Dementia Research Centre, Department of Neurodegenerative Disease, University College London, Institute of Neurology.
Neuropsychology Unit, IRCCS Fondazione Santa Lucia.
Cogn Sci. 2017 Apr;41(3):659-685. doi: 10.1111/cogs.12348. Epub 2016 Feb 22.
The Abstract Conceptual Feature (ACF) framework predicts that word meaning is represented within a high-dimensional semantic space bounded by weighted contributions of perceptual, affective, and encyclopedic information. The ACF, like latent semantic analysis, is amenable to distance metrics between any two words. We applied predictions of the ACF framework to abstract words using eyetracking via an adaptation of the classical "visual word paradigm" (VWP). Healthy adults (n = 20) selected the lexical item most related to a probe word in a 4-item written word array comprising the target and three distractors. The relation between the probe and each of the four words was determined using the semantic distance metrics derived from ACF ratings. Eye movement data indicated that the word that was most semantically related to the probe received more and longer fixations relative to distractors. Importantly, in sets where participants did not provide an overt behavioral response, the fixation rates were nonetheless significantly higher for targets than distractors, closely resembling trials where an expected response was given. Furthermore, ACF ratings which are based on individual words predicted eye fixation metrics of probe-target similarity at least as well as latent semantic analysis ratings which are based on word co-occurrence. The results provide further validation of Euclidean distance metrics derived from ACF ratings as a measure of one facet of the semantic relatedness of abstract words and suggest that they represent a reasonable approximation of the organization of abstract conceptual space. The data are also compatible with the broad notion that multiple sources of information (not restricted to sensorimotor and emotion information) shape the organization of abstract concepts. While the adapted "VWP" is potentially a more metacognitive task than the classical visual world paradigm, we argue that it offers potential utility for studying abstract word comprehension.
抽象概念特征（ACF）框架预测，单词的意义是在由感知、情感和百科全书信息的加权贡献所限定的高维语义空间中表示的。ACF 与潜在语义分析一样，适用于任何两个词之间的距离度量。我们通过对经典“视觉词范式”（VWP）的改编，使用眼动追踪将 ACF 框架的预测应用于抽象词。健康成年人（n=20）在一个由目标和三个干扰项组成的 4 项书面单词数组中，选择与探针词最相关的词汇项。探针与四个单词中的每一个的关系是通过从 ACF 评分中得出的语义距离度量来确定的。眼动数据表明，与探针最语义相关的词相对于干扰项收到了更多和更长的注视。重要的是，在参与者没有给出明显的行为反应的情况下，目标的注视率仍然明显高于干扰项，这与给出预期反应的情况非常相似。此外，基于单个单词的 ACF 评分至少与基于单词共现的潜在语义分析评分一样，可以很好地预测探针-目标相似性的眼动固定指标。这些结果进一步验证了从 ACF 评分中得出的欧几里得距离度量作为衡量抽象词语义相关性的一个方面的有效性，并表明它们代表了抽象概念空间组织的合理近似。这些数据也与这样一种广泛的观点一致，即多种信息源（不仅限于感觉运动和情感信息）塑造了抽象概念的组织。虽然改编的“VWP”比经典的视觉世界范式更具元认知任务，但我们认为它为研究抽象词理解提供了潜在的效用。
