scholarly journals Online incidental statistical learning of audiovisual word sequences in adults: a registered report

2018 ◽  
Vol 5 (2) ◽  
pp. 171678 ◽  
Author(s):  
Sengottuvel Kuppuraj ◽  
Mihaela Duta ◽  
Paul Thompson ◽  
Dorothy Bishop
Keyword(s):  
Language Learning ◽  
Statistical Learning ◽  
Short Term Memory ◽  
Reaction Time Data ◽  
Learning Task ◽  
Two Dimensions ◽  
Learning Ability ◽  
Time Data ◽  
Novel Approach ◽  
Continuous Stream

Statistical learning has been proposed as a key mechanism in language learning. Our main goal was to examine whether adults are capable of simultaneously extracting statistical dependencies in a task where stimuli include a range of structures amenable to statistical learning within a single paradigm. We devised an online statistical learning task using real word auditory–picture sequences that vary in two dimensions: (i) predictability and (ii) adjacency of dependent elements. This task was followed by an offline recall task to probe learning of each sequence type. We registered three hypotheses with specific predictions. First, adults would extract regular patterns from continuous stream (effect of grammaticality). Second, within grammatical conditions, they would show differential speeding up for each condition as a factor of statistical complexity of the condition and exposure. Third, our novel approach to measure online statistical learning would be reliable in showing individual differences in statistical learning ability. Further, we explored the relation between statistical learning and a measure of verbal short-term memory (STM). Forty-two participants were tested and retested after an interval of at least 3 days on our novel statistical learning task. We analysed the reaction time data using a novel regression discontinuity approach. Consistent with prediction, participants showed a grammaticality effect, agreeing with the predicted order of difficulty for learning different statistical structures. Furthermore, a learning index from the task showed acceptable test–retest reliability ( r  = 0.67). However, STM did not correlate with statistical learning. We discuss the findings noting the benefits of online measures in tracking the learning process.

scholarly journals Statistical learning in domestic chicks is modulated by strain and sex

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Chiara Santolin ◽  
Orsola Rosa-Salva ◽  
Bastien S. Lemaire ◽  
Lucia Regolin ◽  
Giorgio Vallortigara
Keyword(s):  
Sex Differences ◽  
Statistical Learning ◽  
Comparative Research ◽  
Learning Task ◽  
Human Infants ◽  
Sensory Inputs ◽  
Automated Tracking ◽  
Domestic Chicks ◽  
Continuous Stream

Abstract Statistical learning is a key mechanism for detecting regularities from a variety of sensory inputs. Precocial newborn domestic chicks provide an excellent model for (1) exploring unsupervised forms of statistical learning in a comparative perspective, and (2) elucidating the ecological function of statistical learning using imprinting procedures. Here we investigated the role of the sex of the chicks in modulating the direction of preference (for familiarity or novelty) in a visual statistical learning task already employed with chicks and human infants. Using both automated tracking and direct human coding, we confirmed chicks’ capacity to recognize the presence of a statistically defined structure underlying a continuous stream of shapes. Using a different chicken strain than previous studies, we were also able to highlight sex differences in chicks’ propensity to approach the familiar or novel sequence. This could also explain a previous failure to reveal statistical learning in chicks which sex was however not determined. Our study confirms chicks’ ability to track visual statistics. The pivotal role of sex in determining familiarity or novelty preferences in this species and the interaction with the animals’ strain highlight the importance to contextualize comparative research within the ecology of each species.

scholarly journals Synesthetes perseverate in implicit learning: Evidence from a non-stationary statistical learning task

2018 ◽  
Vol 72 (7) ◽  
pp. 1771-1779 ◽  
Author(s):  
Kaitlyn R Bankieris ◽  
Ting Qian ◽  
Richard N Aslin
Keyword(s):  
Reaction Time ◽  
Implicit Learning ◽  
Time Course ◽  
Probability Distributions ◽  
Computer Game ◽  
Reaction Time Data ◽  
Learning Task ◽  
Time Data ◽  
Learning Abilities ◽  
Small Set

