Language-specific neural dynamics extend syntax into the time domain.
Studies of perception have long shown that the brain adds information to its sensory analysis of the physical environment. A touchstone example for humans is language use: to comprehend a physical signal like speech, the brain must add linguistic knowledge, including syntax. Yet, syntactic rules and...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS Biology |
| Online Access: | https://doi.org/10.1371/journal.pbio.3002968 |
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| author | Cas W Coopmans Helen de Hoop Filiz Tezcan Peter Hagoort Andrea E Martin |
| author_facet | Cas W Coopmans Helen de Hoop Filiz Tezcan Peter Hagoort Andrea E Martin |
| author_sort | Cas W Coopmans |
| collection | DOAJ |
| description | Studies of perception have long shown that the brain adds information to its sensory analysis of the physical environment. A touchstone example for humans is language use: to comprehend a physical signal like speech, the brain must add linguistic knowledge, including syntax. Yet, syntactic rules and representations are widely assumed to be atemporal (i.e., abstract and not bound by time), so they must be translated into time-varying signals for speech comprehension and production. Here, we test 3 different models of the temporal spell-out of syntactic structure against brain activity of people listening to Dutch stories: an integratory bottom-up parser, a predictive top-down parser, and a mildly predictive left-corner parser. These models build exactly the same structure but differ in when syntactic information is added by the brain-this difference is captured in the (temporal distribution of the) complexity metric "incremental node count." Using temporal response function models with both acoustic and information-theoretic control predictors, node counts were regressed against source-reconstructed delta-band activity acquired with magnetoencephalography. Neural dynamics in left frontal and temporal regions most strongly reflect node counts derived by the top-down method, which postulates syntax early in time, suggesting that predictive structure building is an important component of Dutch sentence comprehension. The absence of strong effects of the left-corner model further suggests that its mildly predictive strategy does not represent Dutch language comprehension well, in contrast to what has been found for English. Understanding when the brain projects its knowledge of syntax onto speech, and whether this is done in language-specific ways, will inform and constrain the development of mechanistic models of syntactic structure building in the brain. |
| format | Article |
| id | doaj-art-633605aa8d264a83910bca19aca96874 |
| institution | Kabale University |
| issn | 1544-9173 1545-7885 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Biology |
| spelling | doaj-art-633605aa8d264a83910bca19aca968742025-02-05T05:30:18ZengPublic Library of Science (PLoS)PLoS Biology1544-91731545-78852025-01-01231e300296810.1371/journal.pbio.3002968Language-specific neural dynamics extend syntax into the time domain.Cas W CoopmansHelen de HoopFiliz TezcanPeter HagoortAndrea E MartinStudies of perception have long shown that the brain adds information to its sensory analysis of the physical environment. A touchstone example for humans is language use: to comprehend a physical signal like speech, the brain must add linguistic knowledge, including syntax. Yet, syntactic rules and representations are widely assumed to be atemporal (i.e., abstract and not bound by time), so they must be translated into time-varying signals for speech comprehension and production. Here, we test 3 different models of the temporal spell-out of syntactic structure against brain activity of people listening to Dutch stories: an integratory bottom-up parser, a predictive top-down parser, and a mildly predictive left-corner parser. These models build exactly the same structure but differ in when syntactic information is added by the brain-this difference is captured in the (temporal distribution of the) complexity metric "incremental node count." Using temporal response function models with both acoustic and information-theoretic control predictors, node counts were regressed against source-reconstructed delta-band activity acquired with magnetoencephalography. Neural dynamics in left frontal and temporal regions most strongly reflect node counts derived by the top-down method, which postulates syntax early in time, suggesting that predictive structure building is an important component of Dutch sentence comprehension. The absence of strong effects of the left-corner model further suggests that its mildly predictive strategy does not represent Dutch language comprehension well, in contrast to what has been found for English. Understanding when the brain projects its knowledge of syntax onto speech, and whether this is done in language-specific ways, will inform and constrain the development of mechanistic models of syntactic structure building in the brain.https://doi.org/10.1371/journal.pbio.3002968 |
| spellingShingle | Cas W Coopmans Helen de Hoop Filiz Tezcan Peter Hagoort Andrea E Martin Language-specific neural dynamics extend syntax into the time domain. PLoS Biology |
| title | Language-specific neural dynamics extend syntax into the time domain. |
| title_full | Language-specific neural dynamics extend syntax into the time domain. |
| title_fullStr | Language-specific neural dynamics extend syntax into the time domain. |
| title_full_unstemmed | Language-specific neural dynamics extend syntax into the time domain. |
| title_short | Language-specific neural dynamics extend syntax into the time domain. |
| title_sort | language specific neural dynamics extend syntax into the time domain |
| url | https://doi.org/10.1371/journal.pbio.3002968 |
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