Toward a brain-based componential semantic representation

Abstract

Componential theories of lexical semantics assume that concepts can be represented by sets of features or attributes that are in some sense primitive or basic components of meaning. The binary features used in classical category and prototype theories are problematic in that these features are themselves complex concepts, leaving open the question of what constitutes a primitive feature. The present availability of brain imaging tools has enhanced interest in how concepts are represented in brains, and accumulating evidence supports the claim that these representations are at least partly "embodied" in the perception, action, and other modal neural systems through which concepts are experienced. In this study we explore the possibility of devising a componential model of semantic representation based entirely on such functional divisions in the human brain. We propose a basic set of approximately 65 experiential attributes based on neurobiological considerations, comprising sensory, motor, spatial, temporal, affective, social, and cognitive experiences. We provide normative data on the salience of each attribute for a large set of English nouns, verbs, and adjectives, and show how these attribute vectors distinguish a priori conceptual categories and capture semantic similarity. Robust quantitative differences between concrete object categories were observed across a large number of attribute dimensions. A within- versus between-category similarity metric showed much greater separation between categories than representations derived from distributional (latent semantic) analysis of text. Cluster analyses were used to explore the similarity structure in the data independent of a priori labels, revealing several novel category distinctions. We discuss how such a representation might deal with various longstanding problems in semantic theory, such as feature selection and weighting, representation of abstract concepts, effects of context on semantic retrieval, and conceptual combination. In contrast to componential models based on verbal features, the proposed representation systematically relates semantic content to large-scale brain networks and biologically plausible accounts of concept acquisition.

Close yet independent: Dissociation of social from valence and abstract semantic dimensions in the left anterior temporal lobe

“…Abstractness in the left superior ATL has been consistently reported in the literature (Binder et al, 2009;Wang et al, 2010). Abstract words differ from concrete words in a wide range of dimensions, including various types of semantic (e.g., higher loadings on social and emotional contents, lack of sensory referents) and linguistic features (e.g., heavier reliance on linguistic information; Barsalou & Wiemer-Hastings, 2005;Binder et al, 2016;Kousta et al, 2011;Paivio, 2013;Recchia & Jones, 2012;Wang et al, 2018). Researchers observing social effects in the ATL have speculated that the abstractness in the left ATL may be driven by the use of social words as abstract stimuli (Skipper et al, 2011;Zahn et al, 2007), that is, reflecting a social effect rather than an abstractness effect.…”

“…For stimulus selection, we collected ratings of 633 two-character Chinese nouns on the following three properties: Sociality (how often the meaning of a noun involves an interaction between people (Binder et al, 2016;Lin et al, 2015), 1 = never, 7 = always), valence (1 = negative, 4 = neutral, 7 = positive), and concreteness (1 = very abstract; 7 = very concrete). For stimulus selection, we collected ratings of 633 two-character Chinese nouns on the following three properties: Sociality (how often the meaning of a noun involves an interaction between people (Binder et al, 2016;Lin et al, 2015), 1 = never, 7 = always), valence (1 = negative, 4 = neutral, 7 = positive), and concreteness (1 = very abstract; 7 = very concrete).…”

“…We included an additional condition of concrete object words (e.g., "spoon") to test the relationship between sociality/valence and general abstractness effects. For stimulus selection, we collected ratings of 633 two-character Chinese nouns on the following three properties: Sociality (how often the meaning of a noun involves an interaction between people (Binder et al, 2016;Lin et al, 2015), 1 = never, 7 = always), valence (1 = negative, 4 = neutral, 7 = positive), and concreteness (1 = very abstract; 7 = very concrete). We recruited 26, 33, and 31 college students for the above ratings, respectively, and computed the mean ratings for each word.…”

“…Here, we focused on a specific type of "social" words, that is, those whose referents are meaningful in the context of interpersonal interactions (Binder et al, 2016;Lin, Bi, Zhao, Luo, & Li, 2015), to explicitly address the aspect of social interactions and to avoid the further confounding of additional semantic dimensions across conditions. We then tested the relationship between these dimensions and the welldocumented abstractness preference in the ATL (Binder, Desai, Graves, & Conant, 2009;Wang et al, 2010), given the discussion about whether the abstractness preference is in fact driven by sociality and/or valence (Kousta, Vigliocco, Vinson, Andrews, & Del Campo, 2011;Zahn et al, 2007).…”

A Study of Representational Similarity: The Emergence of Object Concepts in Rapid Serial Visual Presentation Streams

“…Consistent with the embodied view, evidence from neuroscience demonstrated that much of the conceptual knowledge associated with perception and action was represented and distributed in regions in the ventral and lateral temporal cortex that overlapped with neural substrates responsible for perceiving and acting (Binder et al, 2016;Barsalou, 2008;Martin, 2007;Martin & Chao, 2001;Humphreys & Price, 2002;Pulvermüller et al, 2005;Vigliocco et al, 2004). However, evidence from other neuroimaging studies also corroborated the Domain Specificity account.…”