Resolving the Micro-Macro Disconnect to Address Core Features of Seizure Networks

Farrell Jordan S.; Quynh-Anh Nguyen; Soltesz Ivan

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Resolving the Micro-Macro Disconnect to Address Core Features of Seizure Networks

机译：解析微型宏脱离连接以解决癫痫发作网络的核心特征

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Current drug treatments for epilepsy attempt to broadly restrict excitability to mask a symptom, seizures, with little regard for the heterogeneous mechanisms that underlie disease manifestation across individuals. Here, we discuss the need for a more complete view of epilepsy, outlining how key features at the cellular and microcircuit level can significantly impact disease mechanisms that are not captured by the most common methodology to study epilepsy, electroencephalography (EEG). We highlight how major advances in neuroscience tool development now enable multi-scale investigation of fundamental questions to resolve the currently controversial understanding of seizure networks. These findings will provide essential insight into what has emerged as a disconnect between the different levels of investigation and identify new targets and treatment options.

机译：目前癫痫的药物治疗试图大概限制兴奋性掩盖症状，癫痫发作，几乎没有考虑到个体疾病表现的异质机制。在这里，我们讨论了更完整的癫痫视图，概述了细胞和微电路水平的关键特征如何显着影响疾病机制，这些方法不会被最常见的方法研究癫痫，脑电图（EEG）。我们强调了神经科学工具开发的主要进步现已使多规模调查对基本问题进行多规模调查，以解决目前对癫痫发作网络的争议理解。这些调查结果将对在不同级别的调查和识别新目标和治疗方面之间的脱离的东西中提供必要的洞察力。

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《Neuron》 |2019年第6期|共13页
作者
Farrell Jordan S.; Quynh-Anh Nguyen; Soltesz Ivan;
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Stanford Univ Dept Neurosurg Stanford CA 94305 USA;

Stanford Univ Dept Neurosurg Stanford CA 94305 USA;

Stanford Univ Dept Neurosurg Stanford CA 94305 USA;

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原文格式 PDF
正文语种 eng
中图分类神经病学;
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1. Resolving the Micro-Macro Disconnect to Address Core Features of Seizure Networks [J] . Farrell Jordan S., Quynh-Anh Nguyen, Soltesz Ivan Neuron . 2019,第6期

机译：解析微型宏脱离连接以解决癫痫发作网络的核心特征
2. Automatic epileptic seizure detection in EEGs based on line length feature and artificial neural networks. [J] . Guo L, Rivero D, Dorado J, Journal of Neuroscience Methods . 2010,第1期

机译：基于线长特征和人工神经网络的脑电图癫痫发作自动检测。
3. Evolution of functional connectivity in contact and force chain networks: Feature vectors, k-cores and minimal cycles [évolution de connectivité fonctionnelle des réseaux de contact et de chaines de force] [J] . Tordesillas A., OSullivan P., Walker D.M., Comptes rendus. Mecanique . 2010,第10a11期

机译：接触和力链网络中功能连接的演变：特征向量，k核和最小周期[接触和力链网络中功能连接的演变]
4. Derivation of a Micro-Macro Link for Collective Decision-Making Systems Uncover Network Features Based on Drift Measurements [C] . Heiko Hamann, Gabriele Valentini, Yara Khaluf, International conference on parallel problem solving from nature . 2014

机译：集体决策系统的微宏链接的推导揭示了基于漂移测量的网络特征
5. Multi-Feature Analysis of Eeg Signal on Seizure Patterns and Deep Neural Structures for Prediction of Epileptic Seizures [D] . Ma, Xinyuan. 2020

机译：癫痫发作模式和深神经结构对癫痫癫痫发作预测的多种特征分析
6. Micro-Macro Analysis of Complex Networks [O] . Massimo Marchiori, Lino Possamai 2015

机译：复杂网络的微观分析
7. The micro-macro disconnect of purchasing power parity [O] . Paul R. Bergin, Reuven Glick, Jyh-Lin Wu 100

机译：购买力平价的微观宏观脱节
8. Epileptic Seizures from Abnormal Networks: Why Some Seizures Defy Predictability. [R] . Anderson, W. S., Azhar, F., Kudela, P., 2011

机译：异常网络的癫痫发作：为什么有些癫痫发作会破坏可预测性。

Resolving the Micro-Macro Disconnect to Address Core Features of Seizure Networks

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