Multidimensional encoding strategy of spiking neurons
Multidimensional encoding strategy of spiking neurons
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DOI：
10.1162/089976600300015240
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发表时间：
2000-07-01
影响因子：
2.9
通讯作者：
Wilke, SD
中科院分区：
文献类型：
--
作者：
Eurich, CW;Wilke, SD
感觉系统中的神经反应通常由多种刺激特征触发。利用信息论，我们研究了随机尖峰神经元群体的编码准确性，这些神经元的特征是针对不同特征的不同调谐宽度。最准确地表示一个特征的最佳编码策略包括在要编码的维度上的窄调谐，以增加单神经元Fisher信息，以及在所有其他维度上的宽调谐，以增加活跃神经元的数量。没有足够的感受野重叠的极窄调谐将严重恶化编码。这意味着存在用于待编码特征的最佳调谐宽度。根据经验，只有所有刺激特征的子集通常是可访问的。在这种情况下，可以计算相对编码误差，其基于测量的调谐曲线产生神经群体的功能的标准。
Neural responses in sensory systems are typically triggered by a multitude of stimulus features. Using information theory, we study the encoding accuracy of a population of stochastically spiking neurons characterized by different tuning widths for the different features. The optimal encoding strategy for representing one feature most accurately consists of narrow tuning in the dimension to be encoded, to increase the single-neuron Fisher information, and broad tuning in all other dimensions, to increase the number of active neurons. Extremely narrow tuning without sufficient receptive field overlap will severely worsen the coding. This implies the existence of an optimal tuning width for the feature to be encoded. Empirically, only a subset of all stimulus features will normally be accessible. In this case, relative encoding errors can be calculated that yield a criterion for the function of a neural population based on the measured tuning curves.