Voutsas Kyriakos, Adamy Jürgen
Control Theory and Robotics Laboratory, Darmstadt University of Technology, Darmstadt 64283, Germany.
IEEE Trans Neural Netw. 2007 Nov;18(6):1785-99. doi: 10.1109/TNN.2007.899623.
In this paper, a binaural sound source lateralization spiking neural network (NN) will be presented which is inspired by most recent neurophysiological studies on the role of certain nuclei in the superior olivary complex (SOC) and the inferior colliculus (IC). The binaural sound source lateralization neural network (BiSoLaNN) is a spiking NN based on neural mechanisms, utilizing complex neural models, and attempting to simulate certain parts of nuclei of the auditory system in detail. The BiSoLaNN utilizes both excitatory and inhibitory ipsilateral and contralateral influences arrayed in only one delay line originating in the contralateral side to achieve a sharp azimuthal localization. It will be shown that the proposed model can be used both for purposes of understanding the mechanisms of an NN of the auditory system and for sound source lateralization tasks in technical applications, e.g., its use with the Darmstadt robotic head (DRH).
在本文中,将提出一种双耳声源定位脉冲神经网络(NN),其灵感来源于最近关于上橄榄复合体(SOC)和下丘(IC)中某些核团作用的神经生理学研究。双耳声源定位神经网络(BiSoLaNN)是一种基于神经机制的脉冲神经网络,利用复杂的神经模型,并试图详细模拟听觉系统核团的某些部分。BiSoLaNN利用仅起源于对侧的一条延迟线中排列的兴奋性和抑制性同侧和对侧影响,以实现精确的方位定位。结果将表明,所提出的模型既可以用于理解听觉系统神经网络的机制,也可以用于技术应用中的声源定位任务,例如与达姆施塔特机器人头部(DRH)一起使用。