Spike-threshold adaptation predicted by membrane potential dynamics in vivo.
Spike-threshold adaptation predicted by membrane potential dynamics in vivo.
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DOI：
10.1371/journal.pcbi.1003560
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发表时间：
2014-04
影响因子：
4.3
通讯作者：
Brette R
中科院分区：
文献类型：
--
作者：
Fontaine B;Peña JL;Brette R
神经元以脉冲序列编码信息，当它们的膜电位越过一个阈值时，脉冲序列就会被触发。在体内，峰值阈值表现出很大的可变性，这表明阈值动态对神经元的组合输入如何在峰值中编码有深远的影响。阈值变异性可以通过对膜电位的适应来解释。然而，也可能是大多数阈值可变性反映了噪声和过程，而不是阈值适应。在此，我们研究了仓鸮听觉神经元反应的阈值变化。我们发现尖峰阈值可以通过一个阈值自适应的模型来定量预测，在短时间尺度上跟踪膜电位。因此，在这些神经元中，缓慢的电压波动不会导致尖峰，因为它们被阈值适应过滤了。更重要的是，这些神经元只能在毫秒的时间尺度上对同时到达的输入尖峰做出反应。这些结果表明，对膜电位的快速适应捕获了体内峰值阈值的变异性。当神经元的膜电位超过一个阈值时，神经元会出现峰值，但在体内记录的同一神经元中，这个阈值是可变的。这种可变性可能反映了噪声，或使阈值随膜电位变化的确定性过程。第二种选择将产生重要的功能后果。在这里，我们发现阈值变异性是神经元的真实特征，它反映了在短时间尺度上对膜电位的适应，而噪声的影响很小。这表明，确定性模型可以仅基于膜电位预测峰值。
Neurons encode information in sequences of spikes, which are triggered when their membrane potential crosses a threshold. In vivo, the spiking threshold displays large variability suggesting that threshold dynamics have a profound influence on how the combined input of a neuron is encoded in the spiking. Threshold variability could be explained by adaptation to the membrane potential. However, it could also be the case that most threshold variability reflects noise and processes other than threshold adaptation. Here, we investigated threshold variation in auditory neurons responses recorded in vivo in barn owls. We found that spike threshold is quantitatively predicted by a model in which the threshold adapts, tracking the membrane potential at a short timescale. As a result, in these neurons, slow voltage fluctuations do not contribute to spiking because they are filtered by threshold adaptation. More importantly, these neurons can only respond to input spikes arriving together on a millisecond timescale. These results demonstrate that fast adaptation to the membrane potential captures spike threshold variability in vivo. Neurons spike when their membrane potential exceeds a threshold value, but this value has been shown to be variable in the same neuron recorded in vivo. This variability could reflect noise, or deterministic processes that make the threshold vary with the membrane potential. The second alternative would have important functional consequences. Here, we show that threshold variability is a genuine feature of neurons, which reflects adaptation to the membrane potential at a short timescale, with little contribution from noise. This demonstrates that a deterministic model can predict spikes based only on the membrane potential.
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DOI：
10.1523/jneurosci.1840-10.2010
发表时间：
2010-09-08
期刊：
The Journal of neuroscience : the official journal of the Society for Neuroscience
影响因子：
--
作者：
Howard MA;Rubel EW
通讯作者：
Rubel EW
影响因子：
4.3
作者：
Angelino, Elaine;Brenner, Michael P.
通讯作者：
Brenner, Michael P.
DOI：
10.1523/jneurosci.4064-11.2011
发表时间：
2011-11-09
期刊：
The Journal of neuroscience : the official journal of the Society for Neuroscience
影响因子：
--
作者：
Grubb MS;Shu Y;Kuba H;Rasband MN;Wimmer VC;Bender KJ
通讯作者：
Bender KJ
影响因子：
4.3
作者：
Brette R
通讯作者：
Brette R
DOI：
10.1073/pnas.130200797
发表时间：
2000-07-05
影响因子：
11.1
作者：
Azouz, R;Gray, CM
通讯作者：
Gray, CM