Modeling the nonlinear properties of the in vitro hippocampal perforant path-dentate system using multielectrode array technology
Modeling the nonlinear properties of the in vitro hippocampal perforant path-dentate system using multielectrode array technology
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DOI：
10.1109/tbme.2007.908075
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发表时间：
2008-02-01
影响因子：
4.6
通讯作者：
Berger, Theodore W.
中科院分区：
文献类型：
--
作者：
Dimoka, Angelika;Courellis, Spiros H.;Berger, Theodore W.
提出了一种描述海马齿状回非线性动态变化的建模方法，并进行了实验验证。齿状回是海马中最先通过穿通通路接收和整合感觉信息的区域，穿通通路由两条不同的通路组成：1）外侧通路和2）内侧穿通通路，本文采用非参数的三阶Poisson-Volterra模型来研究和捕捉这两条通路的短期动力学特征。这两个途径的非线性特征是由Poisson-Volterra核，这是非线性动力学变换的定量描述符。核计算与实验数据从体外海马脑片。用定制的多电极阵列测量电生理活动，该阵列允许用随机脉冲序列进行选择性刺激并同时记录胞外场电位活动。结果表明，这种数学上严格的方法是适合的多途径复杂的海马，并产生可解释的模型，具有良好的预测能力。所得到的模型不仅准确地预测先前报道的电生理描述符，如成对脉冲，但更重要的是，可以用来预测齿状颗粒细胞的电生理活动，以任意的刺激模式在穿孔路径。
A modeling approach to characterize the nonlinear dynamic transformations of the dentate gyrus of the hippocampus is presented and experimentally validated. The dentate gyrus is the first region of the hippocampus which receives and integrates sensory information via the perforant path. The perforant path is composed of two distinct pathways: 1) the lateral path and 2) the medial perforant path. The proposed approach examines and captures the short-term dynamic characteristics of these two pathways using a nonparametric, third-order Poisson-Volterra model. The nonlinear characteristics of the two pathways are represented by Poisson-Volterra kernels, which are quantitative descriptors of the nonlinear dynamic transformations. The kernels were computed with experimental data from in vitro hippocampal slices. The electrophysiological activity was measured with custom-made multielectrode arrays, which allowed selective stimulation with random impulse trains and simultaneous recordings of extracellular field potential activity. The results demonstrate that this mathematically rigorous approach is suitable for the multipathway complexity of the hippocampus and yields interpretable models that have excellent predictive capabilities. The resulting models not only accurately predict previously reported electrophysiological descriptors, such as paired pulses, but more important, can be used to predict the electrophysiological activity of dentate granule cells to arbitrary stimulation patterns at the perforant path.