Edin Fredrik, Machens Christian K, Schütze Hartmut, Herz Andreas V M
Institute for Theoretical Biology, Humboldt Universität zu Berlin, Invalidenstr. 43, 10115 Berlin, Germany.
J Comput Neurosci. 2004 Jul-Aug;17(1):47-56. doi: 10.1023/B:JCNS.0000023868.18446.a2.
Shaped by evolutionary processes, sensory systems often represent behaviorally relevant stimuli with higher fidelity than other stimuli. The stimulus dependence of neural reliability could therefore provide an important clue in a search for relevant sensory signals. We explore this relation and introduce a novel iterative algorithm that allows one to find stimuli that are reliably represented by the sensory system under study. To assess the quality of a neural representation, we use stimulus reconstruction methods. The algorithm starts with the presentation of an initial stimulus (e.g. white noise). The evoked spike train is recorded and used to reconstruct the stimulus online. Within a closed-loop setup, this reconstruction is then played back to the sensory system. Iterating this procedure, the newly generated stimuli can be better and better reconstructed. We demonstrate the feasibility of this method by applying it to auditory receptor neurons in locusts. Our data show that the optimal stimuli often exhibit pronounced sub-threshold periods that are interrupted by short, yet intense pulses. Similar results are obtained for simple model neurons and suggest that these stimuli are encoded with high reliability by a large class of neurons.
受进化过程影响，感觉系统通常比其他刺激更准确地呈现与行为相关的刺激。因此，神经可靠性对刺激的依赖性可能为寻找相关感觉信号提供重要线索。我们探讨了这种关系，并引入了一种新颖的迭代算法，该算法可让人们找到在所研究的感觉系统中得到可靠表征的刺激。为了评估神经表征的质量，我们使用刺激重建方法。该算法从呈现初始刺激（例如白噪声）开始。记录诱发的脉冲序列并用于在线重建刺激。在闭环设置中，然后将此重建结果反馈给感觉系统。重复此过程，新生成的刺激可以得到越来越好的重建。我们将此方法应用于蝗虫的听觉受体神经元，证明了该方法的可行性。我们的数据表明，最佳刺激通常表现出明显的阈下周期，这些周期被短暂但强烈的脉冲打断。简单模型神经元也得到了类似的结果，这表明这些刺激被一大类神经元以高可靠性编码。
