Firzlaff Uwe, Schörnich Sven, Hoffmann Susanne, Schuller Gerd, Wiegrebe Lutz
Department Biologie II, Ludwig-Maximilians-Universität München, D-82152 Planegg-Martinsried, Germany.
J Neurosci. 2006 Jan 18;26(3):785-91. doi: 10.1523/JNEUROSCI.3478-05.2006.
Bats quickly navigate through a highly structured environment relying on echolocation. Large natural objects in the environment, like bushes or trees, produce complex stochastic echoes, which can be characterized by the echo roughness. Previous work has shown that bats can use echo roughness to classify the stochastic properties of natural objects. This study provides both psychophysical and electrophysiological data to identify a neural correlate of statistical echo analysis in the bat Phyllostomus discolor. Psychophysical results show that the bats require a fixed minimum roughness of 2.5 (in units of base 10 logarithm of the stimulus fourth moment) for roughness discrimination. Electrophysiological results reveal a subpopulation of 15 of 94 recorded cortical units, located in an anterior region of auditory cortex, whose rate responses changed significantly with echo roughness. It is shown that the behavioral ability to discriminate differences in the statistics of complex echoes can be quantitatively predicted by the neural responses of this subpopulation of auditory-cortical neurons.
蝙蝠依靠回声定位在高度结构化的环境中快速导航。环境中的大型自然物体,如灌木丛或树木,会产生复杂的随机回声,其特征可以用回声粗糙度来描述。先前的研究表明,蝙蝠可以利用回声粗糙度对自然物体的随机特性进行分类。本研究提供了心理物理学和电生理学数据,以确定杂色叶口蝠对统计回声分析的神经关联。心理物理学结果表明,蝙蝠进行粗糙度辨别时需要固定的最小粗糙度为2.5(以刺激第四矩的常用对数为单位)。电生理学结果显示,在记录的94个皮层单元中,有15个位于听觉皮层前部区域的亚群,其放电率响应随回声粗糙度的变化而显著改变。研究表明,这种听觉皮层神经元亚群的神经反应可以定量预测蝙蝠辨别复杂回声统计差异的行为能力。