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Communication Challenges Faced by Spanish-Speaking Caregivers of Children with Medical Complexity: a Qualitative Study
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In: J Racial Ethn Health Disparities (2021)
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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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The Visual Array Task: A Novel Gaze-Based Measure of Object Label and Category Knowledge
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In: Dev Sci (2020)
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Differential Activation of the Visual Word Form Area During Auditory Phoneme Perception in Youth with Dyslexia
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In: Neuropsychologia (2020)
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Transcranial direct current stimulation to treat aphasia: Longitudinal analysis of a randomized controlled trial
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Interoperability of Medication Classification Systems: Lessons Learned Mapping Established Pharmacologic Classes (EPCs) to SNOMED CT
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Predicting brain activation patterns associated with individual lexical concepts based on five sensory-motor attributes
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Abstract:
While major advances have been made in uncovering the neural processes underlying perceptual representations, our grasp of how the brain gives rise to conceptual knowledge remains relatively poor. Recent work has provided strong evidence that concepts rely, at least in part, on the same sensory and motor neural systems through which they were acquired, but it is still unclear whether the neural code for concept representation uses information about sensory-motor features to discriminate between concepts. In the present study, we investigate this question by asking whether an encoding model based on five semantic attributes directly related to sensory-motor experience – sound, color, visual motion, shape, and manipulation – can successfully predict patterns of brain activation elicited by individual lexical concepts. We collected ratings on the relevance of these five attributes to the meaning of 820 words, and used these ratings as predictors in a multiple regression model of the fMRI signal associated with the words in a separate group of participants. The five resulting activation maps were then combined by linear summation to predict the distributed activation pattern elicited by a novel set of 80 test words. The encoding model predicted the activation patterns elicited by the test words significantly better than chance. As expected, prediction was successful for concrete but not for abstract concepts. Comparisons between encoding models based on different combinations of attributes indicate that all five attributes contribute to the representation of concrete concepts. Consistent with embodied theories of semantics, these results show, for the first time, that the distributed activation pattern associated with a concept combines information about different sensory-motor attributes according to their respective relevance. Future research should investigate how additional features of phenomenal experience contribute to the neural representation of conceptual knowledge.
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Keyword:
Article
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URL: https://doi.org/10.1016/j.neuropsychologia.2015.04.009 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4638171/ http://www.ncbi.nlm.nih.gov/pubmed/25863238
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Dialect Awareness and Lexical Comprehension of Mainstream American English in African American English-Speaking Children
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Distributional structure in language: Contributions to noun–verb difficulty differences in infant word recognition
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Anatomy is strategy: Skilled reading differences associated with structural connectivity differences in the reading network
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Toddlers Activate Lexical Semantic Knowledge in the Absence of Visual Referents: Evidence from Auditory Priming
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The Role of Left Occipitotemporal Cortex in Reading: Reconciling Stimulus, Task, and Lexicality Effects
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Noun–noun combination: Meaningfulness ratings and lexical statistics for 2,160 word pairs
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The relationship between phonological and auditory processing and brain organization in beginning readers
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Rules vs. Statistics: Insights from a Highly Inflected Language
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White Students Reflecting on Whiteness: Understanding Emotional Responses
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Connecting Cues: Overlapping Regularities Support Cue Discovery in Infancy
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Letting Structure Emerge: Connectionist and Dynamical Systems Approaches to Cognition
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