  This article presents a neural language architecture of sentence structure in
the brain, in which sentences are temporal connection paths that interconnect
neural structures underlying their words. Words remain 'in-situ', hence they
are always content-addressable. Arbitrary and novel sentences (with novel
words) can be created with 'neural blackboards' for words and sentences. Hence,
the unlimited productivity of natural language can be achieved with a 'fixed'
small world like network structure. The article focuses on the neural
blackboard for sentences. The architecture uses only one 'connection matrix'
for binding all structural relations between words in sentences. Its ability to
represent arbitrary (English) sentences is discussed in detail, based on a
comprehensive analysis of them. The architecture simulates intra-cranial brain
activity observed during sentence processing and fMRI observations related to
sentence complexity and ambiguity. The simulations indicate that the observed
effects relate to global control over the architecture, not to the sentence
structures involved, which predicts higher activity differences related to
complexity and ambiguity with higher comprehension capacity. Other aspects
discussed are the 'intrinsic' sentence structures provided by connection paths
and their relation to scope and inflection, the use of a dependency parser for
control of binding, long-distance dependencies and gaps, question answering,
ambiguity resolution based on backward processing without explicit
backtracking, garden paths, and performance difficulties related to embeddings.
