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Hu A, Kozloff V, Owen Van Horne A, Chugani D, Qi Z. Dissociation Between Linguistic and Nonlinguistic Statistical Learning in Children with Autism. J Autism Dev Disord 2024; 54:1912-1927. [PMID: 36749457 PMCID: PMC10404646 DOI: 10.1007/s10803-023-05902-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/11/2023] [Indexed: 02/08/2023]
Abstract
Statistical learning (SL), the ability to detect and extract regularities from inputs, is considered a domain-general building block for typical language development. We compared 55 verbal children with autism (ASD, 6-12 years) and 50 typically-developing children in four SL tasks. The ASD group exhibited reduced learning in the linguistic SL tasks (syllable and letter), but showed intact learning for the nonlinguistic SL tasks (tone and image). In the ASD group, better linguistic SL was associated with higher language skills measured by parental report and sentence recall. Therefore, the atypicality of SL in autism is not domain-general but tied to specific processing constraints related to verbal stimuli. Our findings provide a novel perspective for understanding language heterogeneity in autism.
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Affiliation(s)
- Anqi Hu
- Department of Linguistics and Cognitive Science, University of Delaware, 125 E Main St., Newark, DE, 19716, USA.
| | - Violet Kozloff
- Department of Linguistics and Cognitive Science, University of Delaware, 125 E Main St., Newark, DE, 19716, USA
- Department of Communication Sciences and Disorders, Northwestern University, Evanston, IL, USA
| | - Amanda Owen Van Horne
- Department of Communication Sciences and Disorders, University of Delaware, Newark, DE, USA
| | - Diane Chugani
- Department of Communication Sciences and Disorders, University of Delaware, Newark, DE, USA
| | - Zhenghan Qi
- Department of Linguistics and Cognitive Science, University of Delaware, 125 E Main St., Newark, DE, 19716, USA
- Department of Communication Sciences and Disorders, Northeastern University, Boston, MA, USA
- Department of Psychology, Northeastern University, Boston, MA, USA
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2
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Bettoni R, Riva V, Molteni M, Macchi Cassia V, Bulf H, Cantiani C. Rules generalization in children with dyslexia. RESEARCH IN DEVELOPMENTAL DISABILITIES 2024; 146:104673. [PMID: 38280272 DOI: 10.1016/j.ridd.2024.104673] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 12/29/2023] [Accepted: 01/08/2024] [Indexed: 01/29/2024]
Abstract
BACKGROUND Rule learning (RL) is the ability to extract and generalize higher-order repetition-based structures. Children with Developmental Dyslexia (DD) often report difficulties in learning complex regularities in sequential stimuli, which might be due to the complexity of the rule to be learned. Learning high-order repetition-based rules represents a building block for the development of language skills. AIMS This study investigates the ability to extract and generalize simple, repetition-based visual rules (e.g., ABA) in 8-11-year-old children without (TD) and with a diagnosis of Development Dyslexia (DD) and its relationship with language and reading skills. METHOD Using a forced-choice paradigm, children were first exposed to a visual sequence containing a repetition-based rule (e.g., ABA) and were then asked to recognize familiar and novel rules generated by new visual elements. Standardized language and reading tests were also administered to both groups. RESULTS The accuracy in recognizing rules was above chance for both groups, even though DD children were less accurate than TD children, suggesting a less efficient RL mechanism in the DD group. Moreover, visual RL was positively correlated with both language and reading skills. CONCLUSION These results further confirm the crucial role of RL in the acquisition of linguistic skills and mastering reading abilities.
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Affiliation(s)
- Roberta Bettoni
- Department of Psychology, University of Milano-Bicocca, Milan, Italy.
