Presentations

Abstract

Serial naming deficits have been identified as core symptoms of developmental dyslexia. A prominent hypothesis is that naming delays are due to inefficient phonological encoding, yet the exact nature of this underlying impairment remains largely underspecified. Here we used recordings of eye movements and word onset latencies to examine at what processing level the dyslexic naming deficit emerges: localized at an early stage of lexical encoding or rather later at the level of phonetic or motor planning. 23 dyslexic and 25 control adult readers were tested on a serial object naming task for 30 items and an analogous reading task, where phonological neighborhood density and word-frequency were manipulated. Results showed that both word properties influenced early stages of phonological activation (first fixation and first-pass duration) equally in both groups of participants. Moreover, in the control group any difficulty appeared to be resolved early in the reading process, while for dyslexic readers a processing disadvantage for low-frequency words and for words with sparse neighborhood also emerged in a measure that included late stages of output planning (eye-voice span). Thus, our findings suggest suboptimal phonetic and/or articulatory planning in dyslexia.

Abstract

Reading functions beyond early visual precessing are known to be lateralized to the left hemisphere, but how left-lateralization arises during literacy acquisition is an open question. Bilateral processing or rightward asymmetries have previously been associated with developmental dyslexia. However, it is unclear at present to what extent this lack of left-lateralization reflects differences in reading ability. In this study, a group of illiterate adults in rural India (N=29) participated in a literacy training program over the course of six months. fMRI measures were obtained before and after training on a number of different visual stimulus categories, including written sentences, false fonts, and object categories such as houses and faces. This training group was matched on demographic and socioeconomic variables to an illiterate no-training group and to low- and highly-literate control groups, who were also scanned twice but received no training (total N=90). In a cross-sectional analysis before training, reading ability was positively correlated with increased BOLD responses in a left-lateralized network including the dorsal and ventral visual streams for text and false fonts, but not for other types of visual stimuli. A longitudinal analysis of learning effects in the training group showed that beginning readers engage bilateral networks more than proficient readers. Lateralization of BOLD responses was further examined by calculating laterality indices in specific regions. We observed training-related changes in lateralization for processing written stimuli in a number of subregions in the dorsal and ventral visual streams, as well as in the cerebellum. Together with the cross-sectional results, these data suggest a causal relationship between reading ability and the degree of hemispheric asymmetry in processing written materials.

Abstract

Reading functions beyond early visual precessing are known to be lateralized to the left hemisphere, but how left-lateralization arises during literacy acquisition is an open question. Bilateral processing or rightward asymmetries have previously been associated with developmental dyslexia. However, it is unclear at present to what extent this lack of left-lateralization reflects differences in reading ability. In this study, a group of illiterate adults in rural India (N=29) participated in a literacy training program over the course of six months. fMRI measures were obtained before and after training on a number of different visual stimulus categories, including written sentences, false fonts, and object categories such as houses and faces. This training group was matched on demographic and socioeconomic variables to an illiterate no-training group and to low- and highly-literate control groups, who were also scanned twice but received no training (total N=90). In a cross-sectional analysis before training, reading ability was positively correlated with increased BOLD responses in a left-lateralized network including the dorsal and ventral visual streams for text and false fonts, but not for other types of visual stimuli. A longitudinal analysis of learning effects in the training group showed that beginning readers engage bilateral networks more than proficient readers. Lateralization of BOLD responses was further examined by calculating laterality indices in specific regions. We observed training-related changes in lateralization for processing written stimuli in a number of subregions in the dorsal and ventral visual streams, as well as in the cerebellum. Together with the cross-sectional results, these data suggest a causal relationship between reading ability and the degree of hemispheric asymmetry in processing written materials.

Abstract

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.

Abstract

How do human cultural inventions such as reading result in neural re-organization? In this first longitudinal study with young completely illiterate adult participants, we measured brain responses to speech, text, and other categories of visual stimuli with fMRI before and after a group of illiterate participants in India completed a literacy training program in which they learned to read and write Devanagari script. A literate and an illiterate no-training control group were matched to the training group in terms of socioeconomic background and were recruited from the same societal community in two villages of a rural area near Lucknow, India. This design permitted investigating effects of literacy cross-sectionally across groups before training (N=86) as well as longitudinally (training group N=25). The two analysis approaches yielded converging results: Literacy was associated with enhanced, left-lateralized responses to written text along the ventral stream (including lingual gyrus, fusiform gyrus, and parahippocampal gyrus), dorsal stream (intraparietal sulcus), and (pre-) motor systems (pre-central sulcus, supplementary motor area) and thalamus (pulvinar). Significantly reduced responses were observed bilaterally in the superior parietal lobe (precuneus) and in the right angular gyrus. These effects corroborate and extend previous findings from cross-sectional studies. However, effects of literacy were specific to written text and (to a lesser extent) to false fonts. We did not find any evidence for effects of literacy on responses in the auditory cortex in our Hindi-speaking participants. This raises questions about the extent to which phonological representations are altered by literacy acquisition.

