Reconstruction of Sensory Stimuli Encoded with Integrate-and-Fire Neurons with Random Thresholds.
Reconstruction of Sensory Stimuli Encoded with Integrate-and-Fire Neurons with Random Thresholds.
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DOI：
10.1155/2009/682930
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发表时间：
2009-05-25
影响因子：
1.9
通讯作者：
Pnevmatikakis EA
中科院分区：
文献类型：
--
作者：
Lazar AA;Pnevmatikakis EA
我们提出了一种通用的方法来重建带有随机阈值的泄漏积分与点火神经元编码的感觉刺激。激励被建模为再生核希尔伯特空间的元素。重建的基础是找到最小化正则化二次最优准则的刺激。我们详细地讨论了将感觉刺激建模为绝对连续函数以及具有绝对连续一阶导数的刺激的重构。给出了用单个神经元和一组神经元编码的刺激的重建结果。给出的例子说明了重建算法的性能作为阈值变化性的函数。
We present a general approach to the reconstruction of sensory stimuli encoded with leaky integrate-and-fire neurons with random thresholds. The stimuli are modeled as elements of a Reproducing Kernel Hilbert Space. The reconstruction is based on finding a stimulus that minimizes a regularized quadratic optimality criterion. We discuss in detail the reconstruction of sensory stimuli modeled as absolutely continuous functions as well as stimuli with absolutely continuous first-order derivatives. Reconstruction results are presented for stimuli encoded with single as well as a population of neurons. Examples are given that demonstrate the performance of the reconstruction algorithms as a function of threshold variability.
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