Model-based analysis and control of a network of basal ganglia spiking neurons in the normal and parkinsonian states.
Model-based analysis and control of a network of basal ganglia spiking neurons in the normal and parkinsonian states.
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DOI：
10.1088/1741-2560/8/4/045002
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发表时间：
2011-08
影响因子：
4
通讯作者：
Oweiss KG
中科院分区：
文献类型：
--
作者：
Liu J;Khalil HK;Oweiss KG
在许多应用中，通过微刺激控制错综复杂连接的神经元网络的时空放电模式是非常期望的。本文研究了利用基于模型的方法通过微刺激分析和控制基底神经节（BG）Hodgkin-Huxley（HH）尖峰神经元网络模型的可行性。对该网络模型的详细分析表明，它可以再现正常和病理性帕金森病状态下BG神经元的实验观察特征。一个简化的神经元放电率模型，确定从详细的HH网络模型，捕捉基本的网络动态。数学分析的简化模型揭示了网络的结构和时空模式的微刺激的动态响应之间的系统关系的存在。我们表明，网络突触组织和微刺激的局部机制都可以对微刺激网络可能产生的时空放电模式施加严格限制，这可能会阻碍微刺激在某些条件下实现预期目标的有效性。最后，我们证明了反馈控制设计的数学分析的简化模型的辅助下，确实是有效的驱动BG网络在正常和Parskinsonian状态，按照规定的时空发射模式。我们进一步表明，多巴胺耗尽BG网络的特征的节奏/振荡模式可以被抑制作为控制的输出苍白球internalis（GPi）的神经元在网络中的一个亚群的时空模式的直接后果。这项工作可能提供合理的解释的机制，脑深部电刺激（DBS）在PD的治疗效果，并铺平了道路，以模型为基础，网络级分析和闭环控制和优化DBS参数，以及许多其他应用。
Controlling the spatiotemporal firing pattern of an intricately connected network of neurons through microstimulation is highly desirable in many applications. We investigated in this paper the feasibility of using a model-based approach to the analysis and control of a Basal Ganglia (BG) network model of Hodgkin–Huxley (HH) spiking neurons through microstimulation. Detailed analysis of this network model suggests that it can reproduce the experimentally observed characteristics of BG neurons under a normal and a pathological Parkinsonian state. A simplified neuronal firing rate model, identified from the detailed HH network model, is shown to capture the essential network dynamics. Mathematical analysis of the simplified model reveals the presence of a systematic relationship between the network’s structure and its dynamic response to spatiotemporally patterned microstimulation. We show that both the network synaptic organization and the local mechanism of microstimulation can impose tight constraints on the possible spatiotemporal firing patterns that can be generated by the microstimulated network, which may hinder the effectiveness of microstimulation to achieve a desired objective under certain conditions. Finally, we demonstrate that the feedback control design aided by the mathematical analysis of the simplified model is indeed effective in driving the BG network in the normal and Parskinsonian states to follow a prescribed spatiotemporal firing pattern. We further show that the rhythmic/oscillatory patterns that characterize a dopamine-depleted BG network can be suppressed as a direct consequence of controlling the spatiotemporal pattern of a subpopulation of the output Globus Pallidus internalis (GPi) neurons in the network. This work may provide plausible explanations for the mechanisms underlying the therapeutic effects of Deep Brain Stimulation (DBS) in PD and pave the way towards a model-based, network level analysis and closed-loop control and optimization of DBS parameters, among many other applications.
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影响因子：
3.7
作者：
Eldawlatly, Seif;Oweiss, Karim G.
通讯作者：
Oweiss, Karim G.
影响因子：
4.8
作者：
Baker, Kenneth B.;Kopell, Brian H.;Rezai, Ali R.
通讯作者：
Rezai, Ali R.
影响因子：
2.5
作者：
BERGMAN, H;WICHMANN, T;DELONG, MR
通讯作者：
DELONG, MR
影响因子：
2.5
作者：
Butovas, S;Schwarz, C
通讯作者：
Schwarz, C
影响因子：
64.8
作者：
de la Rocha, Jaime;Doiron, Brent;Reyes, Alex
通讯作者：
Reyes, Alex