Falk Huettig

Publications

Displaying 1 - 22 of 22
  • Araujo, S., Narang, V., Misra, D., Lohagun, N., Khan, O., Singh, A., Mishra, R. K., Hervais-Adelman, A., & Huettig, F. (2023). A literacy-related color-specific deficit in rapid automatized naming: Evidence from neurotypical completely illiterate and literate adults. Journal of Experimental Psychology: General, 152(8), 2403-2409. doi:10.1037/xge0001376.

    Abstract

    There is a robust positive relationship between reading skills and the time to name aloud an array of letters, digits, objects, or colors as quickly as possible. A convincing and complete explanation for the direction and locus of this association remains, however, elusive. In this study we investigated rapid automatized naming (RAN) of every-day objects and basic color patches in neurotypical illiterate and literate adults. Literacy acquisition and education enhanced RAN performance for both conceptual categories but this advantage was much larger for (abstract) colors than every-day objects. This result suggests that (i) literacy/education may be causal for serial rapid naming ability of non-alphanumeric items, (ii) differences in the lexical quality of conceptual representations can underlie the reading-related differential RAN performance.

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  • Ferreira, F., & Huettig, F. (2023). Fast and slow language processing: A window into dual-process models of cognition. [Open Peer commentary on De Neys]. Behavioral and Brain Sciences, 46: e121. doi:10.1017/S0140525X22003041.

    Abstract

    Our understanding of dual-process models of cognition may benefit from a consideration of language processing, as language comprehension involves fast and slow processes analogous to those used for reasoning. More specifically, De Neys's criticisms of the exclusivity assumption and the fast-to-slow switch mechanism are consistent with findings from the literature on the construction and revision of linguistic interpretations.
  • Garrido Rodriguez, G., Norcliffe, E., Brown, P., Huettig, F., & Levinson, S. C. (2023). Anticipatory processing in a verb-initial Mayan language: Eye-tracking evidence during sentence comprehension in Tseltal. Cognitive Science, 47(1): e13292. doi:10.1111/cogs.13219.

    Abstract

    We present a visual world eye-tracking study on Tseltal (a Mayan language) and investigate whether verbal information can be used to anticipate an upcoming referent. Basic word order in transitive sentences in Tseltal is Verb-Object-Subject (VOS). The verb is usually encountered first, making argument structure and syntactic information available at the outset, which should facilitate anticipation of the post-verbal arguments. Tseltal speakers listened to verb-initial sentences with either an object-predictive verb (e.g., ‘eat’) or a general verb (e.g., ‘look for’) (e.g., “Ya slo’/sle ta stukel on te kereme”, Is eating/is looking (for) by himself the avocado the boy/ “The boy is eating/is looking (for) an avocado by himself”) while seeing a visual display showing one potential referent (e.g., avocado) and three distractors (e.g., bag, toy car, coffee grinder). We manipulated verb type (predictive vs. general) and recorded participants' eye-movements while they listened and inspected the visual scene. Participants’ fixations to the target referent were analysed using multilevel logistic regression models. Shortly after hearing the predictive verb, participants fixated the target object before it was mentioned. In contrast, when the verb was general, fixations to the target only started to increase once the object was heard. Our results suggest that Tseltal hearers pre-activate semantic features of the grammatical object prior to its linguistic expression. This provides evidence from a verb-initial language for online incremental semantic interpretation and anticipatory processing during language comprehension. These processes are comparable to the ones identified in subject-initial languages, which is consistent with the notion that different languages follow similar universal processing principles.
  • Huettig, F., Voeten, C. C., Pascual, E., Liang, J., & Hintz, F. (2023). Do autistic children differ in language-mediated prediction? Cognition, 239: 105571. doi:10.1016/j.cognition.2023.105571.

