4 research outputs found

    Audio-visual speech perception: a developmental ERP investigation

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    Being able to see a talking face confers a considerable advantage for speech perception in adulthood. However, behavioural data currently suggest that children fail to make full use of these available visual speech cues until age 8 or 9. This is particularly surprising given the potential utility of multiple informational cues during language learning. We therefore explored this at the neural level. The event-related potential (ERP) technique has been used to assess the mechanisms of audio-visual speech perception in adults, with visual cues reliably modulating auditory ERP responses to speech. Previous work has shown congruence-dependent shortening of auditory N1/P2 latency and congruence-independent attenuation of amplitude in the presence of auditory and visual speech signals, compared to auditory alone. The aim of this study was to chart the development of these well-established modulatory effects over mid-to-late childhood. Experiment 1 employed an adult sample to validate a child-friendly stimulus set and paradigm by replicating previously observed effects of N1/P2 amplitude and latency modulation by visual speech cues; it also revealed greater attenuation of component amplitude given incongruent audio-visual stimuli, pointing to a new interpretation of the amplitude modulation effect. Experiment 2 used the same paradigm to map cross-sectional developmental change in these ERP responses between 6 and 11 years of age. The effect of amplitude modulation by visual cues emerged over development, while the effect of latency modulation was stable over the child sample. These data suggest that auditory ERP modulation by visual speech represents separable underlying cognitive processes, some of which show earlier maturation than others over the course of development

    Neuro-myths in the classroom

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    Have you ever heard that we only use 10% of our brains? It is a nice thought that we could tap into hidden brain power—but could most of our brains really be doing nothing all day? No! Every bit of your brain is busy 24 hours a day. There are lots of these so-called neuro-myths floating around: ideas about the brain that sound true, but are not. There is usually a good reason why a neuro-myth got started: maybe there is an element of truth to it, or maybe people would just like it to be true. In this article we explore three widely believed neuro-myths about the growing brain, and explain why it is important for you to know what is true and what is not. We will explore whether you can change how clever you are, whether girls and boys think differently from each other, and whether some children are “left brained” and some are “right brained.

    Applications of cross-sectional methodologies in developmental psychology

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    Book synopsis: Fully revised and updated, the second edition of the International Encyclopedia of the Social and Behavioral Sciences, first published in 2001, offers a source of social and behavioral sciences reference material that is broader and deeper than any other. Available in both print and online editions, it comprises over 3,900 articles, commissioned by 71 Section Editors, and includes 90,000 bibliographic references as well as comprehensive name and subject indexes

    Mechanisms of developmental regression in autism and the broader phenotype: a neural network modeling approach.

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    Loss of previously established behaviors in early childhood constitutes a markedly atypical developmental trajectory. It is found almost uniquely in autism and its cause is currently unknown (Baird et al., 2008). We present an artificial neural network model of developmental regression, exploring the hypothesis that regression is caused by overaggressive synaptic pruning and identifying the mechanisms involved. We used a novel population-modeling technique to investigate developmental deficits, in which both neurocomputational parameters and the learning environment were varied across a large number of simulated individuals. Regression was generated by the atypical setting of a single pruning-related parameter. We observed a probabilistic relationship between the atypical pruning parameter and the presence of regression, as well as variability in the onset, severity, behavioral specificity, and recovery from regression. Other neurocomputational parameters that varied across the population modulated the risk that an individual would show regression. We considered a further hypothesis that behavioral regression may index an underlying anomaly characterizing the broader autism phenotype. If this is the case, we show how the model also accounts for several additional findings: shared gene variants between autism and language impairment (Vernes et al., 2008); larger brain size in autism but only in early development (Redcay & Courchesne, 2005); and the possibility of quasi-autism, caused by extreme environmental deprivation (Rutter et al., 1999). We make a novel prediction that the earliest developmental symptoms in the emergence of autism should be sensory and motor rather than social and review empirical data offering preliminary support for this prediction
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