کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6014521 | 1185935 | 2011 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Computational model prospective on the observation of proictal states in epileptic neuronal systems
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علم عصب شناسی
علوم اعصاب رفتاری
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چکیده انگلیسی
Epilepsy is a pathological condition of the human central nervous system in which normal brain functions are impaired by unexpected transitions to states called seizures. We developed a lumped neuronal model that has the property of switching between two states as a result of intrinsic or extrinsic perturbations, such as noisy fluctuations. In one version of the model, seizure risk is controlled by a single connectivity parameter representing excitatory couplings between two model lumps. We show that this risk can be reconstructed from calculation of the cross-covariance between the activities of the two neural populations during the nonictal phase. In a second simulation sequence, we use a system of 10 interconnected lumps with randomly generated connectivity matrices. We show again that the tendency to develop seizures can be inferred from the cross-covariances calculated during the nonictal states. Our conclusion is that the risk of epileptic transitions in biological systems can be objectively quantified. This article is part of a Supplemental Special Issue entitled The Future of Automated Seizure Detection and Prediction.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Epilepsy & Behavior - Volume 22, Supplement 1, December 2011, Pages S102-S109
Journal: Epilepsy & Behavior - Volume 22, Supplement 1, December 2011, Pages S102-S109
نویسندگان
Stiliyan Kalitzin, Marcus Koppert, George Petkov, Demetrios Velis, F. Lopes da Silva,