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Andrew J. Anderson
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Journal Articles
Publisher: Journals Gateway
Journal of Cognitive Neuroscience (2016) 28 (11): 1749–1759.
Published: 01 November 2016
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View articletitled, Semantic Structural Alignment of Neural Representational Spaces Enables Translation between English and Chinese Words
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for article titled, Semantic Structural Alignment of Neural Representational Spaces Enables Translation between English and Chinese Words
Two sets of items can share the same underlying conceptual structure, while appearing unrelated at a surface level. Humans excel at recognizing and using alignments between such underlying structures in many domains of cognition, most notably in analogical reasoning. Here we show that structural alignment reveals how different people's neural representations of word meaning are preserved across different languages, such that patterns of brain activation can be used to translate words from one language to another. Groups of Chinese and English speakers underwent fMRI scanning while reading words in their respective native languages. Simply by aligning structures representing the two groups' neural semantic spaces, we successfully infer all seven Chinese–English word translations. Beyond language translation, conceptual structural alignment underlies many aspects of high-level cognition, and this work opens the door to deriving many such alignments directly from neural representational content.
Journal Articles
Publisher: Journals Gateway
Journal of Cognitive Neuroscience (2014) 26 (3): 658–681.
Published: 01 March 2014
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View articletitled, Discriminating Taxonomic Categories and Domains in Mental Simulations of Concepts of Varying Concreteness
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for article titled, Discriminating Taxonomic Categories and Domains in Mental Simulations of Concepts of Varying Concreteness
Most studies of conceptual knowledge in the brain focus on a narrow range of concrete conceptual categories, rely on the researchers' intuitions about which object belongs to these categories, and assume a broadly taxonomic organization of knowledge. In this fMRI study, we focus on concepts with a variety of concreteness levels; we use a state of the art lexical resource (WordNet 3.1) as the source for a relatively large number of category distinctions and compare a taxonomic style of organization with a domain-based model (an example domain is Law). Participants mentally simulated situations associated with concepts when cued by text stimuli. Using multivariate pattern analysis, we find evidence that all Taxonomic categories and Domains can be distinguished from fMRI data and also observe a clear concreteness effect: Tools and Locations can be reliably predicted for unseen participants, but less concrete categories (e.g., Attributes , Communications , Events , Social Roles ) can only be reliably discriminated within participants. A second concreteness effect relates to the interaction of Domain and Taxonomic category membership: Domain (e.g., relation to Law vs. Music) can be better predicted for less concrete categories. We repeated the analysis within anatomical regions, observing discrimination between all/most categories in the left mid occipital and left mid temporal gyri, and more specialized discrimination for concrete categories Tool and Location in the left precentral and fusiform gyri, respectively. Highly concrete/abstract Taxonomic categories and Domain were segregated in frontal regions. We conclude that both Taxonomic and Domain class distinctions are relevant for interpreting neural structuring of concrete and abstract concepts.