Subharmonic stochastic synchronization and resonance in neuronal systems
Subharmonic stochastic synchronization and resonance in neuronal systems
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DOI：
10.1103/physreve.65.050902
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发表时间：
2002-05-01
影响因子：
2.4
通讯作者：
Savino, GV
中科院分区：
文献类型：
--
作者：
Chialvo, DR;Calvo, O;Savino, GV
我们研究由噪声和至少两个弱周期信号同时驱动的模型神经元的响应。我们关注频率分量为 kf(o),(k+1)f(o),... (k+n)f(o) 且 k>1 的信号。神经子的输出是一系列以随机脉冲间隔间隔的脉冲。我们找到了一个最佳输入噪声强度，其输出脉冲的间隔类似于 1/f(o)，即，在输入中缺失的频率处存在随机共振 (SR)。即使噪声强度更高，也会在输入中存在的频率处发现额外但较弱的共振。这是 SR 的另一种形式，也是最稳健的。共振是一种增强频率的频率，输入中不存在这种频率，并且无法通过任何线性处理来恢复。这对于理解感觉系统（包括感知复杂音调的神经元机制）非常重要。
We study the response of,a model,neuron, driven simultaneously by noise and at least two weak periodic signals. We focus on signals with frequencies components kf(o),(k+1)f(o),... (k+n)f(o) with k>1. The neunon's, output is a sequence of pulses spaced,at random interpulse intervals. We find an optimum input noise intensity for which the output pulses are spaced similar to1/f(o), i.e., there is a stochastic resonance (SR) at a frequency missing in the,input. Even higher noise intensities, uncover additional, but weaker, resonances at frequencies present in the input. This is a different form of SR whereby the most robust. resonance is,the one enhancing a frequency, which is absent in the input, and which is not possible to recover via any linear processing. This can be important in understanding sensory systems including the neuronal mechanism for perception of complex tones.