Program in Neural Computation, Carnegie Mellon University Pittsburgh, PA, USA ; Center for the Neural Basis of Cognition Pittsburgh, PA, USA.
Front Comput Neurosci. 2013 Aug 21;7:113. doi: 10.3389/fncom.2013.00113. eCollection 2013.
Synchronization plays an important role in neural signal processing and transmission. Many hypotheses have been proposed to explain the origin of neural synchronization. In recent years, correlated noise-induced synchronization has received support from many theoretical and experimental studies. However, many of these prior studies have assumed that neurons have identical biophysical properties and that their inputs are well modeled by white noise. In this context, we use colored noise to induce synchronization between oscillators with heterogeneity in both phase-response curves and frequencies. In the low noise limit, we derive novel analytical theory showing that the time constant of colored noise influences correlated noise-induced synchronization and that oscillator heterogeneity can limit synchronization. Surprisingly, however, heterogeneous oscillators may synchronize better than homogeneous oscillators given low input correlations. We also find resonance of oscillator synchronization to colored noise inputs when firing frequencies diverge. Collectively, these results prove robust for both relatively high noise regimes and when applied to biophysically realistic spiking neuron models, and further match experimental recordings from acute brain slices.
同步在神经信号处理和传输中起着重要作用。许多假说被提出以解释神经同步的起源。近年来,相关噪声诱导的同步得到了许多理论和实验研究的支持。然而,这些先前的研究大多假设神经元具有相同的生理特性,并且它们的输入可以很好地用白噪声来建模。在这种情况下,我们使用有色噪声来诱导相位响应曲线和频率都存在异质性的振荡器之间的同步。在低噪声极限下,我们推导出了新的解析理论,表明有色噪声的时间常数会影响相关噪声诱导的同步,并且振荡器的异质性会限制同步。然而,令人惊讶的是,在输入相关性较低的情况下,异构振荡器可能比同质振荡器同步得更好。当发射频率发散时,我们还发现振荡器同步对有色噪声输入的共振。总的来说,这些结果在相对较高的噪声环境下以及应用于生物物理上逼真的尖峰神经元模型时都是稳健的,并且与急性脑切片的实验记录相匹配。