Trends Cogn Sci. 1997 Oct;1(7):252-61. doi: 10.1016/S1364-6613(97)01079-6.
The ease with which highly developed brains can generate representations of a virtually unlimited diversity of perceptual objects indicates that they have developed very efficient mechanisms to analyse and represent relations among incoming signals. Here, we propose that two complementary strategies are applied to cope with these combinatorial problems. First, elementary relations are represented by the tuned responses of individual neurons that acquire their specific response properties (feature selectivity) through appropriate convergence of input connections in hierarchically structured feed-forward architectures. Second, complex relations that cannot be represented economically by the responses of individual neurons are represented by assemblies of cells that are generated by dynamic association of individual, featureselective cells. The signature identifying the responses of an assembly as components of a coherent code is thought to be the synchronicity of the respective discharges. The compatibility of this hypothesis is examined in the context of recent data on the dynamics of synchronization phenomena, the dependence of synchronization on central states and the relations between the synchronization behaviour of neurons and perception.
高度发达的大脑能够轻松生成几乎无限多样的感知对象的表象,这表明它们已经发展出非常有效的机制来分析和表示传入信号之间的关系。在这里,我们提出了两种互补的策略来应对这些组合问题。首先,基本关系是通过在分层结构的前馈架构中适当汇聚输入连接,由个体神经元的调谐反应来表示的,这些神经元通过输入连接的适当汇聚获得其特定的反应特性(特征选择性)。其次,不能通过单个神经元的反应经济地表示的复杂关系,是由通过个体、特征选择性细胞的动态关联生成的细胞集合来表示的。被认为是相干代码组件的集合反应的特征是各自放电的同步性。在最近关于同步现象动力学、同步对中枢状态的依赖性以及神经元的同步行为与感知之间关系的数据背景下,检验了这一假设的兼容性。