Casabitefight pt 21

Prolegomena to a Neurocomputational Architecture for Human Grammatical Encoding and Decoding

Por um escritor misterioso
Last updated 26 dezembro 2024
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
Graded sensitivity to structure and meaning throughout the human language network
Prolegomena to a Neurocomputational Architecture for Human Grammatical Encoding and Decoding
Frontiers Syntactic flexibility and planning scope: the effect of verb bias on advance planning during sentence recall
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
Frontiers Syntactic flexibility and planning scope: the effect of verb bias on advance planning during sentence recall
Prolegomena to a Neurocomputational Architecture for Human Grammatical Encoding and Decoding
Some example grammar entries. They can be combined to derive the
Prolegomena to a Neurocomputational Architecture for Human Grammatical Encoding and Decoding
Regions more activated for producing before than after
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
The Brain Basis of Language Processing: From Structure to Function
Prolegomena to a Neurocomputational Architecture for Human Grammatical Encoding and Decoding
A) Lateral/Medial pathways as implemented in the model (B) PRc and PHc
Prolegomena to a Neurocomputational Architecture for Human Grammatical Encoding and Decoding
The effect of changing (A) the amount of inhibition in DG proximal, and
Prolegomena to a Neurocomputational Architecture for Human Grammatical Encoding and Decoding
Regions More Activated for Producing Before than After Sentences
Recomendado para você
você pode gostar

© 2014-2024 atsrb.gos.pk. All rights reserved.