Neuronal oscillations and the rate-to-phase transform: mechanism, model and mutual information.
Neuronal oscillations and the rate-to-phase transform: mechanism, model and mutual information.
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DOI：
10.1113/jphysiol.2008.164111
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发表时间：
2009-02-15
期刊：
影响因子：
--
通讯作者：
Paulsen O
中科院分区：
文献类型：
--
作者：
McLelland D;Paulsen O
理论和实验研究表明，振荡加工模式在神经元计算中起着重要作用。一个很好的支持的想法是，在振荡期间的净兴奋性输入将被报告在点火阶段，一个“速率到相位变换”，并且该变换可能实现时间代码。在这里，我们调查的效率，这个代码在基本的单细胞计算的水平。首先，我们开发了一个通用的框架，用于理解由单个神经元实现的速率到相位变换。采用全细胞膜片钳技术记录离体大鼠海马锥体神经元，研究了在一定生理放电频率范围内，模拟θ频率（5 Hz）和γ频率（40 Hz）振荡时，紧张性兴奋与放电相位之间的关系。在θ频率振荡期间，每个周期的第一个尖峰的相位是紧张性兴奋的近线性函数，随着兴奋的增加，从振荡周期的峰值到谷值前进了整整180度。与此相反，这种关系是不明显的伽马振荡，在此期间的相位的发射几乎是独立的紧张性兴奋性输入的水平范围内的生理放电率。我们表明，一个简单的分析模型可以基本上捕捉到这种行为，使泛化到其他振荡状态和细胞类型。这种变换对信息进行编码的能力受到神经元活动的时间精度的限制。使用我们的整个细胞记录的数据，我们计算了有关放电速率或相位的输入信息，并发现相位编码明显更有效。因此，处理的时间模式可以使神经元编码固有地更有效，从而允许减少处理时间或所需神经元的数量。
Theoretical and experimental studies suggest that oscillatory modes of processing play an important role in neuronal computations. One well supported idea is that the net excitatory input during oscillations will be reported in the phase of firing, a ‘rate-to-phase transform’, and that this transform might enable a temporal code. Here, we investigate the efficiency of this code at the level of fundamental single cell computations. We first develop a general framework for the understanding of the rate-to-phase transform as implemented by single neurons. Using whole cell patch-clamp recordings of rat hippocampal pyramidal neurons in vitro, we investigated the relationship between tonic excitation and phase of firing during simulated theta frequency (5 Hz) and gamma frequency (40 Hz) oscillations, over a range of physiological firing rates. During theta frequency oscillations, the phase of the first spike per cycle was a near-linear function of tonic excitation, advancing through a full 180 deg, from the peak to the trough of the oscillation cycle as excitation increased. In contrast, this relationship was not apparent for gamma oscillations, during which the phase of firing was virtually independent of the level of tonic excitatory input within the range of physiological firing rates. We show that a simple analytical model can substantially capture this behaviour, enabling generalization to other oscillatory states and cell types. The capacity of such a transform to encode information is limited by the temporal precision of neuronal activity. Using the data from our whole cell recordings, we calculated the information about the input available in the rate or phase of firing, and found the phase code to be significantly more efficient. Thus, temporal modes of processing can enable neuronal coding to be inherently more efficient, thereby allowing a reduction in processing time or in the number of neurons required.
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影响因子：
1.6
作者：
Gautrais, J;Thorpe, S
通讯作者：
Thorpe, S
影响因子：
64.8
作者：
HOPFIELD, JJ
通讯作者：
HOPFIELD, JJ
影响因子：
3
作者：
NG, B;BARRY, PH
通讯作者：
BARRY, PH
影响因子：
5.5
作者：
BRYANT, HL;SEGUNDO, JP
通讯作者：
SEGUNDO, JP
DOI：
10.1073/pnas.0401125101
发表时间：
2004-04-20
影响因子：
11.1
作者：
Hopfield, JJ
通讯作者：
Hopfield, JJ