| | - Valentina Riva
- Child Psychopathology Unit, Scientific Institute, IRCCS E. Medea, Bosisio Parini, Lecco, Italy
| | - Massimo Molteni
- Child Psychopathology Unit, Scientific Institute, IRCCS E. Medea, Bosisio Parini, Lecco, Italy
| | | | - Hermann Bulf
- Department of Psychology, University of Milano-Bicocca, Milan, Italy
| | - Chiara Cantiani
- Child Psychopathology Unit, Scientific Institute, IRCCS E. Medea, Bosisio Parini, Lecco, Italy
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3
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Abreu R, Postarnak S, Vulchanov V, Baggio G, Vulchanova M. The association between statistical learning and language development during childhood: A scoping review. Heliyon 2023; 9:e18693. [PMID: 37554804 PMCID: PMC10405008 DOI: 10.1016/j.heliyon.2023.e18693] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 07/09/2023] [Accepted: 07/25/2023] [Indexed: 08/10/2023] Open
Abstract
The statistical account of language acquisition asserts that language is learned through computations on the statistical regularities present in natural languages. This type of account can predict variability in language development measures as arising from individual differences in extracting this statistical information. Given that statistical learning has been attested across different domains and modalities, a central question is which modality is more tightly yoked with language skills. The results of a scoping review, which aimed for the first time at identifying the evidence of the association between statistical learning skills and language outcomes in typically developing infants and children, provide preliminary support for the statistical learning account of language acquisition, mostly in the domain of lexical outcomes, indicating that typically developing infants and children with stronger auditory and audio-visual statistical learning skills perform better on lexical competence tasks. The results also suggest that the relevance of statistical learning skills for language development is dependent on sensory modality.
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Affiliation(s)
- Regina Abreu
- Language Acquisition and Language Processing Lab, Norwegian University of Science and Technology – Trondheim, Norway
| | | | - Valentin Vulchanov
- Language Acquisition and Language Processing Lab, Norwegian University of Science and Technology – Trondheim, Norway
| | - Giosuè Baggio
- Language Acquisition and Language Processing Lab, Norwegian University of Science and Technology – Trondheim, Norway
| | - Mila Vulchanova
- Language Acquisition and Language Processing Lab, Norwegian University of Science and Technology – Trondheim, Norway
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Potter CE, Lew-Williams C. Frequent vs. infrequent words shape toddlers' real-time sentence comprehension. JOURNAL OF CHILD LANGUAGE 2023:1-11. [PMID: 37401467 PMCID: PMC10764636 DOI: 10.1017/s0305000923000387] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/05/2023]
Abstract
We examined how noun frequency and the typicality of surrounding linguistic context contribute to children's real-time comprehension. Monolingual English-learning toddlers viewed pairs of pictures while hearing sentences with typical or atypical sentence frames (Look at the… vs. Examine the…), followed by nouns that were higher- or lower-frequency labels for a referent (horse vs. pony). Toddlers showed no significant differences in comprehension of nouns in typical and atypical sentence frames. However, they were less accurate in recognizing lower-frequency nouns, particularly among toddlers with smaller vocabularies. We conclude that toddlers can recognize nouns in diverse sentence contexts, but their representations develop gradually.
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Affiliation(s)
- Christine E Potter
- Department of Psychology, University of Texas at El Paso, USA
- Department of Psychology, Princeton University, USA
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5
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Lukács Á, Dobó D, Szőllősi Á, Németh K, Lukics KS. Reading fluency and statistical learning across modalities and domains: Online and offline measures. PLoS One 2023; 18:e0281788. [PMID: 36952465 PMCID: PMC10035921 DOI: 10.1371/journal.pone.0281788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 02/01/2023] [Indexed: 03/25/2023] Open
Abstract
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.
