Prolegomena to a Neurocomputational Architecture for Human Grammatical Encoding and Decoding

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Last updated 25 outubro 2024
Prolegomena to a Neurocomputational Architecture for Human Grammatical  Encoding and Decoding
Prolegomena to a Neurocomputational Architecture for Human Grammatical  Encoding and Decoding
Shared Language: Overlap and Segregation of the Neuronal Infrastructure for Speaking and Listening Revealed by Functional MRI - Laura Menenti, Sarah M. E. Gierhan, Katrien Segaert, Peter Hagoort, 2011
Prolegomena to a Neurocomputational Architecture for Human Grammatical  Encoding and Decoding
The structure of our model of scene description. It echoes the
Prolegomena to a Neurocomputational Architecture for Human Grammatical  Encoding and Decoding
Training (A) and testing (B) datasets. Each block or slot
Prolegomena to a Neurocomputational Architecture for Human Grammatical  Encoding and Decoding
Duration of the MV analysis of garden-path sentence (5a) as a function
Prolegomena to a Neurocomputational Architecture for Human Grammatical  Encoding and Decoding
Minimalist lexicon of sentence (1)
Prolegomena to a Neurocomputational Architecture for Human Grammatical  Encoding and Decoding
Absolute and relative use frequency of Study 1 lexical categories
Prolegomena to a Neurocomputational Architecture for Human Grammatical  Encoding and Decoding
TCG as a two-route model of language comprehension. The utterance input
Prolegomena to a Neurocomputational Architecture for Human Grammatical  Encoding and Decoding
Application of the placement rules in Table 1 to sentence (2). The
Prolegomena to a Neurocomputational Architecture for Human Grammatical  Encoding and Decoding
Neuroinformatics Volume 12, issue 1
Prolegomena to a Neurocomputational Architecture for Human Grammatical  Encoding and Decoding
PDF] Incremental sentence generation: a computer model of grammatical encoding
Prolegomena to a Neurocomputational Architecture for Human Grammatical  Encoding and Decoding
PDF) Prolegomena to a Neurocomputational Architecture for Human Grammatical Encoding and Decoding
Prolegomena to a Neurocomputational Architecture for Human Grammatical  Encoding and Decoding
Kempen, Verb-second word order after German weil 'because': Psycholinguistic theory from corpus-linguistic data
Prolegomena to a Neurocomputational Architecture for Human Grammatical  Encoding and Decoding
PDF] Parsing Verb-Final Clauses in German: Garden-path and ERP Effects Modeled by a Parallel Dynamic Parser
Prolegomena to a Neurocomputational Architecture for Human Grammatical  Encoding and Decoding
PDF) From sentence structure to intonation contour
Prolegomena to a Neurocomputational Architecture for Human Grammatical  Encoding and Decoding
Regions More Activated for Producing Before than After Sentences

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