Morrison Robert G, Krawczyk Daniel C, Holyoak Keith J, Hummel John E, Chow Tiffany W, Miller Bruce L, Knowlton Barbara J
Department of Psychology, University of California, Los Angelesm 90095-1563, USA.
J Cogn Neurosci. 2004 Mar;16(2):260-71. doi: 10.1162/089892904322984553.
Analogy is important for learning and discovery and is considered a core component of intelligence. We present a computational account of analogical reasoning that is compatible with data we have collected from patients with cortical degeneration of either their frontal or anterior temporal cortices due to frontotemporal lobar degeneration (FTLD). These two patient groups showed different deficits in picture and verbal analogies: frontal lobe FTLD patients tended to make errors due to impairments in working memory and inhibitory abilities, whereas temporal lobe FTLD patients tended to make errors due to semantic memory loss. Using the "Learning and Inference with Schemas and Analogies" model, we provide a specific account of how such deficits may arise within neural networks supporting analogical problem solving.
类比对于学习和发现很重要，并且被认为是智力的核心组成部分。我们提出了一种类比推理的计算解释，该解释与我们从因额颞叶痴呆（FTLD）导致额叶或颞前叶皮质变性的患者那里收集到的数据相一致。这两组患者在图片和言语类比方面表现出不同的缺陷：额叶FTLD患者往往由于工作记忆和抑制能力受损而犯错，而颞叶FTLD患者往往由于语义记忆丧失而犯错。使用“基于图式和类比的学习与推理”模型，我们具体说明了在支持类比问题解决的神经网络中这些缺陷是如何产生的。
