Nelson T J
Biol Cybern. 1983;49(2):79-88. doi: 10.1007/BF00320388.
A consideration of the storage of information as an energized neuronal state leads to the development of a new type of neural network model which is capable of pattern recognition, concept formation and recognition of patterns of events in time. The network consists of several layers of cells, each cell representing by connections from the lower levels some combination of features or concepts. Information travels toward higher layers by such connections during an association phase, and then reverses during a recognition phase, where higher-order concepts can redirect the flow to more appropriate elements, revising the perception of the environment. This permits a more efficient method of distinguishing closely-related patterns and also permits the formation of negative associations, which is a likely requirement for formation of "abstract" concepts.
将信息存储视为一种活跃的神经元状态，由此发展出一种新型神经网络模型，该模型能够进行模式识别、概念形成以及及时识别事件模式。该网络由几层细胞组成，每个细胞通过与较低层级的连接来表示某些特征或概念的组合。在联想阶段，信息通过此类连接向更高层级传播，然后在识别阶段反向传播，在此阶段，高阶概念可将信息流重新导向更合适的元素，从而修正对环境的感知。这允许采用一种更有效的方法来区分密切相关的模式，还允许形成负向联想，这可能是形成“抽象”概念的必要条件。
