Department of Psychology, Carnegie Mellon University, 5000Forbes Avenue, Pittsburgh, PA 15213-3890, USA.
Psychol Rev. 2010 Jan;117(1):284-8. doi: 10.1037/a0017101.
According to Bowers, the finding that there are neurons with highly selective responses to familiar stimuli supports theories positing localist representations over approaches positing the type of distributed representations typically found in parallel distributed processing (PDP) models. However, his conclusions derive from an overly narrow view of the range of possible distributed representations and of the role that PDP models can play in exploring their properties. Although it is true that current distributed theories face challenges in accounting for both neural and behavioral data, the proposed localist account--to the extent that it is articulated at all--runs into more fundamental difficulties. Central to these difficulties is the problem of specifying the set of entities a localist unit represents.
根据鲍尔斯的说法,发现神经元对熟悉的刺激有高度选择性的反应,这支持了局部表示的理论,而不是分布式表示的理论,通常在并行分布式处理 (PDP) 模型中发现。然而,他的结论源自对可能的分布式表示的范围以及 PDP 模型在探索其性质方面所能发挥的作用的过于狭隘的看法。虽然当前的分布式理论确实面临着解释神经和行为数据的挑战,但所提出的局部主义解释——就其表达而言——遇到了更多的基本困难。这些困难的核心是指定局部单位所表示的实体集的问题。