Abstract:

Semantic unification is one of the core components of language production and comprehension. In this paper, the most relevant models about semantic unification were described, including multiple phases model (Friederici, 2002), Bilateral Activation, Integration and Selection model (BIAS) (Jung-Beeman, 2005), Memory, Unification and Control model (MUC) (Hagoort, 2005), N400 model (Lau, Phillips, & Poeppel, 2008). The issues at core of debate include the definition of semantic unification and the corresponding locus, as well as whether there is a linguistic specific unification locus. Following the BIAS model and the N400 model, semantic unification is apart from semantic selection and controlled processing. While according to MUC model, semantic unification refers to the process by which we construct complex meaning based on elementary semantic blocks (e.g. words). It relies on selection and inhibition due to the inherent ambiguity nature of language comprehension. However, selection is not always a prerequisite for semantic unification. Unification constructs semantic representation that is not already available in long-term memory. In addition, some information which should be unified is unique and does not engage selection. For instance, Tesink et al. (Tesink, et al., 2009) found left inferior frontal gyrus activation when content violated against character’s gender information as indicated by the acoustics of the voice (for example, a men said he was in pregnant), a situation unlikely relies on selection. In the future, it would be helpful to further investigate whether the activation in left inferior frontal gyrus during semantic unification is linguistic-specified or domain general. Since it was found that activation between semantic unification and general cognitive control such as flanker task induced control processing was overlap (Ye & Zhou, 2009). Moreover, cumulative evidence suggested that functional connected network rather than single region support cognition. Thus the field would be benefit from connectivity analysis for semantic unification. The connectivity network may involve the cortical and subcortical structures, and bilateral hemispheres.

摘要：

语义整合是语言阅读理解中非常重要的环节。随着认知神经科学技术的广泛应用，当前关于语义整合的研究取得了长足进步，各种模型层出不穷。但是不同模型对于语义整合的功能定位及其内在机制却存在较大的争议。本文首先介绍当前关于语义整合的主要模型，然后对当前不同理论模型之间关于语义整合的界定，以及语义整合的功能定位是在额下回还是颞叶的争论进行了分析。我们认为，关于语义整合的实质、语义整合的功能网络将是未来研究的主要方向，相关的研究对于语言理解理论的发展将具有重要的启示。