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Affiliation(s)
- Ágnes Lukács
- Department of Cognitive Science, Budapest University of Technology and Economics, Budapest, Hungary
- MTA-BME Momentum Language Acquisition Research Group, Eötvös Loránd Research Network (ELKH), Budapest, Hungary
| | - Dorottya Dobó
- Department of Cognitive Science, Budapest University of Technology and Economics, Budapest, Hungary
- MTA-BME Momentum Language Acquisition Research Group, Eötvös Loránd Research Network (ELKH), Budapest, Hungary
| | - Ágnes Szőllősi
- Institute of Cognitive Neuroscience and Psychology, Eötvös Loránd Research Network (ELKH), Budapest, Hungary
- Centre for Cognitive Medicine, University of Szeged, Szeged, Hungary
| | - Kornél Németh
- Department of Cognitive Science, Budapest University of Technology and Economics, Budapest, Hungary
| | - Krisztina Sára Lukics
- Department of Cognitive Science, Budapest University of Technology and Economics, Budapest, Hungary
- MTA-BME Momentum Language Acquisition Research Group, Eötvös Loránd Research Network (ELKH), Budapest, Hungary
- * E-mail:
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6
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Antovich DM, Graf Estes K. Statistical word segmentation: Anchoring learning across contexts. INFANCY 2023; 28:257-276. [PMID: 36536549 DOI: 10.1111/infa.12525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 09/09/2022] [Accepted: 10/31/2022] [Indexed: 12/24/2022]
Abstract
The present experiments were designed to assess infants' abilities to use syllable co-occurrence regularities to segment fluent speech across contexts. Specifically, we investigated whether 9-month-old infants could use statistical regularities in one speech context to support speech segmentation in a second context. Contexts were defined by different word sets representing contextual differences that might occur across conversations or utterances. This mimics the integration of information across multiple interactions within a single language, which is critical for language acquisition. In particular, we performed two experiments to assess whether a statistically segmented word could be used to anchor segmentation in a second, more challenging context, namely speech with variable word lengths. The results of Experiment 1 were consistent with past work suggesting that statistical learning may be hindered by speech with word-length variability, which is inherent to infants' natural speech environments. In Experiment 2, we found that infants could use a previously statistically segmented word to support word segmentation in a novel, challenging context. We also present findings suggesting that this ability was associated with infants' early word knowledge but not their performance on a cognitive development assessment.
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Affiliation(s)
- Dylan M Antovich
- Center for Mind and Brain, Psychology Department, University of California, Davis, Davis, California, USA
| | - Katharine Graf Estes
- Center for Mind and Brain, Psychology Department, University of California, Davis, Davis, California, USA
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7
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Lukics KS, Lukács Á. Modality, presentation, domain and training effects in statistical learning. Sci Rep 2022; 12:20878. [PMID: 36463280 PMCID: PMC9719496 DOI: 10.1038/s41598-022-24951-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 11/22/2022] [Indexed: 12/07/2022] Open
Abstract
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.
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Affiliation(s)
- Krisztina Sára Lukics
- grid.6759.d0000 0001 2180 0451Department of Cognitive Science, Budapest University of Technology and Economics, Műegyetem rkp. 3., H-1111 Budapest, Hungary ,grid.5018.c0000 0001 2149 4407MTA-BME Momentum Language Acquisition Research Group, Eötvös Loránd Research Network (ELKH), Budapest, Hungary
| | - Ágnes Lukács
- grid.6759.d0000 0001 2180 0451Department of Cognitive Science, Budapest University of Technology and Economics, Műegyetem rkp. 3., H-1111 Budapest, Hungary ,grid.5018.c0000 0001 2149 4407MTA-BME Momentum Language Acquisition Research Group, Eötvös Loránd Research Network (ELKH), Budapest, Hungary
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Ruba AL, Pollak SD, Saffran JR. Acquiring Complex Communicative Systems: Statistical Learning of Language and Emotion. Top Cogn Sci 2022; 14:432-450. [PMID: 35398974 PMCID: PMC9465951 DOI: 10.1111/tops.12612] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2011] [Revised: 03/16/2022] [Accepted: 03/17/2022] [Indexed: 11/30/2022]
Abstract
During the early postnatal years, most infants rapidly learn to understand two naturally evolved communication systems: language and emotion. While these two domains include different types of content knowledge, it is possible that similar learning processes subserve their acquisition. In this review, we compare the learnable statistical regularities in language and emotion input. We then consider how domain-general learning abilities may underly the acquisition of language and emotion, and how this process may be constrained in each domain. This comparative developmental approach can advance our understanding of how humans learn to communicate with others.