Abstract

We conceptualize objects based on sensory and motor information gleaned from real-world experience. But to what extent is such conceptual information structured according to higher level linguistic features too? Here we investigate whether classifiers, a grammatical category, shape the conceptual representations of objects. In three experiments native Mandarin speakers (speakers of a classifier language) and native Dutch speakers (speakers of a language without classifiers) judged the similarity of a target object (presented as a word or picture) with four objects (presented as words or pictures). One object shared a classifier with the target, the other objects did not, serving as distractors. Across all experiments, participants judged the target object as more similar to the object with the shared classifier than distractor objects. This effect was seen in both Dutch and Mandarin speakers, and there was no difference between the two languages. Thus, even speakers of a non-classifier language are sensitive to object similarities underlying classifier systems, and using a classifier system does not exaggerate these similarities. This suggests that classifier systems simply reflect, rather than affect, conceptual structure.

Abstract

In sentence comprehension, readers and listeners often anticipate upcoming information (e.g., Altmann & Kamide, 1999). We investigated two aspects of this process, namely 1) what is pre-activated when anticipating an upcoming word (the contents of predictions), and 2) which cognitive mechanisms are involved. The contents of predictions at the level of meaning could be restricted to functional semantic attributes (e.g., edibility; Altmann & Kamide, 1999). However, when words are processed other types of information can also be activated, such as object shape representations. It is unknown whether this type of information is already activated when upcoming words are predicted. Forty-five adult participants listened to predictable words in sentence contexts (e.g., "In 1969 Neil Armstrong was the first man to set foot on the moon.") while looking at visual displays of four objects. Their eye movements were recorded. There were three conditions: target present (e.g., a moon and three distractor objects that were unrelated to the predictable word in terms of semantics, shape, and phonology), shape competitor (e.g., a tomato and three unrelated distractors), and distractors only (e.g., rice and three other unrelated objects). Across lists, the same pictures and sentences were used in the different conditions. We found that participants already showed a significant bias for the target object (moon) over unrelated distractors several seconds before the target was mentioned, demonstrating that they were predicting. Importantly, there was also a smaller but significant shape competitor (tomato) preference starting at about a second before critical word onset, consistent with predictions involving the referent’s shape. The mechanisms of predictions could be specific to language tasks, or language could use processing principles that are also used in other domains of cognition. We investigated whether performance in non-linguistic prediction is related to prediction in language processing, taking an individual differences approach. In addition to the language processing task, the participants performed a simple cueing task (after Posner, Nissen, & Ogden, 1978). They pressed one of two buttons (left/right) to indicate the location of an X symbol on the screen. On half of the trials, the X was preceded by a neutral cue (+). On the other half, an arrow cue pointing left (<) or right (>) indicated the upcoming X's location with 80% validity (i.e., the arrow cue was correct 80% of the time). The SOA between cue and target was 500 ms. Prediction was quantified as the mean response latency difference between the neutral and valid condition. This measure correlated positively with individual participants' anticipatory target and shape competitor preference (r = .27; r = .45), and was a significant predictor of anticipatory looks in linear mixed-effects regression models of the data. Participants who showed more facilitation from the arrow cues predicted to a higher degree in the linguistic task. This suggests that prediction in language processing may use mechanisms that are also used in other domains of cognition. References Altmann, G. T. M., & Kamide, Y. (1999). Incremental interpretation at verbs: Restricting the domain of subsequent reference. Cognition, 73(3), 247-264. Posner, M. I., Nissen, M. J., & Ogden, W. C. (1978). Attended and unattended processing modes: The role of set for spatial location. In: H.L. Pick, & I.J. Saltzman (Eds.), Modes of perceiving and processing information. Hillsdale, N.J.: Lawrence Erlbaum Associates.

Abstract

Hub-and-spoke models of semantic processing which integrate modality specific information within a central resource have proven successful in capturing a range of neuropsychological phenomena (Rogers et al, 2004; Dilkina et al, 2008). Within our study we investigate whether the scope of the Hub-and-spoke architectural framework can be extended to capture behavioural phenomena in other areas of cognition. The visual world paradigm (VWP) has contributed significantly to our understanding of the information and processes involved in spoken word recognition. In particular it has highlighted the importance of non-linguistic influences during language processing, indicating that combined information from vision, phonology, and semantics is evident in performance on such tasks (see Huettig, Rommers & Meyer, 2011). Huettig & McQueen (2007) demonstrated that participants’ fixations to objects presented within a single visual display varied systematically according to their phonological, semantic and visual relationship to a spoken target word. The authors argue that only an explanation allowing for influence from all three knowledge types is capable of accounting for the observed behaviour. To date computational models of the VWP (Allopenna et al, 1998; Mayberry et al, 2009; Kukona et al, 2011) have focused largely on linguistic aspects of the task and have therefore been unable to offer explanations for the growing body of experimental evidence emphasising the influence of non-linguistic information on spoken word recognition. Our study demonstrates that an emergent connectionist model, based on the Hub-and-spoke models of semantic processing, which integrates visual, phonological and functional information within a central resource, is able to capture the intricate time course dynamics of eye fixation behaviour reported in Huettig & McQueen (2007). Our findings indicate that such language mediated visual attention phenomena can emerge largely due to the statistics of the problem domain and may not require additional domain specific processing constraints.