    Abstract

    Prediction appears to be an important characteristic of the human mind. It has also been suggested that prediction is a core difference of autistic children. Past research exploring language-mediated anticipatory eye movements in autistic children, however, has been somewhat contradictory, with some studies finding normal anticipatory processing in autistic children with low levels of autistic traits but others observing weaker prediction effects in autistic children with less receptive language skills. Here we investigated language-mediated anticipatory eye movements in young children who differed in the severity of their level of autistic traits and were in professional institutional care in Hangzhou, China. We chose the same spoken sentences (translated into Mandarin Chinese) and visual stimuli as a previous study which observed robust prediction effects in young children (Mani & Huettig, 2012) and included a control group of typically-developing children. Typically developing but not autistic children showed robust prediction effects. Most interestingly, autistic children with lower communication, motor, and (adaptive) behavior scores exhibited both less predictive and non-predictive visual attention behavior. Our results raise the possibility that differences in language-mediated anticipatory eye movements in autistic children with higher levels of autistic traits may be differences in visual attention in disguise, a hypothesis that needs further investigation.
  • Huettig, F., & Ferreira, F. (2023). The myth of normal reading. Perspectives on Psychological Science, 18(4), 863-870. doi:10.1177/17456916221127226.

    Abstract

    We argue that the educational and psychological sciences must embrace the diversity of reading rather than chase the phantom of normal reading behavior. We critically discuss the research practice of asking participants in experiments to read “normally”. We then draw attention to the large cross-cultural and linguistic diversity around the world and consider the enormous diversity of reading situations and goals. Finally, we observe that people bring a huge diversity of brains and experiences to the reading task. This leads to certain implications. First, there are important lessons for how to conduct psycholinguistic experiments. Second, we need to move beyond Anglo-centric reading research and produce models of reading that reflect the large cross-cultural diversity of languages and types of writing systems. Third, we must acknowledge that there are multiple ways of reading and reasons for reading, and none of them is normal or better or a “gold standard”. Finally, we must stop stigmatizing individuals who read differently and for different reasons, and there should be increased focus on teaching the ability to extract information relevant to the person’s goals. What is important is not how well people decode written language and how fast people read but what people comprehend given their own stated goals.
  • Hintz, F., & Huettig, F. (2015). The complexity of the visual environment modulates language-mediated eye gaze. In R. Mishra, N. Srinivasan, & F. Huettig (Eds.), Attention and Vision in Language Processing (pp. 39-55). Berlin: Springer. doi:10.1007/978-81-322-2443-3_3.

    Abstract

    Three eye-tracking experiments investigated the impact of the complexity of the visual environment on the likelihood of word-object mapping taking place at phonological, semantic and visual levels of representation during language-mediated visual search. Dutch participants heard spoken target words while looking at four objects embedded in displays of different complexity and indicated the presence or absence of the target object. During filler trials the target objects were present, but during experimental trials they were absent and the display contained various competitor objects. For example, given the target word “beaker”, the display contained a phonological (a beaver, bever), a shape (a bobbin, klos), a semantic (a fork, vork) competitor, and an unrelated distractor (an umbrella, paraplu). When objects were presented in simple four-object displays (Experiment 2), there were clear attentional biases to all three types of competitors replicating earlier research (Huettig and McQueen, 2007). When the objects were embedded in complex scenes including four human-like characters or four meaningless visual shapes (Experiments 1, 3), there were biases in looks to visual and semantic but not to phonological competitors. In both experiments, however, we observed evidence for inhibition in looks to phonological competitors, which suggests that the phonological forms of the objects nevertheless had been retrieved. These findings suggest that phonological word-object mapping is contingent upon the nature of the visual environment and add to a growing body of evidence that the nature of our visual surroundings induces particular modes of processing during language-mediated visual search.
  • Huettig, F., & Brouwer, S. (2015). Delayed anticipatory spoken language processing in adults with dyslexia - Evidence from eye-tracking. Dyslexia, 21(2), 97-122. doi:10.1002/dys.1497.

