Fractional differentiation by neocortical pyramidal neurons.
Fractional differentiation by neocortical pyramidal neurons.
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DOI：
10.1038/nn.2212
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发表时间：
2008-11
影响因子：
25
通讯作者：
Fairhall, Adrienne L.
中科院分区：
文献类型：
--
作者：
Lundstrom, Brian N.;Higgs, Matthew H.;Spain, William J.;Fairhall, Adrienne L.
神经系统适应刺激统计的变化。然而，它是不知道如何刺激与复杂的时间动态驱动的动态适应和由此产生的放电率。对于单个神经元，人们通常认为适应具有单一的时间尺度。在这里，我们表明，单一的大鼠新皮层锥体神经元适应的时间尺度，这取决于刺激统计的变化的时间尺度。这种多时间尺度适应与分数阶微分一致，使得神经元的放电速率是缓慢变化的刺激参数的分数阶导数。在生物学上，即使神经元的分数分化有效地产生适应与许多时间尺度，我们发现，它的实施只需要几个，适当平衡的已知的自适应机制。分数微分为单个神经元提供了一个基本的和通用的计算，可以有助于有效的信息处理，刺激预期，和振荡神经元放电的频率无关的相移。
Neural systems adapt to changes in stimulus statistics. However, it is not known how stimuli with complex temporal dynamics drive the dynamics of adaptation and the resulting firing rate. For single neurons, it has often been assumed that adaptation has a single time scale. Here, we show that single rat neocortical pyramidal neurons adapt with a time scale that depends on the time scale of changes in stimulus statistics. This multiple time scale adaptation is consistent with fractional order differentiation, such that the neuron’s firing rate is a fractional derivative of slowly varying stimulus parameters. Biophysically, even though neuronal fractional differentiation effectively yields adaptation with many time scales, we find that its implementation requires only a few, properly balanced known adaptive mechanisms. Fractional differentiation provides single neurons with a fundamental and general computation that can contribute to efficient information processing, stimulus anticipation, and frequency independent phase shifts of oscillatory neuronal firing.
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影响因子：
5.3
作者：
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