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

Speech segmentation requires flexible mechanisms to remain robust to features such as speech rate and pronunciation. Recent hypotheses suggest that low-frequency neural oscillations entrain to ongoing syllabic and phrasal rates, and that neural entrainment provides a speech-rate invariant means to discretize linguistic tokens from the acoustic signal. How this mechanism functionally operates remains unclear. Here, we test the hypothesis that neural entrainment reflects temporal predictive mechanisms. It implies that neural entrainment is built on the dynamics of past speech information: the brain would internalize the rhythm of preceding speech to parse the ongoing acoustic signal at optimal time points. A direct prediction is that ongoing neural oscillatory activity should match the rate of preceding speech even if the stimulation changes, for instance when the speech rate suddenly increases or decreases. Crucially, the persistence of neural entrainment to past speech rate should modulate speech perception. We performed an MEG experiment in which native Dutch speakers listened to sentences with varying speech rates. The beginning of the sentence (carrier window) was either presented at a fast or a slow speech rate, while the last three words (target window) were displayed at an intermediate rate across trials. Participants had to report the perception of the last word of the sentence, which was ambiguous with regards to its vowel duration (short vowel /ɑ/ – long vowel /aː/ contrast). MEG data was analyzed in source space using beamformer methods. Consistent with previous behavioral reports, the perception of the ambiguous target word was influenced by the past speech rate; participants reported more /aː/ percepts after a fast speech rate, and more /ɑ/ after a slow speech rate. During the carrier window, neural oscillations efficiently tracked the dynamics of the speech envelope. During the target window, we observed oscillatory activity that corresponded in frequency to the preceding speech rate. Traces of neural entrainment to the past speech rate were significantly observed in medial prefrontal areas. Right superior temporal cortex also showed persisting oscillatory activity which correlated with the observed perceptual biases: participants whose perception was more influenced by the manipulation in speech rate also showed stronger remaining neural oscillatory patterns. The results show that neural entrainment lasts after rhythmic stimulation. The findings further provide empirical support for oscillatory models of speech processing, suggesting that neural oscillations actively encode temporal predictions for speech comprehension.

Abstract

Previous research indicates that general cognitive abilities, such as attention or executive control, contribute to language processing (Hartsuiker & Barkhuysen, 2006; Jongman et al., 2014; Shao et al., 2013). Potential effects of language-specific abilities, such as vocabulary, on language processing in adult native speakers have been examined less extensively. Goals: a) develop and assess measures of vocabulary size in Dutch native speakers, and b) investigate the relationship between individual differences in vocabulary and language processing.

Abstract

Listeners are continuously exposed to a broad range of speech rates. Earlier work has shown that listeners perceive phonetic category boundaries relative to contextual speech rate. It has been suggested that this process of speech rate normalization occurs across talker changes. This would predict that the speech rate of talker A influences perception of the rate of another talker B. We assessed this hypothesis by testing effects of speech rate on the perception on the Dutch vowel continuum /A/-/a:/. One participant group was exposed to 'neutral' speech from talker A intermixed with fast speech from talker B. Another group listened to the same speech from talker A, but to slow speech from talker B. We observed a difference in perception of talker A depending on the speech rate of talker B: A's 'neutral' speech was perceived as slow when B spoke faster. These findings corroborate the idea that speech rate normalization occurs across talkers, but they challenge the assumption that listeners average over speech rates from multiple talkers. Instead, they suggest that listeners contrast talker-specific rates.

Abstract

Natural conversations are characterized by smooth transitions of turns between interlocutors. For instance, speakers often respond to questions or requests within half a second. As planning the first word of an utterance can easily take a second or more, this suggests that utterance planning often overlaps with listening to the preceding speaker's utterance. A specific proposal concerning the temporal coordination of listening and speech planning has recently been made by Levinson and Torreira (2016, Frontiers in Psychology; Levinson, 2016, Trends in Cognitive Sciences). They propose that speakers initiate their speech planning as soon as they have understood the speech act and gist of the preceding utterance. However, direct evidence for simultaneous listening and speech planning is scarce. I will first review studies demonstrating that both comprehending spoken utterances and planning them require processing capacity and that these processes can substantially interfere with each other. These data suggest that concurrent speech planning and listening should be cognitively quite challenging. In the second part of the talk I will turn to studies examining directly when utterance planning in dialogue begins. These studies indicate that (regrettably) there are probably no hard-and-fast rules for the temporal coordination of listening and speech planning. I will argue that (regrettably again) we need models that are far more complex than Levinson and Torreira's proposal to understand how listening and speech planning are coordinated in conversation

