Intermodality differences in statistical learning: phylogenetic and ontogenetic influences

In Basque–Spanish bilinguals, statistical learning (SL) in the visual modality was more efficient on nonlinguistic than linguistic input; in the auditory modality, we found the reverse pattern of results. We hypothesize that SL was shaped for processing nonlinguistic environmental stimuli and only later, as the language faculty emerged, recycled for speech processing. This led to further adaptive changes in the neurocognitive mechanisms underlying speech processing, including SL. By contrast, as a recent cultural innovation, written language has not yet led to adaptations. The current study investigated whether such phylogenetic influences on SL can be modulated by ontogenetic influences on a shorter timescale, over the course of individual development. We explored how SL is modulated by the ambient linguistic environment. We found that SL in the auditory modality can be further modulated by exposure to a bilingual environment, in which speakers need to process a wider range of diverse speech cues. This effect was observed only on linguistic, not nonlinguistic, material. We conclude that ontogenetic factors modulate the efficiency of already existing SL ability, honing it for specific types of input, by providing new targets for selection via exposure to different cues in the sensory input.

[1]  J. Rueckl,et al.  INDIVIDUAL DIFFERENCES IN L2 LITERACY ACQUISITION , 2021, Studies in Second Language Acquisition.

[2]  S. Tsuji,et al.  Quantifying the role of rhythm in infants' language discrimination abilities: A meta-analysis , 2021, Cognition.

[3]  N. Sebastián-Gallés,et al.  The ontogeny of early language discrimination: Beyond rhythm , 2021, Cognition.

[4]  Mikhail Ordin,et al.  An evolutionary account of intermodality differences in statistical learning , 2020, Annals of the New York Academy of Sciences.

[5]  S. Tsuji,et al.  Quantifying the role of rhythm in infants' language discrimination abilities: A meta-analysis , 2020, Cognition.

[6]  Noam Siegelman,et al.  Statistical learning abilities and their relation to language , 2020, Lang. Linguistics Compass.

[7]  Christopher M. Conway How does the brain learn environmental structure? Ten core principles for understanding the neurocognitive mechanisms of statistical learning , 2020, Neuroscience & Biobehavioral Reviews.

[8]  David Soto,et al.  Neural bases of learning and recognition of statistical regularities , 2020, Annals of the New York Academy of Sciences.

[9]  Karl J. Friston,et al.  The hierarchically mechanistic mind: an evolutionary systems theory of the human brain, cognition, and behavior , 2019, Cognitive, Affective, & Behavioral Neuroscience.

[10]  Shani Kahta,et al.  Deficits in statistical leaning of auditory sequences among adults with dyslexia. , 2019, Dyslexia.

[11]  Nicola Molinaro,et al.  Electrophysiology of statistical learning: Exploring the online learning process and offline learning product , 2019, The European journal of neuroscience.

[12]  J. Saffran Statistical learning as a window into developmental disabilities , 2018, Journal of Neurodevelopmental Disorders.

[13]  Dare A. Baldwin,et al.  Attention reorganizes as structure is detected in dynamic action , 2018, Memory & Cognition.

[14]  C. Petkov,et al.  Evolutionarily conserved neural signatures involved in sequencing predictions and their relevance for language , 2018, Current Opinion in Behavioral Sciences.

[15]  J. Mehler,et al.  Rhythm in language acquisition , 2017, Neuroscience & Biobehavioral Reviews.

[16]  Katharine Graf Estes,et al.  Infant statistical-learning ability is related to real-time language processing* , 2017, Journal of Child Language.

[17]  Christopher I. Petkov,et al.  Auditory and Visual Sequence Learning in Humans and Monkeys using an Artificial Grammar Learning Paradigm , 2017, Neuroscience.

[18]  Alexander Todorov,et al.  Statistical learning shapes face evaluation , 2016, Nature Human Behaviour.

[19]  R. Henson,et al.  A watershed model of individual differences in fluid intelligence , 2016, Neuropsychologia.

[20]  Shani Kahta,et al.  Implicit learning deficits among adults with developmental dyslexia , 2016, Annals of dyslexia.

[21]  Erik D. Thiessen,et al.  Statistical learning of language: Theory, validity, and predictions of a statistical learning account of language acquisition , 2015 .

[22]  Teresa Cabré,et al.  Intonational phonology of Catalan and its dialectal varieties , 2015 .

[23]  Pilar Prieto,et al.  Intonation in Romance: Systemic similarities and differences , 2015 .

[24]  Morten H. Christiansen,et al.  Domain generality versus modality specificity: the paradox of statistical learning , 2015, Trends in Cognitive Sciences.

[25]  J. Hualde,et al.  Intonation in Basque , 2014 .

[26]  Yukiko Kikuchi,et al.  Auditory Artificial Grammar Learning in Macaque and Marmoset Monkeys , 2013, The Journal of Neuroscience.

