Texture signals in whisker vibrations
Texture signals in whisker vibrations
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DOI：
10.1152/jn.01104.2005
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发表时间：
2006-03-01
影响因子：
2.5
通讯作者：
König, P
中科院分区：
文献类型：
--
作者：
Hipp, J;Arabzadeh, E;König, P
啮齿类动物擅长通过将胡须扫过表面来做出质地判断。在这里，我们的目标是识别出现在胡须振动中的信号，这些信号导致了如此精细的感官辨别。首先，我们使用传感器捕捉在人工系统主动搅拌期间金属晶须中的振动信号，以及在活体大鼠搅拌过程中天然晶须中的振动信号。然后我们开发了一种分类算法，成功地将单次试验的振动频谱与诱导它的纹理相匹配。对于人造胡须，算法在40%的试验中正确识别了八种备选方案中的一种纹理；对于活体天然胡须，算法在80%的试验中正确地识别了五种备选方案中的一种纹理。最后，我们询问了振动光谱的关键区分特征是什么。在人工和自然条件下，两种特征的组合提供了大部分信息：调制功率-代表纹理表面调制的晶须运动部分的功率-随着纹理的粗糙度而增加；调制质心-与功率谱中重心有关的度量-随着纹理的粗糙度而减小。事实上，将信号限制在这两个参数上会导致性能达到全光谱的四分之三。由于早期的工作表明调制功率和质心与胡须通路中的神经元反应直接相关，我们得出结论，生物系统最佳地提取振动特征来进行纹理分类。
Rodents excel in making texture judgments by sweeping their whiskers across a surface. Here we aimed to identify the signals present in whisker vibrations that give rise to such fine sensory discriminations. First, we used sensors to capture vibration signals in metal whiskers during active whisking of an artificial system and in natural whiskers during whisking of rats in vivo. Then we developed a classification algorithm that successfully matched the vibration frequency spectra of single trials to the texture that induced it. For artificial whiskers, the algorithm correctly identified one texture of eight alternatives on 40% of trials; for in vivo natural whiskers, the algorithm correctly identified one texture of five alternatives on 80% of trials. Finally, we asked which were the key discriminative features of the vibration spectra. Under both artificial and natural conditions, the combination of two features accounted for most of the information: The modulation power - the power of the part of the whisker movement representing the modulation due to the texture surface - increased with the coarseness of the texture; the modulation centroid - a measure related to the center of gravity within the power spectrum - decreased with the coarseness of the texture. Indeed, restricting the signal to these two parameters led to performance three-fourths as high as the full spectra. Because earlier work showed that modulation power and centroid are directly related to neuronal responses in the whisker pathway, we conclude that the biological system optimally extracts vibration features to permit texture classification.