Publications

Abstract

What does semantic similarity between two concepts mean? How could we measure it? The way in which semantic similarity is calculated might differ depending on the theoretical notion of semantic representation. In an eye-tracking reading experiment, we investigated whether two widely used semantic similarity measures (based on featural or distributional representations) have distinctive effects on sentence reading times. In other words, we explored whether these measures of semantic similarity differ qualitatively. In addition, we examined whether visually perceived spatial distance interacts with either or both of these measures. Our results showed that the effect of featural and distributional representations on reading times can differ both in direction and in its time course. Moreover, both featural and distributional information interacted with spatial distance, yet in different sentence regions and reading measures. We conclude that featural and distributional representations are distinct components of semantic representation.

Abstract

At present, more than one-fifth of humanity is unable to read and write. We critically examine experimental evidence and theories of how (il)literacy affects the human mind. In our discussion we show that literacy has significant cognitive consequences that go beyond the processing of written words and sentences. Thus, cultural inventions such as reading shape general cognitive processing in non-trivial ways. We suggest that this has important implications for educational policy and guidance as well as research into cognitive processing and brain functioning.

Abstract

Despite the efficiency with which language users typically process spoken language, a growing body of research finds substantial individual differences in both the speed and accuracy of spoken language processing potentially attributable to participants’ literacy skills. Against this background, the current study takes a look at the role of word reading skill in listener’s anticipation of upcoming spoken language input in children at the cusp of learning to read: if reading skills impact predictive language processing, then children at this stage of literacy acquisition should be most susceptible to the effects of reading skills on spoken language processing. We tested 8-year-old children on their prediction of upcoming spoken language input in an eye-tracking task. While children, like in previous studies to-date, were successfully able to anticipate upcoming spoken language input, there was a strong positive correlation between children’s word reading (but not their pseudo-word reading and meta-phonological awareness or their spoken word recognition) skills and their prediction skills. We suggest that these findings are most compatible with the notion that the process of learning orthographic representations during reading acquisition sharpens pre-existing lexical representations which in turn also supports anticipation of upcoming spoken words.

Abstract

Three cross-modal priming experiments examined the influence of pre-exposure to
pictures and printed words on the speed of spoken word recognition. Targets for
auditory lexical decision were spoken Dutch words and nonwords, presented in
isolation (Experiments 1 and 2) or after a short phrase (Experiment 3). Auditory
stimuli were preceded by primes which were pictures (Experiments 1 and 3) or those pictures’ printed names (Experiment 2). Prime-target pairs were phonologically onsetrelated (e.g., pijl-pijn, arrow-pain), were from the same semantic category (e.g., pijlzwaard, arrow-sword), or were unrelated on both dimensions. Phonological
interference and semantic facilitation were observed in all experiments. Priming
magnitude was similar for pictures and printed words, and did not vary with picture
viewing time or number of pictures in the display (either one or four). These effects
arose even though participants were not explicitly instructed to name the pictures and where strategic naming would interfere with lexical decision-making. This suggests
that, by default, processing of related pictures and printed words influences how
quickly we recognize related spoken words.

Abstract

Currently one in five adults is still unable to read despite a rapidly developing world. Here we show that (il)literacy has important consequences for the cognitive ability of selecting relevant information from a visual display of non-linguistic material. In two experiments we compared low to high literacy observers on both an easy and a more difficult visual search task involving different types of chicken. Low literates were consistently slower (as indicated by overall RTs) in both experiments. More detailed analyses, including eye movement measures, suggest that the slowing is partly due to display wide (i.e. parallel) sensory processing but mainly due to post-selection processes, as low literates needed more time between fixating the target and generating a manual response. Furthermore, high and low literacy groups differed in the way search performance was distributed across the visual field. High literates performed relatively better when the target was presented in central regions, especially on the right. At the same time, high literacy was also associated with a more general bias towards the top and the left, especially in the more difficult search. We conclude that learning to read results in an extension of the functional visual field from the fovea to parafoveal areas, combined with some asymmetry in scan pattern influenced by the reading direction, both of which also influence other (e.g. non-linguistic) tasks such as visual search.

Abstract

The effect of literacy on phonological processing has been described in terms of a virus that “infects all speech processing” (Frith, 1998). Empirical data has established that literacy leads to changes to the way in which phonological information is processed. Harm & Seidenberg (1999) demonstrated that a connectionist network trained to map between English orthographic and phonological representations display’s more componential phonological processing than a network trained only to stably represent the phonological forms of words. Within this study we use a similar model yet manipulate the transparency of orthographic-to-phonological mappings. We observe that networks trained on a transparent orthography are better at restoring phonetic features and phonemes. However, networks trained on non-transparent orthographies are more likely to restore corrupted phonological segments with legal, coarser linguistic units (e.g. onset, coda). Our study therefore provides an explicit description of how differences in orthographic transparency can lead to varying strains and symptoms of the ‘literacy virus’.

Abstract

When processing language, the cognitive system has access to information from a range of modalities (e.g. auditory, visual) to support language processing. Language mediated visual attention studies have shown sensitivity of the listener to phonological, visual, and semantic similarity when processing a word. In a computational model of language mediated visual attention, that models spoken word processing as the parallel integration of information from phonological, semantic and visual processing streams, we simulate such effects of competition within modalities. Our simulations raised untested predictions about stronger and earlier effects of visual and semantic similarity compared to phonological similarity around the rhyme of the word. Two visual world studies confirmed these predictions. The model and behavioral studies suggest that, during spoken word comprehension, multimodal information can be recruited rapidly to constrain lexical selection to the extent that phonological rhyme information may exert little influence on this process.

Abstract

Multimodal integration is a central characteristic of human cognition. However our understanding of the interaction between modalities and its influence on behaviour is still in its infancy. This paper examines the value of the Hub & Spoke framework (Plaut, 2002; Rogers et al., 2004; Dilkina et al., 2008; 2010) as a tool for exploring multimodal interaction in cognition. We present a Hub and Spoke model of language–vision information interaction and report the model’s ability to replicate a range of phonological, visual and semantic similarity word-level effects reported in the Visual World Paradigm (Cooper, 1974; Tanenhaus et al, 1995). The model provides an explicit connection between the percepts of language and the distribution of eye gaze and demonstrates the scope of the Hub-and-Spoke architectural framework by modelling new aspects of multimodal cognition.

Abstract

Learning to read and write requires an individual to connect additional orthographic representations to pre-existing mappings between phonological and semantic representations of words. Past empirical results suggest that the process of learning to read and write (at least in alphabetic languages) elicits changes in the language processing system, by either increasing the cognitive efficiency of mapping between representations associated with a word, or by changing the granularity of phonological processing of spoken language, or through a combination of both. Behavioural effects of literacy have typically been assessed in offline explicit tasks that have addressed only phonological processing. However, a recent eye tracking study compared high and low literate participants on effects of phonology and semantics in processing measured implicitly using eye movements. High literates’ eye movements were more affected by phonological overlap in online speech than low literates, with only subtle differences observed in semantics. We determined whether these effects were due to cognitive efficiency and/or granularity of speech processing in a multimodal model of speech processing – the amodal shared resource model (ASR, Smith, Monaghan, & Huettig, 2013). We found that cognitive efficiency in the model had only a marginal effect on semantic processing and did not affect performance for phonological processing, whereas fine-grained versus coarse-grained phonological representations in the model simulated the high/low literacy effects on phonological processing, suggesting that literacy has a focused effect in changing the grain-size of phonological mappings.