Purpose: The current meta-analysis provides a quantitative overview of published and unpublished studies on statistical learning in the auditory verbal domain in people with and without specific ...language impairment (SLI). The database used for the meta-analysis is accessible online and open to updates (Community-Augmented Meta-Analysis), which facilitates the accumulation and evaluation of previous and future studies on statistical learning in this domain. Method: A systematic literature search identified 10 unique experiments examining auditory verbal statistical learning in 213 participants with SLI and 363 without SLI, aged between 6 and 19 years. Data from qualifying studies were extracted and converted to Hedges' g effect sizes. Results: The overall standardized mean difference between participants with SLI and participants without SLI was 0.54, which was significantly different from 0 (p < 0.001, 95% confidence interval 0.36, 0.71). Conclusion: Together, the results of our meta-analysis indicate a robust difference between people with SLI and people without SLI in their detection of statistical regularities in the auditory input. The detection of statistical regularities is, on average, not as effective in people with SLI compared with people without SLI. The results of this meta-analysis are congruent with a statistical learning deficit hypothesis in SLI.
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DOBA, IZUM, KILJ, NUK, ODKLJ, OILJ, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK, VSZLJ
Statistical learning (SL) difficulties have been suggested to contribute to the linguistic and non-linguistic problems observed in children with dyslexia. Indeed, studies have demonstrated that ...children with dyslexia experience problems with SL, but the extent of the problems is unclear. We aimed to examine the performance of children with and without dyslexia across three distinct paradigms using both on- and offline measures, thereby tapping into different aspects of SL. 100 children with and without dyslexia (aged 8-11, 50 per group) completed three SL tasks: serial reaction time (SRT), visual statistical learning (VSL), and auditory nonadjacent dependency learning (A-NADL). Learning was measured through online reaction times during exposure in all tasks, and through offline questions in the VSL and A-NADL tasks. We find significant learning effects in all three tasks, from which we conclude that, collapsing over groups, children are sensitive to the statistical structures presented in the SRT, VSL and A-NADL tasks. No significant interactions of learning effect with group were found in any of the tasks, so we cannot conclude whether or not children with dyslexia perform differently on the SL tasks than their TD peers. These results are discussed in light of the proposed SL deficit in dyslexia.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Antimicrobial silver nanoparticles (AgNPs) are popular in consumer and industrial products, leading to increasing concentrations in the environment. We tested whether exposure to AgNPs could be ...detrimental to a microbe, its host plant, and their symbiotic relationship. When subjected to 10 µg/mL AgNPs, growth of
Bradyrhizobium japonicum
USDA 110 was halted. Axenic nitrogen-fertilized
Glycine max
seedlings were unaffected by 2.5 µg/mL of 30 nm AgNPs, but growth was inhibited with the same dose of 16 nm AgNPs. With 2.5 µg/mL AgNPs, biomass of inoculated plants was 50% of the control. Bacteroids were not found in nodules on plants treated with 2.5 µg/mL AgNPs and plants given 0.5–2.5 µg/mL AgNPs had 40–65% decreased nitrogen fixation. In conclusion, AgNPs not only interfere with general plant and bacterial growth but also inhibit nodule development and bacterial nitrogen fixation. We should be mindful of not releasing AgNPs to the environment or to agricultural land.
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CEKLJ, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Categorization of sensory stimuli is a vital process in understanding the world. In this paper we show that distributional learning plays a role in learning novel object categories in school-aged ...children. An 11-step continuum was constructed based on two novel animate objects by morphing one object into the other in 11 equal steps. Forty-nine children (7-9 years old) were subjected to one of two familiarization conditions during which they saw tokens from the continuum. The conditions differed in the position of the distributional peaks along the continuum. After familiarization it was tested how the children categorized the stimuli. Results show that, in line with our expectations, familiarization condition influenced categorization during the test phase, indicating that the frequency distribution of tokens in the input had induced novel object category formation. These results suggest that distributional learning could play an important role in categorizing sensory stimuli throughout life.
Introduction
Research indicates that statistical learning plays a role in word learning by enabling the learner to track the co-occurrences between words and their visual referents, a process that is ...named cross-situational word learning. Word learning is problematic for children with developmental language disorder (DLD), and a deficit in statistical learning has been suggested to contribute to the language difficulties in these children. Therefore, we investigate whether children with DLD have more difficulty than TD children with learning novel word–referent pairs based on cross-situational statistics in an implicit task, and whether this ability is related to their lexical-semantic skills. Moreover, we look at the role of variability of the learning environment.
Methods
In our implicit cross-situational word learning task, each trial in the exposure phase was in itself ambiguous: two pictures of unknown objects were shown at the same time and two novel words were played consecutively, without indicating which word referred to which object. However, as every word occurred with its correct referent consistently, the children could learn the word–referent pairs across trials. The children were not explicitly instructed to learn the names of new objects. As an on-line measure of learning, eye-movements were recorded during the exposure phase. After exposure, word–referent knowledge was also tested using multiple choice questions. Several measures of lexical-semantic knowledge were administered to the children with DLD, as well as tasks measuring non-verbal intelligence and phonological processing. Contextual variability (the number of different distractors with which a particular word–referent pair occurs across trials) was manipulated between subjects by constructing two types of exposure conditions: low contextual diversity vs. high contextual diversity.