[27]  Aaron R. Seitz,et al.  The effect of statistical learning on internal stimulus representations: Predictable items are enhanced even when not predicted , 2013, Cognition.

[28]  Richard N. Aslin,et al.  The neural correlates of statistical learning in a word segmentation task: An fMRI study , 2013, Brain and Language.

[29]  J. Chiang,et al.  STUDIES IN ASTRONOMICAL TIME SERIES ANALYSIS. VI. BAYESIAN BLOCK REPRESENTATIONS , 2012, 1207.5578.

[30]  Pilar Prieto,et al.  Phonotactic and phrasal properties of speech rhythm. Evidence from Catalan, English, and Spanish , 2012, Speech Commun..

[31]  W. May,et al.  Brief Report: Concurrent Validity of the Leiter-R and KBIT-2 Scales of Nonverbal Intelligence for Children with Autism and Language Impairments , 2012, Journal of autism and developmental disorders.

[32]  Morten H. Christiansen,et al.  Statistical Learning and Language: An Individual Differences Study , 2012 .

[33]  B. Tversky,et al.  The shape of action. , 2011, Journal of experimental psychology. General.

[34]  T. Gollan,et al.  Self-ratings of spoken language dominance: A Multilingual Naming Test (MINT) and preliminary norms for young and aging Spanish–English bilinguals* , 2011, Bilingualism: Language and Cognition.

[35]  Alexa R. Romberg,et al.  Statistical learning and language acquisition. , 2010, Wiley interdisciplinary reviews. Cognitive science.

[36]  J. I. Hualde,et al.  Goizueta Basque , 2010, Journal of the International Phonetic Association.

[37]  Richard N Aslin,et al.  Statistical learning of adjacent and nonadjacent dependencies among nonlinguistic sounds , 2009, Psychonomic bulletin & review.

[38]  J. Mehler,et al.  Bootstrapping word order in prelexical infants: A Japanese–Italian cross-linguistic study , 2008, Cognitive Psychology.

[39]  Dare A. Baldwin,et al.  Segmenting dynamic human action via statistical structure , 2008, Cognition.

[40]  Irene Vogel,et al.  Prosodic Phonology: With a new foreword , 2007 .

[41]  Mariapaola D'Imperio,et al.  The phonetics and phonology of intonational phrasing in Romance , 2007 .

[42]  J. B. Trobalon,et al.  Statistical computations over a speech stream in a rodent , 2005, Perception & psychophysics.

[43]  Karl J. Friston,et al.  A theory of cortical responses , 2005, Philosophical Transactions of the Royal Society B: Biological Sciences.

[44]  A. M. Fernández-Planas,et al.  Castilian Spanish , 2003, Journal of the International Phonetic Association.

[45]  J. Saffran Statistical Language Learning , 2003 .

[46]  J. Saffran Constraints on Statistical Language Learning , 2002 .

[47]  Scott P. Johnson,et al.  Visual statistical learning in infancy: evidence for a domain general learning mechanism , 2002, Cognition.

[48]  Jessica Maye,et al.  Infant sensitivity to distributional information can affect phonetic discrimination , 2002, Cognition.

[49]  Jodie A. Baird,et al.  Discerning intentions in dynamic human action , 2001, Trends in Cognitive Sciences.

[50]  E. Vajda Handbook of the International Phonetic Association: A Guide to the Use of the International Phonetic Alphabet , 2000 .

[51]  Marc Pierce,et al.  Word Prosodic Systems in the Languages of Europe , 2000 .

[52]  Thierry Dutoit,et al.  MBR-PSOLA: Text-To-Speech synthesis based on an MBE re-synthesis of the segments database , 1993, Speech Commun..

[53]  Melissa L. Allen,et al.  Kaufman Brief Intelligence Test , 2021, Encyclopedia of Autism Spectrum Disorders.

[54]  K. Pugh,et al.  Domain Generality and Specificity of Statistical Learning and its Relation with Reading Ability , 2018 .

[55]  Evan Kidd,et al.  Individual Differences in Statistical Learning Predict Children's Comprehension of Syntax. , 2016, Child development.

[56]  Evan Kidd,et al.  Implicit statistical learning is directly associated with the acquisition of syntax. , 2012, Developmental psychology.

[57]  Morten H. Christiansen,et al.  Modality-constrained statistical learning of tactile, visual, and auditory sequences. , 2005, Journal of experimental psychology. Learning, memory, and cognition.

[58]  C. Gussenhoven The phonology of tone and intonation , 2004 .

[59]  Sónia Frota,et al.  Intonational phrasing in Romance: The role of syntactic and prosodic structure , 2004 .

[60]  L. Alloy,et al.  Assessment of covariation by humans and animals: the joint influence of prior expectations and current situational information. , 1984, Psychological review.

[61]  J. Scargle Studies in astronomical time series analysis. I - Modeling random processes in the time domain , 1981 .

[62]  Max W Wheeler,et al.  The Phonology of Catalan , 1979 .