Reducing the variability of neural responses: A computational theory of spike-timing-dependent plasticity
Reducing the variability of neural responses: A computational theory of spike-timing-dependent plasticity
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DOI：
10.1162/neco.2007.19.2.371
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发表时间：
2007-02-01
影响因子：
2.9
通讯作者：
Mozer, Michael C.
中科院分区：
文献类型：
--
作者：
Bohte, Sander M.;Mozer, Michael C.
实验研究观察到，当突触前神经元在突触后神经元之前不久放电时，突触增强；而当突触前神经元在突触后神经元之后不久放电时，突触抑制。突触调节对两个动作电位精确时间的依赖性被称为尖峰时间依赖性可塑性（STDP）。我们从一个简单的计算原理推导出 STDP：突触适应以最小化突触后神经元对给定突触前输入的响应变异性，从而使神经元的输出在面对噪声时变得更加可靠。使用最小化响应变异性的目标函数和 Gerstner (2001) 的生物物理现实尖峰响应模型，我们模拟神经生理学实验并获得特征 STDP 曲线以及其他现象，包括突触可塑性的降低随着突触功效的增加。我们将我们的解释与其他从计算原理推导出 STDP 的努力进行比较，并认为我们的解释提供了对现象最全面的覆盖。因此，面对噪声时神经反应的可靠性可能是无监督皮质适应的关键目标。
Experimental studies have observed synaptic potentiation when a presynaptic neuron fires shortly before a postsynaptic neuron and synaptic depression when the presynaptic neuron fires shortly after. The dependence of synaptic modulation on the precise timing of the two action potentials is known as spike-timing dependent plasticity (STDP). We derive STDP from a simple computational principle: synapses adapt so as to minimize the postsynaptic neuron's response variability to a given presynaptic input, causing the neuron's output to become more reliable in the face of noise.Using an objective function that minimizes response variability and the biophysically realistic spike-response model of Gerstner (2001), we simulate neurophysiological experiments and obtain the characteristic STDP curve along with other phenomena, including the reduction in synaptic plasticity as synaptic efficacy increases. We compare our account to other efforts to derive STDP from computational principles and argue that our account provides the most comprehensive coverage of the phenomena. Thus, reliability of neural response in the face of noise may be a key goal of unsupervised cortical adaptation.