Through computational modeling, here we examine whether visual and task characteristics of writing systems alone can account for lateralization differences in visual word recognition between different languages without assuming influence from left hemisphere (LH) lateralized language processes. We apply a hemispheric processing model of face recognition to visual word recognition; the model implements a theory of hemispheric asymmetry in perception that posits low spatial frequency biases in the right hemisphere and high spatial frequency (HSF) biases in the LH. We show (...) two factors that can influence lateralization: (a) Visual similarity among words: The more similar the words in the lexicon look visually, the more HSF/LH processing is required to distinguish them, and (b) Requirement to decompose words into graphemes for grapheme-phoneme mapping: Alphabetic reading (involving grapheme-phoneme conversion) requires more HSF/LH processing than logographic reading (no grapheme-phoneme mapping). These factors may explain the difference in lateralization between English and Chinese orthographic processing. (shrink)

In Chinese orthography, the most common character structure consists of a semantic radical on the left and a phonetic radical on the right ; the minority, opposite arrangement also exists. Recent studies showed that SP character processing is more left hemisphere lateralized than PS character processing. Nevertheless, it remains unclear whether this is due to phonetic radical position or character type frequency. Through computational modeling with artificial lexicons, in which we implement a theory of hemispheric asymmetry in perception but do (...) not assume phonological processing being LH lateralized, we show that the difference in character type frequency alone is sufficient to exhibit the effect that the dominant type has a stronger LH lateralization than the minority type. This effect is due to higher visual similarity among characters in the dominant type than the minority type, demonstrating the modulation of visual similarity of words on hemispheric lateralization. (shrink)

Expertise in Chinese character recognition is marked by reduced holistic processing, which depends mainly on writing rather than reading experience. Here we show that, while simplified and traditional Chinese readers demonstrated a similar level of HP when processing characters shared between the simplified and traditional scripts, simplified Chinese readers were less holistic than traditional Chinese readers in perceiving simplified characters; this effect depended mainly on their writing rather than reading performance. However, the two groups did not differ in HP of (...) traditional characters, regardless of their difference in reading and writing performances. Our image analysis showed high visual similarity between the two character types, with a larger variance among simplified characters; this may allow simplified Chinese readers to interpolate and generalize their skills to traditional characters. Thus, transfer of perceptual expertise may be constrained by both the similarity in feature and the difference in exemplar variance between the categories. (shrink)

Theoretical models propose that attentional biases might account for the maintenance of social anxiety symptoms. However, previous eye-tracking studies have yielded mixed results. One explanation i...

This article delineates two dimensions along which computational models of face processing may vary, and briefly review three such models, the Dailey and Cottrell model; the O'Reilly and Munakata model; and the Riesenhuber and Poggio. It focuses primarily on one of the models and shows how this model is used to reveal potential mechanisms underlying the neural processing of faces and objects—the development of a specialized face processor, how it could be recruited for other domains, hemispheric lateralization of face processing, (...) facial expression processing, and the development of face discrimination. It turns to the Riesenhuber and Poggio model to describe the elegant way it has been used to predict functional magnetic resonance imaging data on face processing. The overall strategy of these modeling efforts is to sample problems that are constrained by neurophysiological and behavioral data, and to stress the ways in which models can generate novel hypotheses about the way humans process faces. (shrink)