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Using computational modeling to understand the interaction between risk and protective factors in reading disability ...
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Using computational modeling to understand the interaction between risk and protective factors in reading disability ...
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Individual differences in learning the regularities between orthography, phonology and semantics predict early reading skills
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In: J Mem Lang (2020)
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Top-Down Grouping Affects Adjacent Dependency Learning
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In: Psychology Faculty Publications (2020)
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Age -limited learning effects in reading and speech perception ...
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Zevin, Jason D.. - : University of Southern California Digital Library (USC.DL), 2016
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The Neural Correlates of the Interaction between Semantic and Phonological Processing for Chinese Character Reading
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Universal brain signature of proficient reading: Evidence from four contrasting languages.
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In: Proceedings of the National Academy of Sciences of the United States of America, vol 112, iss 50 (2015)
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Universal brain signature of proficient reading: Evidence from four contrasting languages
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Selective attention to phonology dynamically modulates initial encoding of auditory words within the left hemisphere ...
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On the Same Wavelength: Predictable Language Enhances Speaker–Listener Brain-to-Brain Synchrony in Posterior Superior Temporal Gyrus
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Selective attention to phonology dynamically modulates initial encoding of auditory words within the left hemisphere
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In: Yoncheva, Yuliya; Maurer, Urs; Zevin, Jason D; McCandliss, Bruce D (2014). Selective attention to phonology dynamically modulates initial encoding of auditory words within the left hemisphere. NeuroImage, 97:262-270. (2014)
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Effects of rhyme and spelling patterns on auditory word ERPs depend on selective attention to phonology
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Is Statistical Learning Constrained by Lower Level Perceptual Organization?
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Abstract:
In order for statistical information to aid in complex developmental processes such as language acquisition, learning from higher-order statistics (e.g. across successive syllables in a speech stream to support segmentation) must be possible while perceptual abilities (e.g. speech categorization) are still developing. The current study examines how perceptual organization interacts with statistical learning. Adult participants were presented with multiple exemplars from novel, complex sound categories designed to reflect some of the spectral complexity and variability of speech. These categories were organized into sequential pairs and presented such that higher-order statistics, defined based on sound categories, could support stream segmentation. Perceptual similarity judgments and multi-dimensional scaling revealed that participants only perceived three perceptual clusters of sounds and thus did not distinguish the four experimenter-defined categories, creating a tension between lower level perceptual organization and higher-order statistical information. We examined whether the resulting pattern of learning is more consistent with statistical learning being “bottom-up,” constrained by the lower levels of organization, or “top-down,” such that higher-order statistical information of the stimulus stream takes priority over the perceptual organization, and perhaps influences perceptual organization. We consistently find evidence that learning is constrained by perceptual organization. Moreover, participants generalize their learning to novel sounds that occupy a similar perceptual space, suggesting that statistical learning occurs based on regions of or clusters in perceptual space. Overall, these results reveal a constraint on learning of sound sequences, such that statistical information is determined based on lower level organization. These findings have important implications for the role of statistical learning in language acquisition.
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URL: http://www.ncbi.nlm.nih.gov/pubmed/23618755 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4020322 https://doi.org/10.1016/j.cognition.2012.12.006
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Task by stimulus interactions in brain responses during Chinese character processing
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Orthographic influences on division of labor in learning to read Chinese and English: Insights from computational modeling
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