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Abstract:
Abstract mental representation is fundamental for human cognition. Forming such representations in time, especially from dynamic and noisy perceptual input, is a challenge for
any processing modality, but
perhaps none so acutely as for
language processing. We show that
LISA (Hummel & Holyaok, 1997) and
DORA (Doumas, Hummel, & Sandhofer,
2008), models built to process and to
learn structured (i.e., symbolic) rep
resentations of conceptual properties and relations from unstructured inputs, show oscillatory activation during processing that is
highly similar to the cortical activity
elicited by the linguistic stimuli from Ding et al.(2016). We argue, as Ding et
al.(2016), that this activation reflects
formation of hierarchical linguistic representation, and furthermore, that the kind of computational mechanisms
in LISA/DORA (e.g., temporal binding by systematic asynchrony of firing)
may underlie formation of abstract
linguistic representations in the human brain. It may be this repurposing that allowed for the generation or mergence of hierarchical linguistic structure, and therefore, human language, from extant cognitive and neural systems. We
conclude that models of thinking and reasoning and models of language
processing must be integrated
—not only for increased plausiblity, but in order to advance both fields towards a larger integrative model of human cognition
