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ROSE: A neurocomputational architecture for syntax
https://www.sciencedirect.com/science... Elliot Murphy Highlights • Reviews
current neurobiological models of syntactic processing. • Proposes a novel
neurocomputational architecture for syntax (ROSE). • Provides causal
explanations for how distinct levels of ROSE mechanistically relate. •
Explores falsifiability of model and new directions for ROSE. A comprehensive
neural model of language must accommodate four components: representations,
operations, structures and encoding. Recent intracranial research has begun to
map out the feature space associated with syntactic processes, but the field
lacks a unified framework that can direct invasive neural analyses. This
article proposes a neurocomputational architecture for syntax, termed ROSE
(Representation, Operation, Structure, Encoding). Under ROSE, the basic data
structures of syntax are atomic features, types of mental representations (R),
and are coded at the single-unit and ensemble level. Operations (O)
transforming these units into manipulable objects accessible to subsequent
structure-building levels are coded via high frequency broadband γ activity.
Low frequency synchronization and cross-frequency coupling code for recursive
structural inferences (S). Distinct forms of low frequency coupling encode
these structures onto distinct workspaces (E). Causally connecting R to O is
spike-phase/LFP coupling; connecting O to S is phase-amplitude coupling;
connecting S to E are frontotemporal traveling oscillations. ROSE is reliant
on neurophysiologically plausible mechanisms and provides an anatomically
precise and falsifiable grounding for natural language syntax. Active
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