Univ. of Bielefeld, AG Active Sensing, 33501 Bielefeld, Germany.
J Neurophysiol. 2012 May;107(10):2581-93. doi: 10.1152/jn.01073.2011. Epub 2012 Feb 29.
Fish and aquatic frogs detect minute water motion by means of a specialized mechanosensory system, the lateral line. Ubiquitous in fish, the lateral-line system is characterized by hair-cell based sensory structures across the fish's surface called neuromasts. These neuromasts occur free-standing on the skin as superficial neuromasts (SN) or are recessed into canals as canal neuromasts. SNs respond to rapid changes of water velocity in a small layer of fluid around the fish, including the so-called boundary layer. Although omnipresent, the boundary layer's impact on the SN response is still a matter of debate. For the first time using an information-theoretic approach to this sensory system, we have investigated the SN afferents encoding capabilities. Combining covariance analysis, phase analysis, and modeling of recorded neuronal responses of primary lateral line afferents, we show that encoding by the SNs is adequately described as a linear, velocity-responsive mechanism. Afferent responses display a bimodal distribution of opposite Wiener kernels that likely reflected the two hair-cell populations within a given neuromast. Using frozen noise stimuli, we further demonstrate that SN afferents respond in an extremely precise manner and with high reproducibility across a broad frequency band (10-150 Hz), revealing that an optimal decoder would need to rely extensively on a temporal code. This was further substantiated by means of signal reconstruction of spike trains that were time shifted with respect to their original. On average, a time shift of 3.5 ms was enough to diminish the encoding capabilities of primary afferents by 70%. Our results further demonstrate that the SNs' encoding capability is linearly related to the stimulus outside the boundary layer, and that the boundary layer can, therefore, be neglected while interpreting lateral line response of SN afferents to hydrodynamic stimuli.
鱼类和水生青蛙通过一种专门的机械感觉系统——侧线来探测微小的水动力。侧线系统在鱼类中无处不在，其特征是在鱼类表面有基于毛细胞的感觉结构，称为神经丘。这些神经丘有的独立于皮肤存在，称为浅表神经丘（SN），有的则陷入到管道中，称为管神经丘。SN 对鱼类周围小层流体中的水流速度的快速变化做出反应，包括所谓的边界层。尽管边界层无处不在，但它对 SN 反应的影响仍然存在争议。我们首次使用信息论方法研究了这个感觉系统，研究了 SN 传入神经的编码能力。通过对初级侧线传入神经的记录神经元反应进行协方差分析、相位分析和建模，我们表明 SN 的编码可以很好地描述为线性的、对速度有反应的机制。传入神经反应呈现出相反 Wiener 核的双峰分布，这可能反映了给定神经丘内的两种毛细胞群体。使用冻结噪声刺激，我们进一步证明 SN 传入神经在很宽的频率范围内（10-150 Hz）以极其精确和高重复性的方式做出反应，表明最佳解码器需要广泛依赖于时间码。通过相对于原始时间对 Spike 列车进行时间移位的信号重建进一步证实了这一点。平均而言，时间移位 3.5 ms 就足以使初级传入神经的编码能力降低 70%。我们的研究结果进一步表明，SN 的编码能力与边界层以外的刺激呈线性关系，因此在解释 SN 传入神经对水动力刺激的侧线反应时，可以忽略边界层。
