Electronic Resource
Low entropy map of brain oscillatory activity identifies spatially localized events: A new method for automated epilepsy focus prediction
| العنوان: | Low entropy map of brain oscillatory activity identifies spatially localized events: A new method for automated epilepsy focus prediction |
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| المؤلفون: | Universitat Politècnica de Catalunya. Departament de Física, Universitat Politècnica de Catalunya. BIOCOM-SC - Biologia Computacional i Sistemes Complexos, Principe, Alessandro, Tauste Campo, Adrián Francisco, Vila Vidal, Manel, Rocamora, Rodrigo, Deco, Gustavo, Pérez Enríquez, Carmen |
| بيانات النشر: | 2020-03 |
| نوع الوثيقة: | Electronic Resource |
| مستخلص: | The spatial mapping of localized events in brain activity critically depends on the correct identification of the pattern signatures associated with those events. For instance, in the context of epilepsy research, a number of different electrophysiological patterns have been associated with epileptogenic activity. Motivated by the need to define automated seizure focus detectors, we propose a novel data-driven algorithm for the spatial identification of localized events that is based on the following rationale: the distribution of emerging oscillations during confined events across all recording sites is highly non-uniform and can be mapped using a spatial entropy function. By applying this principle to EEG recording obtained from 67 distinct seizure epochs, our method successfully identified the seizure focus on a group of ten drug-resistant temporal lobe epilepsy patients (average sensitivity: 0.94, average specificity: 0.90) together with its characteristic electrophysiological pattern signature. Cross-validation of the method outputs with postresective information revealed the consistency of our findings in long follow-up seizure-free patients. Overall, our methodology provides a reliable computational procedure that might be used as in both experimental and clinical domains to identify the neural populations undergoing an emerging functional or pathological transition. Peer Reviewed Postprint (published version) |
| مصطلحات الفهرس: | Àrees temàtiques de la UPC::Ciències de la salut::Medicina::Neurologia, Àrees temàtiques de la UPC::Matemàtiques i estadística::Anàlisi matemàtica, Epilepsy, Convulsions, Nervous system--Diseases, Seizure onset zone, Intracranial EEG, Time-frequency analysis, Automated detection algorithms, Post-operative outcome, Epilèpsia, Sistema nerviós--Malalties, Article |
| URL: | info:eu-repo/grantAgreement/EC/H2020/785907/EU/Human Brain Project Specific Grant Agreement 2/HBP SGA2 |
| الاتاحة: | Open access content. Open access content Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0 Open Access |
| ملاحظة: | application/pdf English |
| Other Numbers: | HGF oai:upcommons.upc.edu:2117/380393 Principe, A. [et al.]. Low entropy map of brain oscillatory activity identifies spatially localized events: A new method for automated epilepsy focus prediction. "Neuroimage", Març 2020, vol. 208, núm. article 116410. 1053-8119 10.1016/j.neuroimage.2019.116410 1372981087 |
| المصدر المساهم: | UNIV POLITECNICA DE CATALUNYA From OAIster®, provided by the OCLC Cooperative. |
| رقم الانضمام: | edsoai.on1372981087 |
| قاعدة البيانات: | OAIster |
| الوصف غير متاح. |