Abstract
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 Here we argue that the sciences of language are currently in an interim stage using an increasingly outdated scientific visualization borrowed from the box-and-arrow flow charts of the early days of engineering and computer science.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.
Highlights
Scientific Visualizations of Theoretical FrameworksData visualizations techniques have been developed to better understand complex empirical data
All scientists use data visualizations to discover patterns in their phenomena that may have otherwise gone unnoticed
We have argued that linguistic information involved in language processing and language learning appear to be highly integrated and interconnected, and its uptake is continuous at the time scales of language comprehension and of language acquisition
Summary
Data visualizations techniques have been developed to better understand complex empirical data. This model assumes a language faculty that is composed of autonomously organized levels of linguistic representation (i.e., phonetic, phonological, lexical, syntactic, semantic, and pragmatic) These levels are frequently assumed to be modular, organized in rank order of dominance, and to feed unidirectionally into one another in stage-based algorithmic procedures (Figure 1E). As we will detail, phonetic variation can influence a syntactic parse from the bottom up, and a pragmatic inference can alter the perception of an ambiguously heard word in a top-down fashion This new scientific visualization of language comprehension as a trajectory through a single multi-dimensional space, where all information sources and their constraints are conjoined, may help the field let go of its tendency to cling to the original inspiration of boxes-and-arrows and their adjunctive, incremental revisions.
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