta spectrum , and correlation time • High inter-trial correlations for JS-E and beta spectrum • Low inter-trial correlation for correlation time • Correlations between different maps are weak

  15. Neural network model of Epileptic seizure generation: CA3 in Hippocampus [Tateno,1998] • Pyramidal cell (Δ) - Inhibitory inter-neuron () • Field current - Synaptic current Iaf : 해마 외부에서 가해지는 tonic input

  16. 신경 모형계(16x16)의 시공간 발화 패턴 Cpp=0.001 Cpp=0.003 Cpp=0.005 Cpp=0.008 time

  17. STDP (Spike-Timing Dependent Plasticity) [G-q. Bi and M-m. Poo, 1998] Δt : tpost - tpre A+ : maximal synaptic strengthening A- : maximal synaptic weakening Normal hippocampus : A+ ~ A- Abnormal hippocampus : ?

  18. A+와 A-에 따른 신경모형계의 거동 변화 (2) gaf=0.005uS, CPI=0.02uS, CIP=0.02uS

  19. 결론 및 논의 • Spatio-temporal pattern analysis • Power spectrum : • - spatio-temporal pattern of beta rhythm is more informative • - lateral temporal lobe epilepsy is close to the hippocampus • - beta rhythm is generated in the hippocampus • JS-entropy : • - earlier rise of JS entropy in several channels • - the position of rises are consistent with diagnostic of the medical doctors • - the shape of distribution function, es. kurtosis : seizure generation • Mutual information :correlation time • - short correlation time for ictal rhythm • - non-specific map: no information on the localization • Neural network model of seizure generation: • - CA3 model + Spike-Timing Dependent Plasticity • - unbalance between synaptic strengthening and weakining

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