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Affiliation(s)
- Ashley L. Ruba
- Department of PsychologyUniversity of Wisconsin – Madison
| | - Seth D. Pollak
- Department of PsychologyUniversity of Wisconsin – Madison
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Ellis Weismer S, Saffran JR. Differences in Prediction May Underlie Language Disorder in Autism. Front Psychol 2022; 13:897187. [PMID: 35756305 PMCID: PMC9221834 DOI: 10.3389/fpsyg.2022.897187] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 05/19/2022] [Indexed: 01/01/2023] Open
Abstract
Language delay is often one of the first concerns of parents of toddlers with autism spectrum disorder (ASD), and early language abilities predict broader outcomes for children on the autism spectrum. Yet, mechanisms underlying language deficits in autistic children remain underspecified. One prominent component of linguistic behavior is the use of predictions or expectations during learning and processing. Several researcher teams have posited prediction deficit accounts of ASD. The basic assumption of the prediction accounts is that information is processed by making predictions and testing violations against expectations (prediction errors). Flexible (neurotypical) brains attribute differential weights to prediction errors to determine when new learning is appropriate, while autistic individuals are thought to assign disproportionate weight to prediction errors. According to some views, these prediction deficits are hypothesized to lead to higher levels of perceived novelty, resulting in “hyperplasticity” of learning based on the most recent input. In this article, we adopt the perspective that it would be useful to investigate whether language deficits in children with ASD can be attributed to atypical domain-general prediction processes.
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Affiliation(s)
- Susan Ellis Weismer
- Waisman Center, University of Wisconsin, Madison, WI, United States.,Department of Communication Sciences and Disorders, University of Wisconsin, Madison, WI, United States
| | - Jenny R Saffran
- Waisman Center, University of Wisconsin, Madison, WI, United States.,Department of Psychology, University of Wisconsin, Madison, WI, United States
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10
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Polyanskaya L, Manrique HM, Samuel AG, Marín A, García‐Palacios A, Ordin M. Intermodality differences in statistical learning: phylogenetic and ontogenetic influences. Ann N Y Acad Sci 2022; 1511:191-209. [DOI: 10.1111/nyas.14749] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 12/07/2021] [Accepted: 12/19/2021] [Indexed: 12/01/2022]
Affiliation(s)
- Leona Polyanskaya
- Departamento de Psicología y Sociología Universidad de Zaragoza Teruel Spain
| | - Héctor M. Manrique
- Departamento de Psicología y Sociología Universidad de Zaragoza Teruel Spain
| | - Arthur G. Samuel
- Department of Psychology Stony Brook University New York City New York
- Basque Centre on Cognition Brain and Language San Sebastian Spain
| | | | - Azucena García‐Palacios
- Department of Basic Psychology, Clinical and Psychobiology Jaume I University Castellon Spain
- CIBER Fisiopatología Obesidad y Nutrición (CIBERObn) Instituto Carlos III Madrid Spain
| | - Mikhail Ordin
- Universität Konstanz Allgemeine Sprachwissenschaft Konstanz Germany
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11
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Bogaerts L, Siegelman N, Christiansen MH, Frost R. Is there such a thing as a 'good statistical learner'? Trends Cogn Sci 2021; 26:25-37. [PMID: 34810076 DOI: 10.1016/j.tics.2021.10.012] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2021] [Revised: 10/23/2021] [Accepted: 10/25/2021] [Indexed: 12/31/2022]
Abstract
A growing body of research investigates individual differences in the learning of statistical structure, tying them to variability in cognitive (dis)abilities. This approach views statistical learning (SL) as a general individual ability that underlies performance across a range of cognitive domains. But is there a general SL capacity that can sort individuals from 'bad' to 'good' statistical learners? Explicating the suppositions underlying this approach, we suggest that current evidence supporting it is meager. We outline an alternative perspective that considers the variability of statistical environments within different cognitive domains. Once we focus on learning that is tuned to the statistics of real-world sensory inputs, an alternative view of SL computations emerges with a radically different outlook for SL research.
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Affiliation(s)
- Louisa Bogaerts
- Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands.
