Cognitive Science From the Perspective of Linguistic Diversity

This letter addresses two issues in language research that are important to cognitive science: the comparability of word meanings across languages and the neglect of an integrated approach to writing systems. The first issue challenges generativist claims by emphasizing the importance of comparability of data, drawing on typologists' findings about different languages. The second issue addresses the exclusion of diverse writing systems from linguistic investigation and argues for a more extensive study of their effects on language and cognition. We argue for a refocusing of cognitive science research on linguistic diversity in all modalities to develop the most robust understanding of language and its role in human cognition more broadly.

Zipf's Law of Abbreviation holds for individual characters across a broad range of writing systems

Zipf's Law of Abbreviation - the idea that more frequent symbols in a code are simpler than less frequent ones - has been shown to hold at the level of words in many languages. We tested whether it holds at the level of individual written characters. Character complexity is similar to word length in that it requires more cognitive and motor effort for producing and processing more complex symbols. We built a dataset of character complexity and frequency measures covering 27 different writing systems. According to our data, Zipf's Law of Abbreviation holds for every writing system in our dataset - the more frequent characters have lower degrees of complexity and vice-versa. This result provides further evidence of optimization mechanisms shaping communication systems.

Graphic complexity in writing systems

A writing system is a graphic code, i.e., a system of standardized pairings between symbols and meanings in which symbols take the form of images that can endure. The visual character of writing implies that written characters have to fit constraints of the human visual system. One aspect of this optimization lays in the graphic complexity of the characters used by scripts. Scripts are sets of graphic characters used for the written form of one language or more. Using computational methods over a large and diverse dataset (over 47,000 characters, from over 133 scripts), we answer three central questions about the visual complexity of written characters and the evolution of writing: (1) What determines character complexity? (2) Can we find traces of evolutionary change in character complexity? (3) Is complexity distributed in a way that makes character recognition easier? Our study suggests that (1) character complexity depends primarily on which linguistic unit the characters encode, and that (2) there is little evidence of evolutionary change in character complexity. Additionally (3) for an individual character, the half which is encountered first while reading tends to be more complex than that which is encountered last.

The Mirror Generalization Process in Reading: Evidence from Korean Hangul

Mirror invariance or generalisation is the ability to recognise objects as being the same regardless of their spatial orientation. However, when, for example, learning to read Roman script, children need to hone these skills so that they can readily discriminate between mirror letters such as b/d or p/b. Korean Hangul makes a particularly interesting comparison as it has both lateral and vertical perceptually similar mirror letter pairs (i.e., ㅏㅓ, ㅑㅕ, ㅗㅜ, ㅛㅠ). In the current study, we investigated the mirror generalisation effect in native readers of Korean Hangul. We used a similar negative priming paradigm as used by (Ahr et al., Brain and Cognition 117:1-8, 2017) with Roman script readers. In contrast to their findings, we did not find evidence of negative priming due to either lateral (e.g., ㅏ + ㅓ) or vertical (e.g., ㅗ + ㅜ) mirror letter primes in Korean readers. One explanation for these results is that adult readers of Korean Hangul may not experience mirror invariance to the same extent as Roman script readers due to script-specific characteristics. Thus, learning to read this distinctive script may result in readers being less sensitive to mirror reversals than Roman script readers.

GraphCom: A multidimensional measure of graphic complexity applied to 131 written languages

We report a new multidimensional measure of visual complexity (GraphCom) that captures variability in the complexity of graphs within and across writing systems. We applied the measure to 131 written languages, allowing comparisons of complexity and providing a basis for empirical testing of GraphCom. The measure includes four dimensions whose value in capturing the different visual properties of graphs had been demonstrated in prior reading research-(1) perimetric complexity, sensitive to the ratio of a written form to its surrounding white space (Pelli, Burns, Farell, & Moore-Page, 2006); (2) number of disconnected components, sensitive to discontinuity (Gibson, 1969); (3) number of connected points, sensitive to continuity (Lanthier, Risko, Stolz, & Besner, 2009); and (4) number of simple features, sensitive to the strokes that compose graphs (Wu, Zhou, & Shu, 1999). In our analysis of the complexity of 21,550 graphs, we (a) determined the complexity variation across writing systems along each dimension, (b) examined the relationships among complexity patterns within and across writing systems, and (c) compared the dimensions in their abilities to differentiate the graphs from different writing systems, in order to predict human perceptual judgments (n = 180) of graphs with varying complexity. The results from the computational and experimental comparisons showed that GraphCom provides a measure of graphic complexity that exceeds previous measures in its empirical validation. The measure can be universally applied across writing systems, providing a research tool for studies of reading and writing.