Abstract

We show that language users readily learn the probabilities of novel lexical cues to syntactic information (verbs biasing towards a prepositional object dative vs. double-object dative and words biasing towards a verb vs. noun reading) and use these biases in a subsequent production task. In a one-hour exposure phase participants read 12 novel lexical items, embedded in 30 sentence contexts each, in their native language. The items were either strongly (100%) biased towards one grammatical frame or syntactic category assignment or unbiased (50%). The next day participants produced sentences with the newly learned lexical items. They were given the sentence beginning up to the novel lexical item. Their output showed that they were highly sensitive to the biases introduced in the exposure phase.
Given this rapid learning and use of novel lexical cues, this paradigm opens up new avenues to test sentence processing theories. Thus, with close control on the biases participants are acquiring, competition between different frames or category assignments can be investigated using reaction times or neuroimaging methods.
Generally, these results show that language users adapt to the statistics of the linguistic input, even to subtle lexically-driven cues to syntactic information.

Abstract

Subject-verb agreement is one of the most common
grammatical encoding operations in language
production. In many languages, morphological
inflection on verbs code for the number of the head
noun of a subject phrase (e.g., The key to the cabinets
is rusty). Despite the relative ease with which subjectverb
agreement is accomplished, people sometimes
make agreement errors (e.g., The key to the cabinets
are rusty). Such errors offer a window into the early
stages of production planning. Agreement errors are
influenced by both syntactic and semantic factors, and
are more likely to occur when a sentence contains either
conceptual or syntactic number mismatches. Little
is known about the timecourse of these influences,
however, and some controversy exists as to whether
they are independent. The current study was designed
to address these two issues using EEG. Semantic and
syntactic factors influencing number mismatch were
factorially-manipulated in a forced-choice sentence
completion paradigm. To avoid EEG artifact associated
with speaking, participants (N=20) were presented with
a noun-phrase, and pressed a button to indicate which
version of the verb ‘to be’ (is/are) should continue
the sentence. Semantic number was manipulated
using preambles that were semantically-integrated or
unintegrated. Semantic integration refers to the semantic
relationship between nouns in a noun-phrase, with
integrated items promoting conceptual-singularity.
The syntactic manipulation was the number (singular/
plural) of the local noun preceding the decision. This
led to preambles such as “The pizza with the yummy
topping(s)... “ (integated) vs. “The pizza with the tasty
bevarage(s)...” (unintegrated). Behavioral results showed
effects of both Local Noun Number and Semantic
Integration, with more errors and longer reaction times
occurring in the mismatching conditions (i.e., plural
local nouns; unintegrated subject phrases). Classic ERP
analyses locked to the local noun (0-700 ms) and to the
time preceding the response (-600 to 0 ms) showed no
systematic differences between conditions. Despite this
result, we assessed whether difference might emerge
using multivariate pattern analysis (MVPA). Using the
same epochs as above, support-vector machines with a
radial basis function were trained on the single-trial level
to classify the difference between Local Noun Number
and Semantic Integration conditions across time and
channels. Results revealed that both conditions could
be reliably classified at the single subject level, and
that classification accuracy was strongest in the epoch
preceding the response. Classification accuracy was
at chance when a classifier trained to dissociate Local
Noun Number was used to predict Semantic Integration
(and vice versa), providing some evidence of the
independence of the two effects. Significant inter-subject
variability was present in the channels and time-points
that were critical for classification, but earlier timepoints
were more often important for classifying Local Noun
Number than Semantic Integration. One result of this
variability is classification performed across subjects was
at chance, which may explain the failure to find standard
ERP effects. This study thus provides an important first
test of semantic and syntactic influences on subject-verb
agreement with EEG, and demonstrates that where
classic ERP analyses fail, MVPA can reliably distinguish
differences at the neurophysiological level.

Abstract

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.