The role of language in novel task learning

Wout, Felice M Van 'T; Jarrold, Christopher

doi:10.1016/j.cognition.2019.104036

Cited by 11 publications

(24 citation statements)

References 20 publications

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“…According to the cognitive model of implementing novel instructions [1], preparing novel S-R mappings should lead to both a declarative and a procedural working memory representation, which could be associated with ACC and exeRT, respectively, and which might influence novel task learning and execution to different degrees (see also [44]). The finding by van't Wout & Jarrold [45] that the use of language is crucial during the early stage of novel task learning further corroborates this idea. Initially, the linguistic or declarative representation of the S-R mappings might be important for performance, but the procedural representation might become more relevant once the task has been practised.…”

Section: Discussionsupporting

confidence: 57%

Benefits and costs of self-paced preparation of novel task instructions

2021

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Rapidly executing novel instructions is a critical ability. However, it remains unclear whether longer preparation of novel instructions improves performance, and if so, whether this link is modulated by performance benefits and costs of preparation. Regarding the first question, we reanalysed previous data on novel instruction implementation and ran Experiment 1. Experiment 1 consisted of multiple mini-blocks, in which participants prepared four novel stimulus–response (S-R) mappings in a self-paced instruction phase. After participants indicated they were ready, one of the four stimuli was presented and they responded. The reanalysis and Experiment 1 showed that longer preparation indeed led to better performance. To examine if preparation was modulated when the benefits of preparation were reduced, we presented the correct response with the stimulus on some trials in Experiments 2 and 3. Preparation was shorter when the probability that the correct response was presented with the stimulus increased. In Experiment 4, we manipulated the costs of preparation by changing the S-R mappings between the instruction and execution phases on some trials. This had only limited effects on preparation time. In conclusion, self-paced preparation of novel instructions comes with performance benefits and costs, and participants adjust their preparation strategy to the task context.

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Section: Discussionsupporting

confidence: 57%

Benefits and costs of self-paced preparation of novel task instructions

2021

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“…Language could serve as an important function in formulating task representations but become superfluous once those representations were installed. A recent study by van’t Wout and Jarrold (2020) confirms this intuition by reporting articulatory suppression effects during the initial phase of novel task learning and not in a later phase. Support may also come from studies on rapid instructed task learning (RITL, for short), i.e., “the ability to learn task procedures from instruction” ( Cole et al, 2013 , p. 1), an “especially important form of cognitive flexibility” ( Cole et al, 2013 , p. 1) and something humans – as opposed to other animals – excel at.…”

Section: The Use Of Inner Speech In Support Of Cognitive Controlmentioning

confidence: 74%

“…We will treat the first role of labels only briefly, although cognitive control is involved in language processing at many levels ranging from language production to sentence comprehension and specific phenomena like code switching (Levelt, 1989;Hagoort, 2005;Bourguignon and Gracco, 2019;Sulpizio et al, 2020). It touches on the question of how closely linguistic and control systems are connected.…”

Section: The Availability Of Labels As Facilitators Of Cognitive Controlmentioning

confidence: 99%

How Abstract (Non-embodied) Linguistic Representations Augment Cognitive Control

Kompa

Mueller

2020

Front. Psychol.

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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, modalityspecific, 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.

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“…In our third experiment (pre-registration, raw data, analysis code, and stimuli are available as supplemental materials at https://osf.io/mwzfh/), we had two goals: to replicate the effect of articulatory suppression at encoding that emerged in Experiment 2 in support of the linguistic bootstrapping hypothesis, and to test whether this effect is specifically due to blocking access to language rather than due to performing a secondary task. We therefore compared articulatory suppression during encoding to foot tapping, a secondary task that is unrelated to language use but comparable on a number of other characteristics (i.e., it is a rhythmic motor task, does not involve visual perception or hand action that could interfere with stimulus presentation, and it can be sustained throughout the encoding stage without undue fatigue: see Gaillard et al, 2012;van't Wout & Jarrold, 2020). This time, we also manipulated the secondary task at encoding within participants, so that all participants encoded sequences in all three conditions (with no secondary task, while performing articulatory suppression, and while performing foot tapping).…”

Section: Language Increases Working Memory Capacity For Objects 32 Exmentioning

confidence: 99%

Linguistic bootstrapping allows more real-world object concepts to be held in mind

Dymarska¹,

Connell²,

Banks³

2021

Preprint

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[Draft version, 04/03/21. This paper has not been peer reviewed. Please do not copy or cite without author's permission] The linguistic-simulation approach to cognition predicts that language can enable more efficient conceptual processing than purely sensorimotor-affective simulations of concepts. We tested the implications of this approach in working memory, where use of linguistic labels (i.e., words and phrases) could enable more efficient representation of concepts in a limited-capacity store than representation via full sensorimotor simulation; a proposal called linguistic bootstrapping. In four pre-registered experiments using a nonverbal recognition memory paradigm, we asked participants to remember sequences of real-world objects, and used articulatory suppression to selectively block implicit activation of linguistic labels, which we predicted would impair object memory performance. We found that blocking access to language at encoding impaired memory accuracy, though not latency, and that this impairment was not simply dual-task load. Results show that a sequence of up to 10 contextually-situated object concepts can be held in working memory when language is blocked, but this capacity increases to 12 objects when language is available. The findings support the linguistic bootstrapping hypothesis that working memory for familiar object concepts normally relies on language, and that implicitly-retrieved object labels, used as linguistic placeholders, enhance the achievable capacity of working memory beyond what sensorimotor information alone can accomplish.

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The role of language in novel task learning

Cited by 11 publications

References 20 publications

Benefits and costs of self-paced preparation of novel task instructions

Benefits and costs of self-paced preparation of novel task instructions

How Abstract (Non-embodied) Linguistic Representations Augment Cognitive Control

Linguistic bootstrapping allows more real-world object concepts to be held in mind

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