Cell to network computational model of the epileptic human hippocampus suggests specific roles of network and channel dysfunctions in the ictal and interictal oscillations.

IF 1.5 4区 医学 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY Journal of Computational Neuroscience Pub Date : 2022-11-01 DOI:10.1007/s10827-022-00829-5
Amélie Aussel, Radu Ranta, Olivier Aron, Sophie Colnat-Coulbois, Louise Maillard, Laure Buhry
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Abstract

The mechanisms underlying the generation of hippocampal epileptic seizures and interictal events and their interactions with the sleep-wake cycle are not yet fully understood. Indeed, medial temporal lobe epilepsy is associated with hippocampal abnormalities both at the neuronal (channelopathies, impaired potassium and chloride dynamics) and network level (neuronal and axonal loss, mossy fiber sprouting), with more frequent seizures during wakefulness compared with slow-wave sleep. In this article, starting from our previous computational modeling work of the hippocampal formation based on realistic topology and synaptic connectivity, we study the role of micro- and mesoscale pathological conditions of the epileptic hippocampus in the generation and maintenance of seizure-like theta and interictal oscillations. We show, through the simulations of hippocampal activity during slow-wave sleep and wakefulness that: (i) both mossy fiber sprouting and sclerosis account for seizure-like theta activity, (ii) but they have antagonist effects (seizure-like activity occurrence increases with sprouting but decreases with sclerosis), (iii) though impaired potassium and chloride dynamics have little influence on the generation of seizure-like activity, they do play a role on the generation of interictal patterns, and (iv) seizure-like activity and fast ripples are more likely to occur during wakefulness and interictal spikes during sleep.

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癫痫人类海马体的细胞到网络计算模型表明,网络和通道功能障碍在峰间振荡中起着特定的作用。
海马癫痫发作和间歇事件的发生机制及其与睡眠-觉醒周期的相互作用尚不完全清楚。事实上,内侧颞叶癫痫与海马在神经元(通道病变,钾和氯化物动力学受损)和网络水平(神经元和轴突丧失,苔藓状纤维发芽)上的异常有关,与慢波睡眠相比,清醒时癫痫发作更频繁。在本文中,我们从之前基于现实拓扑和突触连通性的海马形成的计算建模工作开始,研究了癫痫海马的微观和中尺度病理条件在癫痫样θ波和间期振荡的产生和维持中的作用。通过模拟慢波睡眠和清醒时的海马活动,我们发现:(i)苔藓纤维发芽和硬化症都是癫痫样θ活动的原因,(ii)但它们具有拮抗剂作用(癫痫样活动的发生随着发芽而增加,但随着硬化症而减少),(iii)尽管受损的钾和氯动力学对癫痫样活动的产生影响不大,但它们确实对发作间期模式的产生起作用。(iv)癫痫样活动和快速波动更有可能发生在清醒期间和睡眠期间的间歇尖峰。
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来源期刊
CiteScore
2.00
自引率
8.30%
发文量
32
审稿时长
3 months
期刊介绍: The Journal of Computational Neuroscience provides a forum for papers that fit the interface between computational and experimental work in the neurosciences. The Journal of Computational Neuroscience publishes full length original papers, rapid communications and review articles describing theoretical and experimental work relevant to computations in the brain and nervous system. Papers that combine theoretical and experimental work are especially encouraged. Primarily theoretical papers should deal with issues of obvious relevance to biological nervous systems. Experimental papers should have implications for the computational function of the nervous system, and may report results using any of a variety of approaches including anatomy, electrophysiology, biophysics, imaging, and molecular biology. Papers investigating the physiological mechanisms underlying pathologies of the nervous system, or papers that report novel technologies of interest to researchers in computational neuroscience, including advances in neural data analysis methods yielding insights into the function of the nervous system, are also welcomed (in this case, methodological papers should include an application of the new method, exemplifying the insights that it yields).It is anticipated that all levels of analysis from cognitive to cellular will be represented in the Journal of Computational Neuroscience.
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