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Ion Channel Stochasticity May Be Critical in Determining the Reliability and Precision of Spike Timing

机译:离子通道随机性可能对确定尖峰定时的可靠性和精度至关重要

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摘要

The firing reliability and precision of an isopotential membrane patch consisting of a realistically large number of ion channels is investigated using a stochastic Hodgkin-Huxley (HH) model. In sharp contrast to the deterministic HH model, the biophysically inspired stochastic model reproduces qualitatively the different reliability and precision characteristics of spike firing in response to DC and fluctuating current input in neocortical neurons, as reported by Mainen & Sejnowski (1995). For DC inputs, spike timing is highly unreliable; the reliability and precision are significantly increased for fluctuating current input. This behavior is critically determined by the relatively small number of excitable channels that are opened near threshold for spike firing rather than by the total number of channels that exist in the membrane patch. Channel fluctuations, together with the inherent bistability in the HH equations, give rise to three additional experimentally observed phenomena: subthreshold oscillations in the membrane voltage for DC input, “spontaneous” spikes for subthreshold inputs, and “missing” spikes for suprathreshold inputs. We suggest that the noise inherent in the operation of ion channels enables neurons to act as “smart” encoders. Slowly varying, uncorrelated inputs are coded with low reliability and accuracy and, hence, the information about such inputs is encoded almost exclusively by the spike rate. On the other hand, correlated presynaptic activity produces sharp fluctuations in the input to the postsynaptic cell, which are then encoded with high reliability and accuracy. In this case, information about the input exists in the exact timing of the spikes. We conclude that channel stochasticity should be considered in realistic models of neurons.
机译:使用随机Hodgkin-Huxley(HH)模型研究了由大量实际离子通道组成的等电位膜片的发射可靠性和精度。与确定性HH模型形成鲜明对比的是,根据Mainen&Sejnowski(1995)的报道,从生物物理上启发的随机模型定性地再现了尖峰脉冲响应DC和新皮质神经元电流输入波动的不同可靠性和精确度特征。对于直流输入,尖峰时序非常不可靠。波动的电流输入大大提高了可靠性和精度。这种行为是由相对较少数量的可激发通道(在接近尖峰发射的阈值附近打开)而不是由膜片中存在的通道总数决定的。通道波动以及HH方程中固有的双稳态,会引起另外三个实验观察到的现象:直流输入的膜电压出现亚阈值振荡,亚阈值输入出现“自发”尖峰,而亚阈值输入出现“缺失”尖峰。我们建议离子通道运行中固有的噪声使神经元能够充当“智能”编码器。缓慢变化的不相关输入以低可靠性和准确性进行编码,因此,有关此类输入的信息几乎全部由尖峰速率编码。另一方面,相关的突触前活动在突触后细胞的输入中产生急剧的波动,然后以高可靠性和准确性对其进行编码。在这种情况下,有关输入的信息存在于尖峰的准确时序中。我们得出结论,在现实的神经元模型中应考虑通道随机性。

著录项

  • 来源
    《Neural computation》 |1998年第7期|1679-1703|共25页
  • 作者单位

    Department of Neurobiology, Institute of Life Sciences, Institute of Computer Science, and Center for Neural Computation, Hebrew University, Jerusalem 91904, Israel;

  • 收录信息 美国《科学引文索引》(SCI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
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