| | | | - Morten H Christiansen
- Haskins Laboratories, New Haven, CT 06511, USA; Cornell University, Ithaca, NY 14850, USA; Aarhus University, 8000 Aarhus, Denmark
| | - Ram Frost
- Haskins Laboratories, New Haven, CT 06511, USA; The Hebrew University of Jerusalem, 91905 Jerusalem, Israel; Basque Center for Cognition, Brain, and Language, 20009 Donostia, Spain
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12
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Ellis EM, Borovsky A, Elman JL, Evans JL. Toddlers' Ability to Leverage Statistical Information to Support Word Learning. Front Psychol 2021; 12:600694. [PMID: 33897523 PMCID: PMC8063043 DOI: 10.3389/fpsyg.2021.600694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Accepted: 02/15/2021] [Indexed: 12/14/2022] Open
Abstract
PURPOSE This study investigated whether the ability to utilize statistical regularities from fluent speech and map potential words to meaning at 18-months predicts vocabulary at 18- and again at 24-months. METHOD Eighteen-month-olds (N = 47) were exposed to an artificial language with statistical regularities within the speech stream, then participated in an object-label learning task. Learning was measured using a modified looking-while-listening eye-tracking design. Parents completed vocabulary questionnaires when their child was 18-and 24-months old. RESULTS Ability to learn the object-label pairing for words after exposure to the artificial language predicted productive vocabulary at 24-months and amount of vocabulary change from 18- to 24 months, independent of non-verbal cognitive ability, socio-economic status (SES) and/or object-label association performance. CONCLUSION Eighteen-month-olds' ability to use statistical information derived from fluent speech to identify words within the stream of speech and then to map the "words" to meaning directly predicts vocabulary size at 24-months and vocabulary change from 18 to 24 months. The findings support the hypothesis that statistical word segmentation is one of the important aspects of word learning and vocabulary acquisition in toddlers.
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Affiliation(s)
- Erica M. Ellis
- Department of Communication Disorders, California State University, Los Angeles, Los Angeles, CA, United States
| | - Arielle Borovsky
- Department of Speech, Language, and Hearing Sciences, Purdue University, West Lafayette, IN, United States
| | - Jeffrey L. Elman
- Center for Research in Language, University of California, San Diego, La Jolla, CA, United States
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA, United States
| | - Julia L. Evans
- School of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX, United States
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13
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Abstract
Visual reaction times to target pictures after naming events are an informative measurement in language acquisition research, because gaze shifts measured in looking-while-listening paradigms are an indicator of infants' lexical speed of processing. This measure is very useful, as it can be applied from a young age onwards and has been linked to later language development. However, to obtain valid reaction times, the infant is required to switch the fixation of their eyes from a distractor to a target object. This means that usually at least half the trials have to be discarded-those where the participant is already fixating the target at the onset of the target word-so that no reaction time can be measured. With few trials, reliability suffers, which is especially problematic when studying individual differences. In order to solve this problem, we developed a gaze-triggered looking-while-listening paradigm. The trials do not differ from the original paradigm apart from the fact that the target object is chosen depending on the infant's eye fixation before naming. The object the infant is looking at becomes the distractor and the other object is used as the target, requiring a fixation switch, and thus providing a reaction time. We tested our paradigm with forty-three 18-month-old infants, comparing the results to those from the original paradigm. The Gaze-triggered paradigm yielded more valid reaction time trials, as anticipated. The results of a ranked correlation between the conditions confirmed that the manipulated paradigm measures the same concept as the original paradigm.
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Affiliation(s)
- Julia Egger
- Max Planck Institute for Psycholinguistics, Wundtlaan 1, 6525XD, Nijmegen, The Netherlands.
| | - Caroline F Rowland
- Max Planck Institute for Psycholinguistics, Wundtlaan 1, 6525XD, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Christina Bergmann
- Max Planck Institute for Psycholinguistics, Wundtlaan 1, 6525XD, Nijmegen, The Netherlands
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14
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Bergelson E. The Comprehension Boost in Early Word Learning: Older Infants Are Better Learners. CHILD DEVELOPMENT PERSPECTIVES 2020; 14:142-149. [PMID: 33569084 PMCID: PMC7872330 DOI: 10.1111/cdep.12373] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Recent research has revealed that infants begin understanding words at around 6 months. After that, infants' comprehension vocabulary increases gradually in a linear way over 8-18 months, according to data from parental checklists. In contrast, infants' word comprehension improves robustly, qualitatively, and in a nonlinear way just after their first birthday, according to data from studies on spoken word comprehension. In this review, I integrate observational and experimental data to explain these divergent results. I argue that infants' comprehension boost is not well-explained by changes in their language input for common words, but rather by proposing that they learn to take better advantage of relatively stable input data. Next, I propose potentially complementary theoretical accounts of what makes older infants better learners. Finally, I suggest how the research community can expand our empirical base in this understudied area, and why doing so will inform our knowledge about child development.
