Towards a complete multiple-mechanism account of predictive language processing [Commentary on Pickering & Garrod]

Although we agree with Pickering & Garrod (P&G) that prediction-by-simulation and prediction-by-association are important mechanisms of anticipatory language processing, this commentary suggests that they: (1) overlook other potential mechanisms that might underlie prediction in language processing, (2) overestimate the importance of prediction-by-association in early childhood, and (3) underestimate the complexity and significance of several factors that might mediate prediction during language processing

Prediction using production or production engaging prediction?

Prominent theories of predictive language processing assume that language production processes are used to anticipate upcoming linguistic input during comprehension (Dell & Chang, 2014; Pickering & Garrod, 2013). Here, we explore the converse case: Does a task set including production in addition to comprehension encourage prediction, compared to a task only including comprehension? To test this hypothesis, we conducted a cross-modal naming experiment (Experiment 1) including an object naming task and a self-paced reading experiment (Experiment 2) that did not include overt production. We used the same predictable (N = 40) and non-predictable (N = 40) sentences in both experiments. The sentences consisted of a fixed agent, a transitive verb and a predictable or non-predictable target word (The man drinks a beer vs. The man buys a beer). Most of the empirical work on prediction used sentences in which the target words were highly predictable (often with a mean cloze probability > .8) and thus it is little surprising that participants engaged in predictive language processing very easily. In the current sentences, the mean cloze probability in the predictable sentences was .39 (ranging from .06 to .8; zero in the non-predictable sentences). If comprehenders are more likely to engage in predictive processing when the task set involves production, we should observe more pronounced effects of prediction in Experiment 1 as compared to Experiment 2. If production does not enhance prediction, we should observe similar effects of prediction in both experiments. In Experiment 1, participants (N = 54) listened to recordings of the sentences which ended right before the spoken target word. Coinciding with the end of the playback, a picture of the target word was shown which the participants were asked to name as fast as possible. Analyses of their naming latencies revealed a statistically significant naming advantage of 106 ms on predictable over non-predictable trials. Moreover, we found that the objects’ naming advantage was predicted by the target words’ cloze probability in the sentences (r = .411, p = .016). In Experiment 2, the same sentences were used in a self-paced reading experiment. To allow for testing of potential spill-over effects, we added a neutral prepositional phrase (buys a beer from the bar keeper/drinks a beer from the shop) to each sentence. Participants (N = 54) read the sentences word-by-word, advancing by pushing the space bar. On 30% of the trials, comprehension questions were used to keep up participants' focus on comprehending the sentences. Analyses of participants’ target and post-target reading times revealed numerical advantages of 6 ms and 20 ms, respectively, in the predictable as compared to the non-predictable condition. However, in both cases, this difference was not statistically reliable (t = .757, t = 1.43) and the significant positive correlation between an item’s naming advantage and its cloze probability as seen in Experiment 1 was absent (r = .037, p = .822). Importantly, the analysis of participants' responses to the comprehension questions, showed that they understood the sentences (mean accuracy = 93%). To conclude, although both experiments used the same sentences, we observed effects of prediction only when the task included production. In Experiment 2, no evidence for anticipation was found although participants clearly understood the sentences and the method has previously been shown to be sensitive to measure prediction effects (Van Berkum et al., 2005). Our results fit with a recent study by Gollan et al. (2011) who found only a small processing advantage of predictive over non-predictive sentences in reading (using highly predictable sentences with a cloze probability > . 87) but a strong prediction effect when participants read the same sentences and carried out an additional object naming task (see also Griffin & Bock, 1998). Taken together, the studies suggest that the comprehenders' task set exerts a powerful influence on the likelihood and magnitude of predictive language processing. When the task set involves language production, as is often the case in natural conversation, comprehenders might engage in prediction to a stronger degree than in pure comprehension tasks. Being able to predict words another person is about to say might optimize the comprehension process and enable smooth turn-taking

