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  A sparse neural code for some speech sounds but not for others

Scharinger, M., Bendixen, A., Trujillo-Barreto, N., & Obleser, J. (2012). A sparse neural code for some speech sounds but not for others. PLoS One, 7(7): e40953. doi:10.1371/journal.pone.0040953.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-000F-AA06-A Version Permalink: http://hdl.handle.net/21.11116/0000-0004-5C1B-8
Genre: Journal Article

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 Creators:
Scharinger, Mathias1, Author              
Bendixen, Alexandra2, Author
Trujillo-Barreto, Nelson3, Author
Obleser, Jonas1, Author              
Affiliations:
1Max Planck Research Group Auditory Cognition, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_751545              
2Institute of Psychology, University of Leipzig, Germany, ou_persistent22              
3Cuban Neurosciences Center, Havana, Cuba, ou_persistent22              

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 Abstract: The precise neural mechanisms underlying speech sound representations are still a matter of debate. Proponents of ‘sparse representations’ assume that on the level of speech sounds, only contrastive or otherwise not predictable information is stored in long-term memory. Here, in a passive oddball paradigm, we challenge the neural foundations of such a ‘sparse’ representation; we use words that differ only in their penultimate consonant (“coronal” [t] vs. “dorsal” [k] place of articulation) and for example distinguish between the German nouns Latz ([lats]; bib) and Lachs ([laks]; salmon). Changes from standard [t] to deviant [k] and vice versa elicited a discernible Mismatch Negativity (MMN) response. Crucially, however, the MMN for the deviant [lats] was stronger than the MMN for the deviant [laks]. Source localization showed this difference to be due to enhanced brain activity in right superior temporal cortex. These findings reflect a difference in phonological ‘sparsity’: Coronal [t] segments, but not dorsal [k] segments, are based on more sparse representations and elicit less specific neural predictions; sensory deviations from this prediction are more readily ‘tolerated’ and accordingly trigger weaker MMNs. The results foster the neurocomputational reality of ‘representationally sparse’ models of speech perception that are compatible with more general predictive mechanisms in auditory perception.

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Language(s): eng - English
 Dates: 2012-03-282012-06-152012-07-16
 Publication Status: Published online
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 Rev. Method: Peer
 Identifiers: DOI: 10.1371/journal.pone.0040953
PMID: 22815876
PMC: PMC3397972
Other: Epub 2012
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Title: PLoS One
Source Genre: Journal
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Pages: - Volume / Issue: 7 (7) Sequence Number: e40953 Start / End Page: - Identifier: ISSN: 1932-6203
CoNE: /journals/resource/1000000000277850