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Choi D, Batterink LJ, Black AK, Paller KA, Werker JF. Preverbal Infants Discover Statistical Word Patterns at Similar Rates as Adults: Evidence From Neural Entrainment. Psychol Sci 2020; 31:1161-1173. [DOI: 10.1177/0956797620933237] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
The discovery of words in continuous speech is one of the first challenges faced by infants during language acquisition. This process is partially facilitated by statistical learning, the ability to discover and encode relevant patterns in the environment. Here, we used an electroencephalogram (EEG) index of neural entrainment to track 6-month-olds’ ( N = 25) segmentation of words from continuous speech. Infants’ neural entrainment to embedded words increased logarithmically over the learning period, consistent with a perceptual shift from isolated syllables to wordlike units. Moreover, infants’ neural entrainment during learning predicted postlearning behavioral measures of word discrimination ( n = 18). Finally, the logarithmic increase in entrainment to words was comparable in infants and adults, suggesting that infants and adults follow similar learning trajectories when tracking probability information among speech sounds. Statistical-learning effects in infants and adults may reflect overlapping neural mechanisms, which emerge early in life and are maintained throughout the life span.
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Affiliation(s)
- Dawoon Choi
- Department of Psychology, University of British Columbia
| | - Laura J. Batterink
- Department of Psychology, Western University
- The Brain and Mind Institute, Western University
| | - Alexis K. Black
- School of Audiology and Speech Sciences, University of British Columbia
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16
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Baek S, Jaffe-Dax S, Emberson LL. How an infant's active response to structured experience supports perceptual-cognitive development. PROGRESS IN BRAIN RESEARCH 2020; 254:167-186. [PMID: 32859286 DOI: 10.1016/bs.pbr.2020.05.015] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Previous research on perceptual and cognitive development has predominantly focused on infants' passive response to experience. For example, if infants are exposed to acoustic patterns in the background while they are engaged in another activity, what are they able to learn? However, recent work in this area has revealed that even very young infants are also capable of active perceptual and cognitive responses to experience. Specifically, recent neuroimaging work showed that infants' perceptual systems predict upcoming sensory events and that learning to predict new events rapidly modulates the responses of their perceptual systems. In addition, there is new evidence that young infants have access to endogenous attention and their prediction and attention are rapidly and robustly modified through learning about patterns in the environment. In this chapter, we present a synthesis of the existing research on the impact of infants' active responses to experience and argue that this active engagement importantly supports infants' perceptual-cognitive development. To this end, we first define what a mechanism of active engagement is and examine how learning, selective attention, and prediction can be considered active mechanisms. Then, we argue that these active mechanisms become engaged in response to higher-order environmental structures, such as temporal, spatial, and relational patterns, and review both behavioral and neural evidence of infants' active responses to these structures or patterns. Finally, we discuss how this active engagement in infancy may give rise to the emergence of specialized perceptual-cognitive systems and highlight directions for future research.
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Affiliation(s)
- Sori Baek
- Psychology Department, Princeton University, Princeton, NJ, United States
| | - Sagi Jaffe-Dax
- Psychology Department, Princeton University, Princeton, NJ, United States
| | - Lauren L Emberson
- Psychology Department, Princeton University, Princeton, NJ, United States.
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Antovich DM, Graf Estes K. One language or two? Navigating cross-language conflict in statistical word segmentation. Dev Sci 2020; 23:e12960. [PMID: 32145042 DOI: 10.1111/desc.12960] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2019] [Revised: 01/22/2020] [Accepted: 02/21/2020] [Indexed: 11/28/2022]
Abstract
Bilingual infants must navigate the similarities and differences between their languages to achieve native proficiency in childhood. Bilinguals learning to find individual words in fluent speech face the possibility of conflicting cues to word boundaries across their languages. Despite this challenge, bilingual infants typically begin to segment and learn words in both languages around the same time as monolinguals. It is possible that early bilingual experience may support infants' abilities to track regularities relevant for word segmentation separately across their languages. In a dual speech stream statistical word segmentation task, we assessed whether 16-month-old infants could track syllable co-occurrence regularities in two artificial languages despite conflicting information across the languages. We found that bilingual, but not monolingual, infants were able to segment the dual speech streams using statistical regularities. Although the two language groups did not differ on secondary measures of cognitive and linguistic development, bilingual infants' real-world experience with bilingual speakers was predictive of their performance in the dual language statistical segmentation task.