Six challenges for embodiment research

20 years after Barsalou's seminal perceptual symbols paper (Barsalou, 1999), embodied cognition, the notion that cognition involves simulations of sensory, motor, or affective states, has moved in status from an outlandish proposal advanced by a fringe movement in psychology to a mainstream position adopted by large numbers of researchers in the psychological and cognitive (neuro)sciences. While it has generated highly productive work in the cognitive sciences as a whole, it had a particularly strong impact on research into language comprehension. The view of a mental lexicon based on symbolic word representations, which are arbitrarily linked to sensory aspects of their referents, for example, was generally accepted since the cognitive revolution in the 1950s. This has radically changed. Given the current status of embodiment as a main theory of cognition, it is somewhat surprising that a close look at the state of the affairs in the literature reveals that the debate about the nature of the processes involved in language comprehension is far from settled and key questions remain unanswered. We present several suggestions for a productive way forward

Looking at nothing facilitates memory retrieval

When processing visual objects, we integrate visual, linguistic and spatial information to form an episodic trace. Re-activating one aspect of the episodic trace of an object re-activates the entire bundle making all integrated information available. Using the blank screen paradigm [1], researchers observed that upon processing spoken linguistic input, participants tended to make eye movements on a blank screen, fixating locations that were previously occupied by objects mentioned in the linguistic utterance or were related. Ferreira and colleagues [2] suggested that 'looking at nothing' facilitated memory retrieval. However, this claim lacks convincing empirical support. In Experiment 1, Dutch participants looked at four-object-displays. Three objects were related to a spoken target word. Given the target word 'beker' (beaker), the display featured a phonological (a bear), a shape (a bobbin), a semantic (a fork) competitor, and an unrelated distractor (an umbrella). Participants were asked to name the objects as fast as possible. Subsequently, the objects disappeared. Participants fixated the center of the screen and listened to the target word. They had to carry out a semantic judgment task (indicating in which position an object had appeared that was semantically related to the objects) or a visual shape similarity judgment (indicating the position of the object similar in shape to the target). In both conditions, we observed that participants re-fixated the empty target location before responding. The set-up of Experiment 2 was identical except that we asked participants to maintain fixating the center of the screen while listening to the spoken word and responding. Performance accuracy was significantly lower in Experiment 2 than in Experiment 1. The results indicate that memory retrieval for objects is impaired when participants are not allowed to look at relevant, though empty locations. [1] Altmann, G. (2004). Language-mediated eye movements in the absence of a visual world: the 'blank screen paradigm'. Cognition, 93(2), B79-B87. [2] Ferreira, F., Apel, J., & Henderson, J. M. (2008). Taking a new look at looking at nothing. Trends Cogn Sci, 12(11), 405-410

Fast and slow language processing: A window into dual-process models of cognition. Commentary on De Neys.

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

Is prediction necessary to understand language?

Many psycholinguistic experiments suggest that prediction is an important characteristic of language processing. Some recent theoretical accounts in the cognitive sciences (e.g., Clark, 2013; Friston, 2010) and psycholinguistics (e.g., Dell & Chang, 2014) appear to suggest that prediction is even necessary to understand language. I will evaluate this proposal. I will first discuss several arguments that may appear to be in line with the notion that prediction is necessary for language processing. These arguments include that prediction provides a unified theoretical principle of the human mind and that it pervades cortical function. We discuss whether evidence of human abilities to detect statistical regularities is necessarily evidence for predictive processing and evaluate suggestions that prediction is necessary for language learning. Five arguments are then presented that question the claim that all language processing is predictive in nature. I point out that not all language users appear to predict language and that suboptimal input makes prediction often very challenging. Prediction, moreover, is strongly context-dependent and impeded by resource limitations. I will also argue that it may be problematic that most experimental evidence for predictive language processing comes from 'prediction-encouraging' experimental set-ups. Finally, I will discuss possible ways that may lead to a further resolution of this debate. We conclude that languages can be learned and understood in the absence of prediction. Claims that all language processing is predictive in nature are premature

The myth of normal reading

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

Word reading skill predicts anticipation of upcoming spoken language input: A study of children developing proficiency in reading

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