Nishimoto Shinji, Ishida Tsugitaka, Ohzawa Izumi
Graduate School of Frontier Biosciences, Osaka University, Osaka 560-8531, Japan.
J Neurosci. 2006 Mar 22;26(12):3269-80. doi: 10.1523/JNEUROSCI.4558-05.2006.
We introduce a novel class of white-noise analyses, named local spectral reverse correlation (LSRC), which is capable of revealing various aspects of visual receptive field profiles that were undetectable previously in a single simple measurement. The method is based on spectral analyses in a two-dimensional spatial frequency domain for spatially localized areas within and around their receptive fields. Extracellular single-unit recordings were performed for area 17 and 18 neurons in anesthetized cats. A dynamic dense noise pattern was presented in which the pattern covered an area two to three times larger than the classical receptive field. Spike trains were then cross-correlated with frequency spectra of localized noise pattern to obtain spatially localized selectivity maps in the two-dimensional frequency domain. Our findings are as follows. (1) The new LSRC method allows measurements of two-dimensional frequency tunings and their spatial extent even for cells with substantial nonlinearity. (2) A small subset of neurons shows spatial inhomogeneity in the two-dimensional frequency tunings. (3) In addition to facilitatory response profiles, we can also visualize suppressive profiles localized both in space and spatial frequency domains. Our results suggest that the new analysis technique can be a powerful tool for measuring visual response profiles that contain inhomogeneity in space, as well as for studying neurons with substantial nonlinearities. These features make the method particularly suitable for studying response profiles of neurons in early as well as intermediate extrastriate visual areas.
我们引入了一类全新的白噪声分析方法，称为局部频谱反向相关（LSRC），它能够揭示视觉感受野轮廓的各个方面，而这些方面在之前的单一简单测量中是无法检测到的。该方法基于对感受野及其周围空间局部区域在二维空间频率域中的频谱分析。对麻醉猫的17区和18区神经元进行了细胞外单单位记录。呈现了一种动态密集噪声模式，其中该模式覆盖的区域比经典感受野大两到三倍。然后将脉冲序列与局部噪声模式的频谱进行互相关，以在二维频率域中获得空间局部选择性图。我们的研究结果如下：（1）新的LSRC方法即使对于具有显著非线性的细胞，也能测量二维频率调谐及其空间范围。（2）一小部分神经元在二维频率调谐中表现出空间不均匀性。（3）除了易化反应轮廓外，我们还可以可视化在空间和空间频率域中定位的抑制性轮廓。我们的结果表明，这种新的分析技术可以成为测量包含空间不均匀性的视觉反应轮廓的强大工具，以及研究具有显著非线性的神经元的有力工具。这些特性使得该方法特别适合研究早期和中级纹外视觉区域中神经元的反应轮廓。
