Schillen T B, König P
Max-Planck-Institut für Hirnforschung, Frankfurt, Germany.
Biol Cybern. 1994;70(5):397-405. doi: 10.1007/BF00203232.
An important step in visual processing is the segregation of objects in a visual scene from one another and from the embedding background. According to current theories of visual neuroscience, the different features of a particular object are represented by cells which are spatially distributed across multiple visual areas in the brain. The segregation of an object therefore requires the unique identification and integration of the pertaining cells which have to be "bound" into one assembly coding for the object in question. Several authors have suggested that such a binding of cells could be achieved by the selective synchronization of temporally structured responses of the neurons activated by features of the same stimulus. This concept has recently gained support by the observation of stimulus-dependent oscillatory activity in the visual system of the cat, pigeon and monkey. Furthermore, experimental evidence has been found for the formation and segregation of synchronously active cell assemblies representing different stimuli in the visual field. In this study, we investigate temporally structured activity in networks with single and multiple feature domains. As a first step, we examine the formation and segregation of cell assemblies by synchronizing and desynchronizing connections within a single feature module. We then demonstrate that distributed assemblies can be appropriately bound in a network comprising three modules selective for stimulus disparity, orientation and colour, respectively. In this context, we address the principal problem of segregating assemblies representing spatially overlapping stimuli in a distributed architecture. Using synchronizing as well as desynchronizing mechanisms, our simulations demonstrate that the binding problem can be solved by temporally correlated responses of cells which are distributed across multiple feature modules.
视觉处理中的一个重要步骤是将视觉场景中的物体彼此分离，并与周围背景分离。根据当前视觉神经科学理论，特定物体的不同特征由在大脑多个视觉区域空间分布的细胞来表征。因此，物体的分离需要对相关细胞进行独特识别和整合，这些细胞必须“绑定”到一个编码该物体的集合中。几位作者提出，细胞的这种绑定可以通过对由相同刺激特征激活的神经元的时间结构响应进行选择性同步来实现。这一概念最近得到了在猫、鸽子和猴子的视觉系统中观察到的刺激依赖性振荡活动的支持。此外，还发现了关于在视野中代表不同刺激的同步活动细胞集合的形成和分离的实验证据。在本研究中，我们研究了具有单个和多个特征域的网络中的时间结构活动。第一步，我们通过在单个特征模块内同步和去同步连接来检查细胞集合的形成和分离。然后我们证明，在一个分别对刺激视差、方向和颜色具有选择性的包含三个模块的网络中，可以适当地绑定分布式集合。在这种情况下，我们解决了在分布式架构中分离代表空间重叠刺激的集合的主要问题。利用同步和去同步机制，我们的模拟表明，绑定问题可以通过分布在多个特征模块中的细胞的时间相关响应来解决。
