Stimulus-Response Curves in Sensory Neurons: How to Find the Stimulus Measurable with the Highest Precision

Stimulus-Response Curves in Sensory Neurons: How to Find the Stimulus Measurable with the Highest Precision
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感觉神经元中的刺激响应曲线:如何以最高精度找到可测量的刺激

DOI:
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发表时间:
2007
期刊:
Brain, Vision, and Artificial Intelligence
影响因子:
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通讯作者:
J. Rospars
J. Rospars
中科院分区:
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文献类型:
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作者:
P. Lánský;O. Pokora;J. Rospars

文献摘要

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为了研究感觉神经元,我们绘制了神经元的反应与刺激水平的关系图。本研究的目的是根据刺激的诱发反应来确定两种不同水平的刺激在多大程度上可以区分开来。提出了噪声影响下响应函数的两种通用模型,并对其进行了研究。我们在这些嘈杂的情况下表明,从识别的角度来看,最合适的信号不是唯一的。为了获得最佳识别,我们建议使用基于Fisher信息的度量。对于这些测量,我们表明,最可识别的信号可能不同于当噪声被忽略时得出的信号。
To study sensory neurons, the neuron response is plotted versus stimulus level. The aim of the present contribution is to determine how well two different levels of the incoming stimulation can be distinguished on the basis of their evoked responses. Two generic models of response function are presented and studied under the influence of noise. We show in these noisy cases that the most suitable signal, from the point of view of its identification, is not unique. To obtain the best identification we propose to use measures based on Fisher information. For these measures, we show that the most identifiable signal may differ from that derived when the noise is neglected.