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Parks KMA, Griffith LA, Armstrong NB, Stevenson RA. Statistical Learning and Social Competency: The Mediating Role of Language. Sci Rep 2020; 10:3968. [PMID: 32132635 PMCID: PMC7055309 DOI: 10.1038/s41598-020-61047-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Accepted: 02/17/2020] [Indexed: 12/17/2022] Open
Abstract
The current study sought to examine the contribution of auditory and visual statistical learning on language and social competency abilities as well as whether decreased statistical learning abilities are related to increased autistic traits. To answer these questions, participants' (N = 95) auditory and visual statistical learning abilities, language, social competency, and level of autistic traits were assessed. Although the relationships observed were relatively small in magnitude, our results demonstrated that visual statistical learning related to language and social competency abilities and that auditory learning was more related to autism symptomatology than visual statistical learning. Furthermore, the relationship between visual statistical learning and social competency was mediated by language comprehension abilities, suggesting that impairments in statistical learning may cascade into impairments in language and social abilities.
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Affiliation(s)
- Kaitlyn M A Parks
- Western University, Department of Psychology, London, ON, Canada.
- Western University, Brain and Mind Institute, London, ON, Canada.
| | - Laura A Griffith
- Western University, Department of Psychology, London, ON, Canada
- Western University, Brain and Mind Institute, London, ON, Canada
| | - Nicolette B Armstrong
- Western University, Department of Psychology, London, ON, Canada
- Western University, Brain and Mind Institute, London, ON, Canada
| | - Ryan A Stevenson
- Western University, Department of Psychology, London, ON, Canada
- Western University, Brain and Mind Institute, London, ON, Canada
- Western University, Program in Neuroscience, London, ON, Canada
- Western University, Department of Psychiatry, London, ON, Canada
- York University, Centre for Vision Research, Toronto, ON, Canada
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Lany J, Shoaib A. Individual differences in non-adjacent statistical dependency learning in infants. JOURNAL OF CHILD LANGUAGE 2020; 47:483-507. [PMID: 31190666 DOI: 10.1017/s0305000919000230] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
There is considerable controversy over the factors that shape infants' developing knowledge of grammar. Work with artificial languages suggests that infants' ability to track statistical regularities within the speech they hear could, in principle, support grammatical development. However, little work has tested whether infants' performance on laboratory tasks reflects factors that are relevant in real-world language learning. Here we tested whether the language that infants hear at home, and their receptive language skills, predict their performance on tasks assessing the ability to learn non-adjacent statistical dependencies (NADs) at 15 months, and whether that in turn predicts sensitivity to native-language NADs at 18 months. We found evidence for some (though not all) of these relations, and primarily for females. The results suggest that performance on the artificial language-learning task reveals something about the mechanisms of grammatical development, and that females and males may be learning NADs differently.
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Affiliation(s)
- Jill Lany
- Department of Psychology, University of Notre Dame, USA
| | - Amber Shoaib
- Department of Psychology, University of Notre Dame, USA
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20
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Hall JE, Owen Van Horne A, Farmer TA. Individual Differences in Verb Bias Sensitivity in Children and Adults With Developmental Language Disorder. Front Hum Neurosci 2019; 13:402. [PMID: 31803036 PMCID: PMC6877742 DOI: 10.3389/fnhum.2019.00402] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2019] [Accepted: 10/28/2019] [Indexed: 12/02/2022] Open
Abstract
A number of experiments support the hypothetical utility of statistical information for language learning and processing among both children and adults. However, tasks in these studies are often very general, and only a few include populations with developmental language disorder (DLD). We wanted to determine whether a stronger relationship might be shown when the measure of statistical learning is chosen for its relevance to the language task when including a substantial number of participants with DLD. The language ability we measured was sensitivity to verb bias - the likelihood of a verb to appear with a certain argument or interpretation. A previous study showed adults with DLD were less sensitive to verb bias than their typical peers. Verb bias sensitivity had not yet been tested in children with DLD. In Study 1, 49 children, ages 7-9 years, 17 of whom were classified as having DLD, completed a task designed to measure sensitivity to verb bias through implicit and explicit measures. We found children with and without DLD showed sensitivity to verb bias in implicit but not explicit measures, with no differences between groups. In Study 2, we used a multiverse approach to investigate whether individual differences in statistical learning predicted verb bias sensitivity in these participants as well as in a dataset of adult participants. Our analysis revealed no evidence of a relationship between statistical learning and verb bias sensitivity in children, which was not unexpected given we found no group differences in Study 1. Statistical learning predicted sensitivity to verb bias as measured through explicit measures in adults, though results were not robust. These findings suggest that verb bias may still be relatively unstable in school age children, and thus may not play the same role in sentence processing in children as in adults. It would also seem that individuals with DLD may not be using the same mechanisms during processing as their typically developing (TD) peers in adulthood. Thus, statistical information may differ in relevance for language processing in individuals with and without DLD.