Synesthetes automatically and consistently experience additional sensory or cognitive perceptions in response to particular environmental stimuli. Recent evidence suggests that the propensity to develop synesthesia is genetic while the particular associations experienced by a given synesthete are influenced by learning. Despite the potential role of implicit learning in the formation of synesthetic associations, there has been minimal investigation of synesthetes’ implicit learning abilities. In this study, we examine linguistic-colour synesthetes’ ability to implicitly learn from and adjust to non-stationary statistics in a domain unrelated to their particular form of synesthesia. Engaging participants in a computer game Whack-the-mole, we utilise the online measure of reaction time to assess the time course of learning. Participants are exposed to “worlds” of probabilities that, unbeknownst to them, undergo unannounced changes, creating unpredictable statistical shifts devoid of accompanying cues. The same small set of probability worlds are repeated throughout the experiment to investigate participants’ ability to retain and learn from this repetitive probabilistic information. The reaction time data provide evidence that synesthetes require more information than nonsynesthetes to benefit from the non-stationary probability distributions. These findings demonstrate that linguistic-colour synesthetes’ implicit learning abilities—in a domain far from their synesthetic experiences—differ from those of nonsynesthetes.

scholarly journals Can We Enhance Statistical Learning? Exploring Statistical Learning Improvement in Children with Vocabulary Delay

2021 ◽  
Vol 26 (3) ◽  
pp. 558-567
Author(s):  
Dongsun Yim ◽  
Yoonhee Yang
Keyword(s):  
Statistical Learning ◽  
Incidental Learning ◽  
Learning Task ◽  
Learning Ability ◽  
The Novel ◽  
Typically Developing ◽  
Learning Improvement ◽  
Group Score ◽  
Domain Specific ◽  
Novel Word Learning

Objectives: If statistical learning ability is critical for language acquisition and language development, it is necessary to confirm whether enhancing statistical learning ability can improve the children’s language skills. The present study investigated whether children with and without vocabulary delay (VD) show a difference in improving statistical learning (SL) tasks manipulated with implicit, implicit*2 and explicit conditions, and with visual and auditory domains; and also explores the relationship among SL, vocabulary, and quick incidental learning (QUIL).Methods: A total of 132 children between 3 to 8 years participated in this study, including vocabulary delayed children (N= 34) and typically developing children (N = 98). Participants completed SL tasks which were composed of three exposure conditions, and Quick incidental learning (QUIL) tasks to tap the novel word learning ability.Results: The VD group score was significantly lower than the TD group in the explicit condition of the auditory statistical learning task, and there was a significant correlation between QUIL and SL_auditory (implicit*2) only in the TD group.Conclusion: These results may explain that the TD group was ready to accept the explicit cues for learning as a domain-specific (auditory) benefit, and their auditory SL ability can be closely linked to vocabulary abilities. The current study suggests one possibility; that the VD group can increase the statistical learning ability through double auditory exposures. The novel quick incidental learning in the TD group was supported by the statistical learning, but this was not seen in the VD group.

scholarly journals Statistical Language Learning and Vagus Nerve Stimulation: A Pilot Study

2019 ◽  
Vol 21 (1) ◽  
Author(s):  
Ivette De Aguiar ◽  
Edith Kaan
Keyword(s):  
Vagus Nerve ◽  
Language Learning ◽  
Statistical Learning ◽  
Memory Task ◽  
Learning Task ◽  
Phonological Memory ◽  
Retest Reliability ◽  
Learning Tasks ◽  
Transcutaneous Stimulation ◽  
Test Retest Reliability

Applying transcutaneous stimulation to the auricular branch of the vagus nerve (tVNS) has been shown to enhance associative learning in humans. The main goal of the project is to investigate the effect tVNS has on procedural learning, specifically implicit statistical language learning. The aim of the experiment reported in this paper was to determine which statistical language learning paradigms would be appropriate to use with tVNS. Since we would be looking at within-subject changes between two sessions (one session with, one session without stimulation), we tested the test-retest reliability of two statistical learning paradigms.  We also tested the correlation between a explicit phonological memory task and the implicit statistical learning tasks to determine whether phonological memory was involved in the statistical learning tasks. Our results showed a high test-retest reliability for the word segmentation and adjacent dependencies statistical learning task. However, the second statistical learning task dealing with non-adjacent dependencies had low test-retest reliability, meaning it would not be appropriate for future studies incorporating tVNS. There was a high correlation between the phonological memory task and both statistical learning taks, indicating implicit statistical learning may recruit phonological memory.

How well does Statistical Learning Address the Challenges of Real-World Language Learning?

