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Purpose Impairments in statistical learning abilities of individuals with developmental dyslexia (DD) have been demonstrated in word segmentation and in visual artificial grammar learning (AGL) tasks, but so far, little attention has been devoted to the AGL abilities of this population in the acoustic verbal domain. This study aimed to test whether adolescents with dyslexia have difficulties in extracting abstract patterns from auditory sequences of nonsense syllables based on a finite state grammar relative to typically developing (TD) peers. We also tested whether incremental presentation of stimuli of different lengths (starting small) has a facilitating effect on learning complex structures in dyslexia (and in TD) as opposed to presenting strings in random order. Method Thirty-one adolescents with DD and 31 age-matched control participants completed an AGL task. Participants passively listened to acoustic sequences of nonsense syllables generated by an artificial grammar in the training phase. In the test phase, they were presented with pairs of novel grammatical and nongrammatical sequences and were required to decide which member of a sequence pair was more similar to the material heard during training. Results Performance levels and the proportion of learners were smaller in participants with DD than in the control group. While the starting small effect was nominally present both in performance levels and in the number of learners in participants with DD, but not in the group with TD, the presentation of strings in incremental order did not statistically improve learning performance in either group. Conclusion Our results suggest that (a) statistical learning of abstract sequences in the acoustic domain is less efficient in people with dyslexia than in TD controls and (b) while incremental presentation of stimuli of different length did not improve learning in our study, the observed pattern of results suggests that the effects of different training designs should be explored further in developmental disorders.

Purpose: The vulnerability of statistical learning (SL) in developmental language disorder (DLD) has mainly been demonstrated with metacognitive offline measures which give little insight into the more specific nature and timing of learning. Our aims in this study were to test SL in children with and without DLD with both online and offline measures and to compare the efficiency of SL in the visual and acoustic modalities in DLD.Method: We explored SL in school-age children with and without DLD matched on age and sex (n = 36). SL was investigated with the use of acoustic verbal and visual nonverbal segmentation tasks relying on online (reaction times and accuracy) and offline (two-alternative forced choice, 2AFC and production) measures.Results: In online measures, learning was evident in both groups in both the visual and acoustic modalities, while offline measures showed difficulties in DLD. The visual production task showed a significant learning effect in both groups, while the visual two-alternative forced choice (2AFC) and the two acoustic offline tasks only showed evidence of learning in the control group. The comparison of learning indices revealed an SL impairment in DLD, which is present in both modalities.Conclusions: Our findings suggest that children with DLD are comparable to typically developing (TD) children in their ability to extract acoustic verbal and visual nonverbal patterns that are cued only by transitional probabilities in online tasks, but they show impairments on metacognitive measures of learning. The pattern of online and offline measures implies that online tests can be more sensitive and valid indices of SL than offline tasks, and the combined use of different measures provides a better picture of learning efficiency, especially in groups where metacognitive tasks are challenging.

While several studies suggest that the nature and properties of the input have significant effects on statistical learning, they have rarely been investigated systematically. In order to understand how input characteristics and their interactions impact statistical learning, we explored the effects of modality (auditory vs. visual), presentation type (serial vs. simultaneous), domain (linguistic vs. non-linguistic), and training type (random, starting small, starting big) on artificial grammar learning in young adults (N = 360). With serial presentation of stimuli, learning was more effective in the auditory than in the visual modality. However, with simultaneous presentation of visual and serial presentation of auditory stimuli, the modality effect was not present. We found a significant domain effect as well: a linguistic advantage over nonlinguistic material, which was driven by the domain effect in the auditory modality. Overall, the auditory linguistic condition had an advantage over other modality-domain types. Training types did not have any overall effect on learning; starting big enhanced performance only in the case of serial visual presentation. These results show that input characteristics such as modality, presentation type, domain and training type influence statistical learning, and suggest that their effects are also dependent on the specific stimuli and structure to be learned.

The vulnerability of statistical learning has been demonstrated in reading difficulties in both the visual and acoustic modalities. We examined segmentation abilities of Hungarian speaking adolescents with different levels of reading fluency in the acoustic verbal and visual nonverbal domains. We applied online target detection tasks, where the extent of learning is reflected in differences between reaction times to predictable versus unpredictable targets. Explicit judgments of well-formedness were also elicited in an offline two-alternative forced choice (2AFC) task. Learning was evident in both the acoustic verbal and visual nonverbal tasks, both in online and offline measures, but learning effects were larger both in online and offline tasks in the verbal acoustic condition. We haven’t found evidence for a significant relationship between statistical learning and reading fluency in adolescents in either modality. Together with earlier findings, these results suggest that the relationship between reading and statistical learning is dependent on the domain, modality and nature of the statistical learning task, on the reading task, on the age of participants, and on the specific language. The online target detection task is a promising tool which can be adapted to a wider set of tasks to further explore the contribution of statistical learning to reading acquisition in participants from different populations.