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Affiliation(s)
- Jessica E. Hall
- Speech, Language, and Hearing Sciences, The University of Arizona, Tucson, AZ, United States
| | - Amanda Owen Van Horne
- Communication Sciences and Disorders, University of Delaware, Newark, DE, United States
| | - Thomas A. Farmer
- Department of Psychology, California State University, Fullerton, Fullerton, CA, United States
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21
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Do current statistical learning tasks capture stable individual differences in children? An investigation of task reliability across modality. Behav Res Methods 2019; 52:68-81. [DOI: 10.3758/s13428-019-01205-5] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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22
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Hoareau M, Yeung HH, Nazzi T. Infants' statistical word segmentation in an artificial language is linked to both parental speech input and reported production abilities. Dev Sci 2019; 22:e12803. [PMID: 30681753 DOI: 10.1111/desc.12803] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2018] [Revised: 11/26/2018] [Accepted: 01/14/2019] [Indexed: 01/11/2023]
Abstract
Individual variability in infant's language processing is partly explained by environmental factors, like the quantity of parental speech input, as well as by infant-specific factors, like speech production. Here, we explore how these factors affect infant word segmentation. We used an artificial language to ensure that only statistical regularities (like transitional probabilities between syllables) could cue word boundaries, and then asked how the quantity of parental speech input and infants' babbling repertoire predict infants' abilities to use these statistical cues. We replicated prior reports showing that 8-month-old infants use statistical cues to segment words, with a preference for part-words over words (a novelty effect). Crucially, 8-month-olds with larger novelty effects had received more speech input at 4 months and had greater production abilities at 8 months. These findings establish for the first time that the ability to extract statistical information from speech correlates with individual factors in infancy, like early speech experience and language production. Implications of these findings for understanding individual variability in early language acquisition are discussed.
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Affiliation(s)
- Mélanie Hoareau
- Integrative Neuroscience and Cognition Center, Université Paris Descartes, Sorbonne Paris Cité, Paris, France
| | - H Henny Yeung
- Department of Linguistics, Simon Fraser University, Burnaby, BC, Canada
| | - Thierry Nazzi
- Integrative Neuroscience and Cognition Center, Université Paris Descartes, Sorbonne Paris Cité, Paris, France.,CNRS (Integrative Neuroscience and Cognition Center, UMR 8002), Paris, France
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Saffran JR. Statistical learning as a window into developmental disabilities. J Neurodev Disord 2018; 10:35. [PMID: 30541453 PMCID: PMC6292000 DOI: 10.1186/s11689-018-9252-y] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Accepted: 11/14/2018] [Indexed: 01/30/2023] Open
Abstract
Until recently, most behavioral studies of children with intellectual and developmental disabilities (IDD) have used standardized assessments as a means to probe etiology and to characterize phenotypes. Over the past decade, however, tasks originally developed to investigate learning processes in typical development have been brought to bear on developmental processes in children with IDD. This brief review will focus on one learning process in particular—statistical learning—and will provide an overview of what has been learned thus far from studies using statistical learning tasks with different groups of children with IDD conditions. While a full picture is not yet available, results to date suggest that studies of learning are both feasible and informative about learning processes that may differ across diagnostic groups, particularly as they relate to language acquisition. More generally, studies focused on learning processes may be highly informative about different developmental trajectories both across groups and within groups of children.
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Affiliation(s)
- Jenny R Saffran
- Waisman Center, University of Wisconsin-Madison, 1500 Highland Ave, Madison, WI, 53705, USA.
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