    Abstract

    It is now well-established that anticipation of up-coming input is a key characteristic of spoken language comprehension. It has also frequently been observed that literacy influences spoken language processing. Here we investigated whether anticipatory spoken language processing is related to individuals’ word reading abilities. Dutch adults with dyslexia and a control group participated in two eye-tracking experiments. Experiment 1 was conducted to assess whether adults with dyslexia show the typical language-mediated eye gaze patterns. Eye movements of both adults with and without dyslexia closely replicated earlier research: spoken language is used to direct attention to relevant objects in the environment in a closely time-locked manner. In Experiment 2, participants received instructions (e.g., "Kijk naar deCOM afgebeelde pianoCOM", look at the displayed piano) while viewing four objects. Articles (Dutch “het” or “de”) were gender-marked such that the article agreed in gender only with the target and thus participants could use gender information from the article to predict the target object. The adults with dyslexia anticipated the target objects but much later than the controls. Moreover, participants' word reading scores correlated positively with their anticipatory eye movements. We conclude by discussing the mechanisms by which reading abilities may influence predictive language processing.
  • Huettig, F. (2015). Four central questions about prediction in language processing. Brain Research, 1626, 118-135. doi:10.1016/j.brainres.2015.02.014.

    Abstract

    The notion that prediction is a fundamental principle of human information processing has been en vogue over recent years. The investigation of language processing may be particularly illuminating for testing this claim. Linguists traditionally have argued prediction plays only a minor role during language understanding because of the vast possibilities available to the language user as each word is encountered. In the present review I consider four central questions of anticipatory language processing: Why (i.e. what is the function of prediction in language processing)? What (i.e. what are the cues used to predict up-coming linguistic information and what type of representations are predicted)? How (what mechanisms are involved in predictive language processing and what is the role of possible mediating factors such as working memory)? When (i.e. do individuals always predict up-coming input during language processing)? I propose that prediction occurs via a set of diverse PACS (production-, association-, combinatorial-, and simulation-based prediction) mechanisms which are minimally required for a comprehensive account of predictive language processing. Models of anticipatory language processing must be revised to take multiple mechanisms, mediating factors, and situational context into account. Finally, I conjecture that the evidence considered here is consistent with the notion that prediction is an important aspect but not a fundamental principle of language processing.
  • Huettig, F., Srinivasan, N., & Mishra, R. (2015). Introduction to 'Attention and vision in language processing'. In R. Mishra, N. Srinivasan, & F. Huettig (Eds.), Attention and vision in language processing. (pp. V-IX). Berlin: Springer.
  • Huettig, F. (2015). Literacy influences cognitive abilities far beyond the mastery of written language. In I. van de Craats, J. Kurvers, & R. van Hout (Eds.), Adult literacy, second language, and cognition. LESLLA Proceedings 2014. Nijmegen: Centre for Language Studies.

    Abstract

    Recent experimental evidence from cognitive psychology and cognitive neuroscience shows that reading acquisition has non-trivial consequences for cognitive processes other than reading per se. In the present chapter I present evidence from three areas of cognition: phonological processing, prediction in language processing, and visual search. These findings suggest that literacy on cognition influences are far-reaching. This implies that a good understanding of the dramatic impact of literacy acquisition on the human mind is an important prerequisite for successful education policy development and guidance of educational support.
  • Mishra, R., Srinivasan, N., & Huettig, F. (Eds.). (2015). Attention and vision in language processing. Berlin: Springer. doi:10.1007/978-81-322-2443-3.
  • Rommers, J., Meyer, A. S., & Huettig, F. (2015). Verbal and nonverbal predictors of language-mediated anticipatory eye movements. Attention, Perception & Psychophysics, 77(3), 720-730. doi:10.3758/s13414-015-0873-x.

