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https://doi.org/10.1...arrow_drop_down
https://doi.org/10.1075/lllt.4...
Part of book or chapter of book . 2017 . Peer-reviewed
Data sources: Crossref
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Neural complexity meets lexical complexity

An issue both in language and in neuroscience
Authors: John H. Schumann;

Neural complexity meets lexical complexity

Abstract

Abstract Complexity Theory provides avenues for understanding many aspects of language acquisition and use, including the language neuroscientists use to label the brain and to think about its structure and functions. A major concern for neuroscience has been the mapping of structure to function. The tendency has been to seek one-to-one mappings between the two, but advances in research have revealed that the brain is characterized by degeneracy in which two or more architecturally different structures can serve the same function. Thus, the brain can operate with many-to-one mappings. This complexity in neural structure is met with the complexity of synonymy in the lexicon of human language that is used to describe the brain. In this chapter I discuss the relationship between degeneracy and complexity and draw an analogy between neural degeneracy and lexical complexity, specifically as seen in synonymy.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
Average
Average
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