Implicit sequence learning of chunking and abstract structures

Fu, Qiuping; Sun, Huiming; Dienes, Zoltán; Fu, Xiaolan

doi:10.1016/j.concog.2018.04.010

Cited by 17 publications

(29 citation statements)

References 52 publications

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“…Although chunk learning has been found to be an important contributor to implicit statistical learning (e.g., Batterink, 2017; Perruchet & Pacton, 2006), it has recently been suggested that both rule-based statistical computation and chunk learning operate during this learning form (Christiansen, 2018; Fu, Sun, Dienes, & Fu, 2018). This would be plausible for the ASRT task, as well.…”

Section: Discussionmentioning

confidence: 99%

Tracking the implicit acquisition of nonadjacent transitional probabilities by ERPs

et al. 2019

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The implicit acquisition of complex probabilistic regularities has been found to be crucial in numerous automatized cognitive abilities, including language processing and associative learning. However, it has not been completely elucidated how the implicit extraction of second-order nonadjacent transitional probabilities is reflected by neurophysiological processes. Therefore, this study investigated the sensitivity of event-related brain potentials (ERPs) to these probabilistic regularities embedded in a sequence of visual stimuli without providing explicit information on the structure of the stimulus stream. Healthy young adults (N = 32) performed a four-choice RT task that included a sequential regularity between nonadjacent trials yielding a complex transitional probability structure. ERPs were measured relative to both stimulus and response onset. RTs indicated the rapid acquisition of the sequential regularity and the transitional probabilities. The acquisition process was also tracked by the stimulus-locked and response-locked P3 component: The P3 peak was larger for the sequence than for the random stimuli, while the late P3 was larger for less probable than for more probable short-range relations among the random stimuli. According to the RT and P3 effects, sensitivity to the sequential regularity is assumed to be supported by the initial sensitivity to the transitional probabilities. These results suggest that stimulus–response contingencies on the probabilistic regularities of the ongoing stimulus context are implicitly mapped and constantly revised. Overall, this study (1) highlights the role of predictive processes during implicit memory formation, and (2) delineates a potential to gain further insight into the dynamics of implicit acquisition processes.

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Section: Discussionmentioning

confidence: 99%

Tracking the implicit acquisition of nonadjacent transitional probabilities by ERPs

et al. 2019

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“…On each trial, one of them was presented in the centre of the computer׳s screen against a silver gray background. They were followed by the triplets from two second-order conditional (SOC) sequence, or by the triplets from neither SOC sequence with different probabilities (see [1] , [2] ).…”

Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

“…Each excel file included four sheets for one experiment. Among them, two sheets were for reaction times in the serial reaction time task: one described the reaction times for each combination of type of stimuli and blocks, while one described reaction times for each combination of type of stimuli and type of deviants (see Fu et al, 2018 ); two sheets were for generation performance in the inclusion and exclusion tests: one described generation performance for each combination of type of stimuli, instructions, and type of deviants, while one described the intercept and slope of generation difference between inclusion and exclusion against confidence ratings for each type of stimuli in Experiments 1 and 2, or described generation differences between inclusion and exclusion for each combination of type of stimuli and attribution in Experiment 3. In a sheet, each column represents each combination of the factors and each row represents one participant.…”

Section: Datamentioning

confidence: 99%

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Dataset of implicit sequence learning of chunking and abstract structures

Sun²,

Dienes

et al. 2019

Data in Brief

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This article describes the data analyzed in the paper “Implicit sequence learning of chunking and abstract structures” (Fu et al., 2018) [1]. It includes reaction times in the serial reaction time task and generation proformance for each confidence rating or attribution under the inclusion and exclusion tests from three experiments. For the serial reaction time task, the independent varialbles were type of stimuli and blocks or type of deviants; for the generation tests, the independent varialbles were type of stimuli, instructions, and confidence ratings or attribution tests. The data can be used to examine wether a computor model can account for what type of knowledge is acquried in implicit sequence learning.

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“…Contrasting with the early results of Reber (1967), a decrease in participants' classification accuracy suggested that learning in the AGL task is perceptually bound (see also : Perruchet & Pacteau, 1990). While abstract processing is extensively documented in both, the AGL task (e.g., Brooks & Vokey, 1991;Lotz & Kinder, 2006;Scott & Dienes, 2008) and the SRTT (e.g., Fu et al, 2018;Kemény & Meier, 2016), it has become increasingly accepted that the perceptual characteristics of the stimuli influence the transference of implicitly learned information between different testing conditions (Conway & Christiansen, 2006;Dienes & Berry, 1997;Dulany et al, 1984;Perruchet & Pacteau, 1990;contrary: Pothos et al, 2006). On the one hand, the above literature highlights the relatively limited transference of the implicitly learned information.…”

Section: Characteristics Of the Surface Stimulimentioning

confidence: 96%

Implicit and explicit learning of socio-emotional information in a dynamic system control task

Costea¹,

Jurchiș²,

Cleeremans³

et al. 2020

Preprint

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Unconscious or, implicit learning (IL) is often described as being instrumental to human social functioning. However, most of the available IL tasks have limited external validity; they use surface stimuli that are not socially relevant. Additionally, the way in which participants exchange information within most of the available tasks departs from the way in which information is being exchanged in real-life social situations. In this study, we report the validation of a novel task, inspired from Broadbent et al. (1984), assessing the implicit and explicit learning of socio-emotional information in a dynamic environment. Participants (N=115) interacted with an animated virtual avatar that displayed different levels of emotional facial expressions. Their task was to regulate the avatar’s facial expression to a speciﬁed level. Unknown to them, the relationship between their inputs and the avatar’s state was mediated by an abstract rule. Results indicate that learning occurred in the task, as participants gradually increased their ability to bring the avatar in the target state. We found evidence for both explicit (consciously knowing the appropriate response) and implicit (knowing the correct responses even when based on subjectively defined unconscious mental states) knowledge acquisition. This is one of the first studies to propose a task for studying the role of IL in interactive social situations. Implications for future research are discussed.

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Implicit sequence learning of chunking and abstract structures

Cited by 17 publications

References 52 publications

Tracking the implicit acquisition of nonadjacent transitional probabilities by ERPs

Tracking the implicit acquisition of nonadjacent transitional probabilities by ERPs

Dataset of implicit sequence learning of chunking and abstract structures

Implicit and explicit learning of socio-emotional information in a dynamic system control task

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