Attachment Preference in Auditory German Sentences: Individual Differences and Pragmatic Strategy

Abstract

Relative clauses modify a preceding element, but as this element can be flexibly located, the point of attachment is sometimes ambiguous. Preference for this attachment can vary within languages such as German, yet explanations for differences in attachment preference related to cognitive strategies or constraints have been conflicting in the current literature. The present study aimed to assess the preference for relative clause attachment among German listeners and whether these preferences could be explained by strategy or individual differences in working memory or musical rhythm ability. We performed a sentence completion experiment, conducted post hoc interviews, and measured working memory and rhythm abilities with diagnostic tests. German listeners had no homogeneous attachment preference, although participants consistently completed individual sentences across trials according to the general preference that they reported offline. Differences in attachment preference were moreover not linked to individual differences in either working memory or musical rhythm ability. However, the pragmatic content of individual sentences sometimes overrode the general syntactic preference in participants with lower rhythm ability. Our study makes an important contribution to the field of psycholinguistics by validating offline self-reports as a reliable diagnostic for an individual’s online relative clause attachment preference. The link between pragmatic strategy and rhythm ability is an interesting direction for future research.

A preliminary fMRI study of relative clause in comprehension among native and non-native Malay language speakers

“…Therefore, we postulated that the Malay SRC was easier to comprehend than ORC by L1 and L2. The current finding has concurred with the previous research in the language which has SVO word order such as English (Pliatsikas et al, 2017), and language that has free word order such as Basque (Arantzeta et al, 2017) and German (Harding et al, 2019).…”

“…ISSN: 2576-828X et al, 2019). They have used various neuroimaging modalities, such as the electroencephalogram (EEG) (Harding et al, 2019;Xiong & Newman, 2021), with event-related potential (ERP) and functional magnetic resonance imaging (fMRI) (Lee et al, 2016;Xu et al, 2020a), to examine the neural substrate underlying the sentence comprehension process. From those neuroimaging techniques, the researchers have found the involvement of frontal and temporal brain regions (Bulut et al, 2018;Xu et al, 2020b).…”

The syntax-meter interface in spoken language and music: Same, different, or individually variable?

“…Native listeners typically have implicit preferences for syntactic well-formedness in both language (Chomsky, 1957; Harding, Sammler, & Kotz, 2019) and music (Lerdahl & Jackendoff, 1983; Rohrmeier & Rebuschat, 2012). For example, in language, a relative clause (in italics, ‘The boss of the bus drivers who went on strike crossed the street’) can ambiguously modify two different nouns (boss or bus drivers) with both options being grammatical.…”

“…This perhaps explains why WM differences are seldom reported in music syntax studies, where musician participants may be clustered at high WM capacity (see Yurgil et al, 2020 for a review on musical training and working memory). Musical ability is also reported to influence cross-domain syntactic processing (Harding, Sammler, & Kotz, 2019; Menon, 2016) as well as the detection of metrical properties in language (Magne et al, 2007; Marie et al, 2011) and music (Geiser et al, 2010). Syntax and meter processing are also influenced by individual differences in temporal perception, because temporal perception may relate to better neural tracking of stimuli that evolve over time (Harding, Sammler, Henry, et al, 2019; Skoe & Kraus, 2010) — with benefits for metrical and syntactic processing (Ding et al, 2015).…”

Similarity Analysis of Learning Interests among Majors Using Complex Networks

“…The number of majors with a larger specialty degree was greater than that with a smaller specialty degree in the network, and the connection condition (degree number) between two major nodes had a serious uneven distribution. Therefore, the similarity network of group learning interest among majors could be characterized as a preference attachment model [29]. In the future, we should strengthen major construction and constantly promote cross-integration of all disciplines.…”