    Abstract

    During language comprehension, listeners often anticipate upcoming information. This can draw listeners’ overt attention to visually presented objects before the objects are referred to. We investigated to what extent the anticipatory mechanisms involved in such language-mediated attention rely on specific verbal factors and on processes shared with other domains of cognition. Participants listened to sentences ending in a highly predictable word (e.g., “In 1969 Neil Armstrong was the first man to set foot on the moon”) while viewing displays containing three unrelated distractor objects and a critical object, which was either the target object (e.g., a moon), or an object with a similar shape (e.g., a tomato), or an unrelated control object (e.g., rice). Language-mediated anticipatory eye movements to targets and shape competitors were observed. Importantly, looks to the shape competitor were systematically related to individual differences in anticipatory attention, as indexed by a spatial cueing task: Participants whose responses were most strongly facilitated by predictive arrow cues also showed the strongest effects of predictive language input on their eye movements. By contrast, looks to the target were related to individual differences in vocabulary size and verbal fluency. The results suggest that verbal and nonverbal factors contribute to different types of language-mediated eye movement. The findings are consistent with multiple-mechanism accounts of predictive language processing.
  • Guerra, E., Huettig, F., & Knoeferle, P. (2014). Assessing the time course of the influence of featural, distributional and spatial representations during reading. In P. Bello, M. Guarini, M. McShane, & B. Scassellati (Eds.), Proceedings of the 36th Annual Meeting of the Cognitive Science Society (CogSci 2014) (pp. 2309-2314). Austin, TX: Cognitive Science Society. Retrieved from https://mindmodeling.org/cogsci2014/papers/402/.

    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.
  • Huettig, F. (2014). Role of prediction in language learning. In P. J. Brooks, & V. Kempe (Eds.), Encyclopedia of language development (pp. 479-481). London: Sage Publications.
  • Huettig, F., & Mishra, R. K. (2014). How literacy acquisition affects the illiterate mind - A critical examination of theories and evidence. Language and Linguistics Compass, 8(10), 401-427. doi:10.1111/lnc3.12092.

    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.
  • Mani, N., & Huettig, F. (2014). Word reading skill predicts anticipation of upcoming spoken language input: A study of children developing proficiency in reading. Journal of Experimental Child Psychology, 126, 264-279. doi:10.1016/j.jecp.2014.05.004.

    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.
  • McQueen, J. M., & Huettig, F. (2014). Interference of spoken word recognition through phonological priming from visual objects and printed words. Attention, Perception & Psychophysics, 76, 190-200. doi:10.3758/s13414-013-0560-8.

    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.
  • Olivers, C. N. L., Huettig, F., Singh, J. P., & Mishra, R. K. (2014). The influence of literacy on visual search. Visual Cognition, 21, 74-101. doi:10.1080/13506285.2013.875498.

    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.

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  • Smith, A. C., Monaghan, P., & Huettig, F. (2014). Examining strains and symptoms of the ‘Literacy Virus’: The effects of orthographic transparency on phonological processing in a connectionist model of reading. In P. Bello, M. Guarini, M. McShane, & B. Scassellati (Eds.), Proceedings of the 36th Annual Meeting of the Cognitive Science Society (CogSci 2014). Austin, TX: Cognitive Science Society.

    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’.
  • Smith, A. C., Monaghan, P., & Huettig, F. (2014). A comprehensive model of spoken word recognition must be multimodal: Evidence from studies of language-mediated visual attention. In P. Bello, M. Guarini, M. McShane, & B. Scassellati (Eds.), Proceedings of the 36th Annual Meeting of the Cognitive Science Society (CogSci 2014). Austin, TX: Cognitive Science Society.

    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.
  • Smith, A. C., Monaghan, P., & Huettig, F. (2014). Modelling language – vision interactions in the hub and spoke framework. In J. Mayor, & P. Gomez (Eds.), Computational Models of Cognitive Processes: Proceedings of the 13th Neural Computation and Psychology Workshop (NCPW13). (pp. 3-16). Singapore: World Scientific Publishing.

    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.
  • Smith, A. C., Monaghan, P., & Huettig, F. (2014). Literacy effects on language and vision: Emergent effects from an amodal shared resource (ASR) computational model. Cognitive Psychology, 75, 28-54. doi:10.1016/j.cogpsych.2014.07.002.

    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.

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