Wilson et al. focus on one class of AGL tasks: the cognitively demanding task of detecting non‐adjacent dependencies (NADs) among items. They provide a typology of the different types of NADs in natural languages and in AGL tasks. A range of cues affect NAD learning, ranging from the variability and number of intervening elements to the presence of shared prosodic cues between the dependent items. These cues, important for humans to discover non‐adjacent dependencies, are also found to facilitate NAD learning (...) in several nonhuman animal species. (shrink)

Wilson et al. focus on one class of AGL tasks: the cognitively demanding task of detecting non‐adjacent dependencies (NADs) among items. They provide a typology of the different types of NADs in natural languages and in AGL tasks. A range of cues affect NAD learning, ranging from the variability and number of intervening elements to the presence of shared prosodic cues between the dependent items. These cues, important for humans to discover non‐adjacent dependencies, are also found to facilitate NAD learning (...) in several nonhuman animal species. (shrink)

Recent scholarship emphasizes the scaffolding role of language for cognition. Language, it is claimed, is a cognition-enhancing niche ( Clark, 2006 ), a programming tool for cognition ( Lupyan and Bergen, 2016 ), even neuroenhancement ( Dove, 2019 ) and augments cognitive functions such as memory, categorization, cognitive control, and meta-cognitive abilities (“thinking about thinking”). Yet, the notion that language enhances or augments cognition, and in particular, cognitive control does not easily fit in with embodied approaches to language processing, or (...) so we will argue. Accounts aiming to explain how language enhances various cognitive functions often employ a notion of abstract representation. Yet, embodied approaches to language processing have it that language processing crucially, according to some accounts even exclusively, involves embodied, modality-specific, i.e., non-abstract representations. In coming to understand a particular phrase or sentence, a prior experience has to be simulated or reenacted. The representation thus activated is embodied (modality-specific) as sensorimotor regions of the brain are thereby recruited. In this paper, we will first discuss the notion of representation, clarify what it takes for a representation to be embodied or abstract, and distinguish between conceptual and (other) linguistic representations. We will then put forward a characterization of cognitive control and examine its representational infrastructure. The remainder of the paper will be devoted to arguing that language augments cognitive control. To that end, we will draw on two lines of research, which investigate how language augments cognitive control: (i) research on the availability of linguistic labels and (ii) research on the active usage of a linguistic code, specifically, in inner speech. Eventually, we will argue that the cognition-enhancing capacity of language can be explained once we assume that it provides us with (a) abstract, non-embodied representations and with (b) abstract, sparse linguistic representations that may serve as easy-to-manipulate placeholders for fully embodied or otherwise more detailed representations. (shrink)

The ability to process center‐embedded structures has been claimed to represent a core function of the language faculty. Recently, several studies have investigated the learning of center‐embedded dependencies in artificial grammar settings. Yet some of the results seem to question the learnability of these structures in artificial grammar tasks. Here, we tested under which exposure conditions learning of center‐embedded structures in an artificial grammar is possible. We used naturally spoken syllable sequences and varied the presence of prosodic cues. The results (...) suggest that mere distributional information does not suffice for successful learning. Prosodic cues marking the boundaries of the major relevant units, however, can lead to learning success. Thus, our data are consistent with the hypothesis that center‐embedded syntactic structures can be learned in artificial grammar tasks if language‐like acoustic cues are provided. (shrink)

Mueller et al. discuss the role of acoustic cues in detecting language structure more generally. Across languages, there are clear links between acoustic cues and syntactic structure. They show that AGL experiments implementing analogous links demonstrate that prosodic cues, as well as various auditory biases, facilitate the learning of structural rules. Some of these biases, e.g. for auditory grouping, are also present in other species.

In order to memorize sentences we use both processes of language comprehension during encoding and processes of language production during maintenance. While the former processes are easily testable via controlled presentation of the input, the latter are more difficult to assess directly as language production is typically initiated and controlled internally. In the present event-related potential (ERP) study we track subvocal rehearsal of sentences, with the goal of studying the concomitant planning processes with the help of a silent cued-production task. (...) Native German participants read different types of sentences word-by-word, then were prompted by a visual cue to silently repeat each individual word, in a rehearsal phase. In order to assess both local and global effects of sentence planning, we presented correct sentences, syntactically or semantically violated sentences, or random word order sequences. Semantic violations during reading elicited an N400 effect at the noun violating the selectional restrictions of the preceding verb. Syntactic violations, induced by a gender incongruency between determiner and noun, led to a P600 effect at the same position. Different ERP patterns occurred during the silent production phase. Here, semantically violated sentences elicited an early fronto-central negativity at the verb, while syntactically violated sentences elicited a late right-frontal positivity at the determiner. Random word order was accompanied by long-lasting slow waves during the production phase. The findings are consistent with models of hierarchical sentence planning and further indicate that the ongoing working memory processes are qualitatively distinct from comprehension mechanisms and neurophysiologically specific for syntactic and lexical-semantic level planning. In conclusion, active working memory maintenance of sentences is likely to comprise specific stages of sentence production that are indicated by ERP correlates of syntactic and semantic planning at the phrasal and clausal level respectively. (shrink)