4.1 Article

Toward a New Scientific Visualization for the Language Sciences

Journal

INFORMATION
Volume 3, Issue 1, Pages 124-150

Publisher

MDPI
DOI: 10.3390/info3010124

Keywords

dynamical systems; language; language acquisition; psycholinguistics; sentence processing; scientific visualization

Funding

  1. NIH [R03-HD051671]
  2. NSF [BCS-0721297]

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All scientists use data visualizations to discover patterns in their phenomena that may have otherwise gone unnoticed. Likewise, we also use scientific visualizations to help us describe our verbal theories and predict those data patterns. But scientific visualization may also constitute a hindrance to theory development when new data cannot be accommodated by the current dominant framework. Here we argue that the sciences of language are currently in an interim stage using an increasingly outdated scientific visualization borrowed from the box-and-arrow flow charts of the early days of engineering and computer science. The original (and not yet fully discarded) version of this obsolete model assumes that the language faculty is composed of autonomously organized levels of linguistic representation, which in turn are assumed to be modular, organized in rank order of dominance, and feed unidirectionally into one another in stage-like algorithmic procedures. We review relevant literature in psycholinguistics and language acquisition that cannot be accommodated by the received model. Both learning and processing of language in children and adults, at various putative 'levels' of representation, appear to be highly integrated and interdependent, and function simultaneously rather than sequentially. The fact that half of the field sees these findings as trivially true and the other half argues fiercely against them suggests to us that the sciences of language are on the brink of a paradigm shift. We submit a new scientific visualization for language, in which stacked levels of linguistic representation are replaced by trajectories in a multidimensional space. This is not a mere redescription. Processing language in the brain equates to traversing such a space in regions afforded by multiple probabilistic cues that simultaneously activate different linguistic representations. Much still needs to be done to convert this scientific visualization into actual implemented models, but at present it allows language scientists to envision new concepts and venues for research that may assist the field in transitioning to a new conceptualization, and provide a clear direction for the next decade.

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