Abstract

Language processing does not take place in isolation from the sensory environment. Listeners are able to recognise spoken words in many different situations, ranging from carefully articulated and noise-free laboratory speech, through casual conversational speech in a quiet room, to degraded conversational speech in a busy train-station. For listeners to be able to recognize speech optimally in each of these listening situations, they must be able to adapt to the constraints of each situation. We investigated this flexibility by comparing the dynamics of the spoken-word recognition process in clear speech and speech disrupted by radio noise. In Experiment 1, Dutch participants listened to clearly articulated spoken Dutch sentences which each included a critical word while their eye movements to four visual objects presented on a computer screen were measured. There were two critical conditions. In the first, the objects included a cohort competitor (e.g., parachute, “parachute”) with the same onset as the critical spoken word (e.g., paraplu, “umbrella”) and three unrelated distractors. In the second condition, a rhyme competitor (e.g., hamer, “hammer”) of the critical word (e.g., kamer, “room”) was present in the display, again with three distractors. To maximize competitor effects pictures of the critical words themselves were not present in the displays on the experimental trials (e.g.,there was no umbrella in the display with the 'paraplu' sentence) and a passive listening task was used (Huettig McQueen, 2007). Experiment 2 was identical to Experiment 1 except that phonemes in the spoken sentences were replaced with radio-signal noises (as in AM radio listening conditions). In each sentence, two,three or four phonemes were replaced with noises. The sentential position of these replacements was unpredictable, but the adjustments were always made to onset phonemes. The critical words (and the immediately surrounding words) were not changed. The question was whether listeners could learn that, under these circumstances, onset information is less reliable. We predicted that participants would look less at the cohort competitors (the initial match to the competitor is less good) and more at the rhyme competitors (the initial mismatch is less bad). We observed a significant experiment by competitor type interaction. In Experiment 1 participants fixated both kinds competitors more than unrelated distractors, but there were more and earlier looks to cohort competitors than to rhyme competitors (Allopenna et al., 1998). In Experiment 2 participants still fixated cohort competitors more than rhyme competitors but the early cohort effect was reduced and the rhyme effect was stronger and occurred earlier. These results suggest that AM radio noise changes the dynamics of spoken word recognition. The well-attested finding of stronger reliance on word onset overlap in speech recognition appears to be due in part to the use of clear speech in most experiments. When onset information becomes less reliable, listeners appear to depend on it less. A core feature of the speech-recognition system thus appears to be its flexibility. Listeners are able to adjust the perceptual weight they assign to different parts of incoming spoken language.

Abstract

If a Mandarin speaker had walked past two rivers and wished to describe how many he had seen, he would have to say “two tiao river”, where tiao designates long, rope-like objects such as rivers, snakes and legs. Tiao is one of several hundred classifiers – a grammatical category in Mandarin. In two eye-tracking studies we presented Mandarin speakers with simple Mandarin sentences through headphones while monitoring their eye-movements to objects presented on a computer monitor. The crucial question is what participants look at while listening to a pre-specified target noun. If classifier categories influence general conceptual processing then on hearing the target noun participants should look at objects that are also members of the same classifier category – even when the classifier is not explicitly present. For example, on hearing scissors, Mandarin speakers should look more at a picture of a chair than at an unrelated object because scissors and chair share the classifier ba. This would be consistent with a Strong Whorfian position, according to which language is a major determinant in shaping conceptual thought (Sapir, 1921; Whorf, 1956). A weaker influence of language-on-thought could be predicted, where language shapes cognitive processing, but only when the language-specific category is actively being processed (Slobin, 1996). According to this account, eye-movements are not necessarily drawn to chair when a participant hears scissors, but they would be on hearing ba scissors. This is because hearing ba activates the linguistic category that both scissors and chair belong to. A third logical possibility is that classifiers are purely formal markers (cf. Greenberg, 1972; Lehman, 1979) that do not influence attentional processing even when they are explicitly present. The data showed that when participants heard a spoken word from the same classifier category as a visually depicted object (e.g. scissors-chair), but the classifier was not explicitly presented in the speech, overt attention to classifier-match objects (e.g. chair) and distractor objects did not differ (Experiment 1). But when the classifier was explicitly presented (e.g. ba, Experiment 2), participants shifted overt attention significantly more to classifier-match objects (e.g. chair) than to distractors. These data are incompatible with the Strong Whorfian hypothesis. Instead the findings support the Weak Whorfian hypothesis that linguistic distinctions force attention to properties of the world but only during active linguistic processing of that distinction (cf. Slobin, 1996).