Results
Both groups of children performed significantly above chance level on the test phase, but the TD children significantly outperformed the children with DLD. We found no significant effect of contextual diversity. The eye-tracking data revealed some evidence of on-line learning, but no differences between groups. Finally, the regression analyses did not reveal any significant predictors of off-line or on-line cross-situational word learning ability.
Discussion
Our results indicate that although children with DLD are able to learn word-referent pairs in an implicit task, they have more difficulty than TD children. Possibly they need more input to achieve the same level.
Visual statistical learning (VSL) was traditionally tested through offline two-alternative forced choice (2-AFC) questions. More recently, online reaction time (RT) measures and alternative offline ...question types have been developed to further investigate learning during exposure and more adequately assess individual differences in adults (
Siegelman et al., 2017b
,
2018
). We assessed the usefulness of these measures for investigating VSL in early-school-aged children. Secondarily, we examined the effect of introducing a cover task, potentially affecting attention, on children’s VSL performance. Fifty-three children (aged 5–8 years) performed a self-paced VSL task containing triplets, in which participants determine the presentation speed and RTs to each stimulus are recorded. Half of the participants performed a cover task, while the other half did not. Online sensitivity to the statistical structure was measured by contrasting RTs to unpredictable versus predictable elements. Subsequently, participants completed 2-AFC (
choose correct triplet
) and 3-AFC (
fill blank to complete triplet
) offline questions. RTs were significantly longer for unpredictable than predictable elements, so we conclude that early-school-aged children are sensitive to the statistical structure during exposure, and that the RT task can measure that. We found no evidence as to whether children can perform above chance on offline 2-AFC or 3-AFC questions, or whether the cover task affects children’s VSL performance. These results show the feasibility of using an online RT task when assessing VSL in early-school-aged children. This task therefore seems suitable for future studies that aim to investigate VSL across development or in clinical populations, perhaps together with behavioral tasks.
Since Saffran, Aslin and Newport (1996) showed that infants were sensitive to transitional probabilities between syllables after being exposed to a few minutes of fluent speech, there has been ample ...research on statistical learning. Word segmentation studies usually test learning by making use of “offline methods” such as forced-choice tasks. However, cognitive factors besides statistical learning possibly influence performance on those tasks. The goal of the present study was to improve a method for measuring word segmentation online. Click sounds were added to the speech stream, both between words and within words. Stronger expectations for the next syllable within words as opposed to between words were expected to result in slower detection of clicks within words, revealing sensitivity to word boundaries. Unexpectedly, we did not find evidence for learning in multiple groups of adults and child participants. We discuss possible methodological factors that could have influenced our results.
The Gradual Learning Algorithm (Boersma 1997) is a constraint-ranking algorithm for learning optimality-theoretic grammars. The purpose of this article is to assess the capabilities of the Gradual ...Learning Algorithm, particularly in comparison with the Constraint Demotion algorithm of Tesar and Smolensky (1993, 1996, 1998, 2000), which initiated the learnability research program for Optimality Theory. We argue that the Gradual Learning Algorithm has a number of special advantages: it can learn free variation, deal effectively with noisy learning data, and account for gradient well-formedness judgments. The case studies we examine involve Ilokano reduplication and metathesis, Finnish genitive plurals, and the distribution of English light and dark /l/.
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BFBNIB, INZLJ, NMLJ, NUK, PNG, UL, UM, UPUK, ZRSKP
Distributional learning of speech sounds (i.e., learning from simple exposure to frequency distributions of speech sounds in the environment) has been observed in the lab repeatedly in both infants ...and adults. The current study is the first attempt to examine whether the capacity for using the mechanism is different in adults than in infants. To this end, a previous event-related potential study that had shown distributional learning of the English vowel contrast /æ/∼/ε/ in 2-to-3-month old Dutch infants was repeated with Dutch adults. Specifically, the adults were exposed to either a bimodal distribution that suggested the existence of the two vowels (as appropriate in English), or to a unimodal distribution that did not (as appropriate in Dutch). After exposure the participants were tested on their discrimination of a representative æ and a representative ε, in an oddball paradigm for measuring mismatch responses (MMRs). Bimodally trained adults did not have a significantly larger MMR amplitude, and hence did not show significantly better neural discrimination of the test vowels, than unimodally trained adults. A direct comparison between the normalized MMR amplitudes of the adults with those of the previously tested infants showed that within a reasonable range of normalization parameters, the bimodal advantage is reliably smaller in adults than in infants, indicating that distributional learning is a weaker mechanism for learning speech sounds in adults (if it exists in that group at all) than in infants.
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This paper argues that if phonological and phonetic phenomena found in language data and in experimental data all have to be accounted for within a single framework, then that framework will have to ...be based on neural networks. We introduce an artificial neural network model that can handle stochastic processing in production and comprehension. With the “inoutstar” learning algorithm, the model is able to handle two seemingly disparate phenomena at the same time: gradual category creation and auditory dispersion. As a result, two aspects of the transmission of language from one generation to the next are integrated in a single model. The model therefore addresses the hitherto unsolved problem of how symbolic-looking discrete language behaviour can emerge in the child from gradient input data from her language environment. We conclude that neural network models, besides being more biologically plausible than other frameworks, hold a promise for fruitful theorizing in an area of linguistics that traditionally assumes both continuous and discrete levels of representation.
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