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Reconciling time, space and function: A new dorsal–ventral stream model of sentence comprehension
Open accessAbstract
We present a new dorsal-ventral stream framework for language comprehension which unifies basic neurobiological assumptions (Rauschecker & Scott, 2009) with a cross-linguistic neurocognitive sentence comprehension model (eADM; Bornkessel & Schlesewsky, 2006). The dissociation between (time-dependent) syntactic structure-building and (time-independent) sentence interpretation assumed within the eADM provides a basis for the division of labour between the dorsal and ventral streams in comprehension. We posit that the ventral stream performs time-independent unifications of conceptual schemata, serving to create auditory objects of increasing complexity. The dorsal stream engages in the time-dependent combination of elements, subserving both syntactic structuring and a linkage to action. Furthermore, frontal regions accomplish general aspects of cognitive control in the service of action planning and execution rather than linguistic processing. This architecture is supported by a range of existing empirical findings and helps to resolve a number of theoretical and empirical puzzles within the existing dorsal-ventral streams literature.
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Chomsky, N. (2014) · The MIT Press eBooks · doi:10.7551/mitpress/9780262527347.001.0001 · Cited by 8,244
Distributed hierarchical processing in the primate cerebral cortex
Felleman, D. J., & Van Essen, D. C. (1991) · Cerebral Cortex · doi:10.1093/cercor/1.1.1 · Cited by 7,783
The cortical organization of speech processing
Hickok, G., & Poeppel, D. (2007) · Nature Reviews Neuroscience · doi:10.1038/nrn2113 · Cited by 5,495
Constructing a language: a usage-based theory of language acquisition
(2003) · Choice Reviews Online · doi:10.5860/choice.41-1385 · Cited by 4,458
Minimalist inquiries : the framework
Chomsky, N. (1998) · Medical Entomology and Zoology · Cited by 4,214
Head-driven phrase structure grammar
Sag, I. A., & Pollard, C. (1994) · Medical Entomology and Zoology · Cited by 3,889
Foundations of Language: Brain, Meaning, Grammar, Evolution
Jackendoff, R. (2002) · doi:10.1093/acprof:oso/9780198270126.001.0001 · Cited by 3,244
Mesulam, M. (1998) · Brain · doi:10.1093/brain/121.6.1013 · Cited by 3,072
Step by step : essays on minimalist syntax in honor of Howard Lasnik
Lasnik, H., Martin, R., Michaels, D., & Uriagereka, J. (2000) · Cited by 2,340
The lexical nature of syntactic ambiguity resolution
MacDonald, M. C., Pearlmutter, N. J., & Seidenberg, M. S. (1994) · Psychological Review · doi:10.1037/0033-295x.101.4.676 · Cited by 2,259
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The neural and computational bases of semantic cognition
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The ontogeny of the cortical language network
Skeide, M. A., & Friederici, A. D. (2016) · Nature Reviews Neuroscience · doi:10.1038/nrn.2016.23 · Cited by 391
The Cortical Organization of Syntax
Matchin, W., & Hickok, G. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhz180 · Cited by 370
The Declarative/Procedural Model
Ullman, M. T. (2016) · Neurobiology of Language · doi:10.1016/b978-0-12-407794-2.00076-6 · Cited by 294
A unifying account of angular gyrus contributions to episodic and semantic cognition
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Metadata
- Authors
- Bornkessel-Schlesewsky, I., & Schlesewsky, M.
- Venue
- Brain and Language
- Publisher
- Elsevier BV
- Published
- 2013-04
- Volume
- 125
- Issue
- 1
- Pages
- 60-76
- ISSN
- 0093-934X (ISSN-L)
- OpenAlex
- W2001427019
- Cited by
- 329
- References
- 112
- FWCI
- 25.58
- Type
- journal article
- Language
- en
- Open access
- hybrid
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.