2018 ◽  
pp. 689-713
Author(s):  
Lucia Sweeney ◽  
Rebecca L. Gómez
Keyword(s):  
Individual Differences ◽  
Natural Language ◽  
Language Learning ◽  
Statistical Learning ◽  
Cognitive Processes ◽  
Real World ◽  
Learning Ability ◽  
World Language ◽  
Word Forms ◽  
Transitional Probabilities

How well does statistical learning address the challenges of real-world language learning? This chapter presents progress in the domain of statistical learning since Saffran et al. (1996) conducted their seminal work. It highlights the extension of statistical learning to acquisition of natural language, and reviews investigations of how infants and adults segment words from speech, acquire word forms, and form abstract grammatical categories through tracking of transitional probabilities and non-adjacent dependencies. It also focuses on research demonstrating the influence of individual differences on statistical learning ability along with neuroimaging studies that reveal cognitive processes supporting statistical learning. The chapter ends by suggesting avenues of research that would further extend the application of statistical learning to natural language acquisition.

scholarly journals How statistical learning interacts with the socioeconomic environment to shape children’s language development

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0244954
Author(s):  
Leyla Eghbalzad ◽  
Joanne A. Deocampo ◽  
Christopher M. Conway
Keyword(s):  
Socioeconomic Status ◽  
Language Development ◽  
Statistical Learning ◽  
Event Related Potentials ◽  
Learning Task ◽  
Learning Ability ◽  
Learning Performance ◽  
Learning Abilities ◽  
Related Potentials ◽  
Social Environmental

Language is acquired in part through statistical learning abilities that encode environmental regularities. Language development is also heavily influenced by social environmental factors such as socioeconomic status. However, it is unknown to what extent statistical learning interacts with SES to affect language outcomes. We measured event-related potentials in 26 children aged 8–12 while they performed a visual statistical learning task. Regression analyses indicated that children’s learning performance moderated the relationship between socioeconomic status and both syntactic and vocabulary language comprehension scores. For children demonstrating high learning, socioeconomic status had a weaker effect on language compared to children showing low learning. These results suggest that high statistical learning ability can provide a buffer against the disadvantages associated with being raised in a lower socioeconomic status household.

scholarly journals What canonical online and offline measures of statistical learning can and cannot tell us

2021 ◽  
Author(s):  
Ava Kiai ◽  
Lucia Melloni
Keyword(s):  
Word Recognition ◽  
Statistical Learning ◽  
Target Detection ◽  
Reaction Times ◽  
Recognition Task ◽  
Reaction Time Data ◽  
Individual Performance ◽  
Detection Task ◽  
Time Data ◽  
Target Detection Task

Statistical learning (SL) allows individuals to rapidly detect regularities in the sensory environment. We replicated previous findings showing that adult participants become sensitive to the implicit structure in a continuous speech stream of repeating tri-syllabic pseudowords within minutes, as measured by standard tests in the SL literature: a target detection task and a 2AFC word recognition task. Consistent with previous findings, we found only a weak correlation between these two measures of learning, leading us to question whether there is overlap between the information captured by these two tasks. Representational similarity analysis on reaction times measured during the target detection task revealed that reaction time data reflect sensitivity to transitional probability, triplet position, word grouping, and duplet pairings of syllables. However, individual performance on the word recognition task was not predicted by similarity measures derived for any of these four features. We conclude that online detection tasks provide richer and multi-faceted information about the SL process, as compared with 2AFC recognition tasks, and may be preferable for gaining insight into the dynamic aspects of SL.

Modeling Within-Person Variance in Reaction Time Data of Older Adults

GeroPsych ◽  
2011 ◽  
Vol 24 (4) ◽  
pp. 169-176 ◽  
Author(s):  
Philippe Rast ◽  
Daniel Zimprich
Keyword(s):  
Reaction Time ◽  
Cognitive Aging ◽  
Reaction Times ◽  
Reaction Time Task ◽  
Reaction Time Data ◽  
Scale Model ◽  
Time Data ◽  
Time Task ◽  
The Mean ◽  
Second Wave

In order to model within-person (WP) variance in a reaction time task, we applied a mixed location scale model using 335 participants from the second wave of the Zurich Longitudinal Study on Cognitive Aging. The age of the respondents and the performance in another reaction time task were used to explain individual differences in the WP variance. To account for larger variances due to slower reaction times, we also used the average of the predicted individual reaction time (RT) as a predictor for the WP variability. Here, the WP variability was a function of the mean. At the same time, older participants were more variable and those with better performance in another RT task were more consistent in their responses.

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