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In previous research, mutual information (MI) was employed to quantify the physical information shared between consecutive phonological segments, based on electromagnetic articulography data. In this study, MI is extended to quantifying coarticulatory resistance (CR) versus overlap in German using ultrasound imaging. Two measurements are tested as input to MI: (1) the highest point on the tongue body and (2) the first coefficient of the discrete Fourier transform (DFT) of the whole tongue contour. Both measures are used to examine changes in coarticulation between two time points during the syllable span: the consonant midpoint and the vowel onset. Results corroborate previous findings reporting differences in coarticulatory overlap in German and across languages. Further, results suggest that MI used with the highest point on the tongue body captures distinctions related both to place and manner of articulation, while the first DFT coefficient does not provide any additional information regarding global (whole tongue) as opposed to local (individual articulator) aspects of CR. However, both methods capture temporal distinctions in coarticulatory resistance between the two time points. Results are discussed with respect to the potential of MI measure to provide a way of unifying coarticulation quantification methods across data collection techniques.
Background: Comprehension of non-canonical sentences is frequently characterised by chance level performance in people with aphasia (PWA). Chance level performance has been interpreted as guessing, but online data does not support this rendering. It is still not clear whether the incorrect sentence processing is guided by the compensatory strategies that PWA might employ to overcome linguistic difficulties.Aims: We aim to study to what extent people with non-fluent aphasia are aware of their sentence comprehension deficits.Methods & Procedures: This study combined offline and online data to investigate the effect of word order and error-awareness on sentence comprehension in a group of PWA and non-brain damaged (NBD) participants. The offline tasks involved auditory sentence picture-matching immediately followed by a confidence rating (CR). Participants were asked to judge the perceived correctness of their previous answer. Online data consisted of eye-tracking.Outcomes & Results: Replicating previous findings, PWA had significantly worse comprehension of Theme-Agent order compared to Agent-Theme order sentences. Controls showed ceiling level sentence comprehension. CR was a poor predictor of response accuracy in PWA, but moderate-good in NBD. A total of 6.8% of judgements were classified as guessing by PWA. Post hoc gaze data analysis indicated that CR was a predictor of the fixation pattern during the presentation of the linguistic stimuli.Conclusions: Results suggest that PWA were mostly unaware of their sentence comprehension errors and did not consciously employ strategies to compensate for their difficulties.
The article takes up on the observations made byKenesei (1994) regarding the position of the Hungarian interrogative marker -e in the clause and its distribution across clause types. Specifically, there are three crucial points: (i) the marker -e is related to the CP-domain, where clause typing is encoded; (ii) -e is obligatory in embedded clauses and optional in main clauses; (iii) -e is licensed in finite clauses only. I argue that certain clause-typing properties are reflected in the Hungarian clause in a lower functional domain, FP. In particular, finiteness and the interrogative nature of the clause are encoded here, as also indicated by focussing in non-interrogative clauses and by constituent questions, respectively. The marker -e is base-generated in the F head, as opposed to a designated FocP or TP/IP, allowing it to fulfil its clause-typing functions. Base-generation is crucial (as opposed to lowering from C) since it is able to capture the relatedness between -e and finiteness: -e is specified as [fin] and while the FP may be generated to host focussed constituents (including wh-elements) in non-finite clauses, a lexically [fin] head cannot be inserted.
Clause typing in Germanic
(2018)
The questionnaire investigates the functional left periphery of various finite clauses in Germanic languages, with particular attention paid to clause-typing elements and the combinations thereof. The questionnaire is mostly concerned with clause typing in embedded clauses, but main clause counterparts are also considered for comparative purposes. The chief aim was to achieve comparable results across Germanic languages, though the standardised questionnaire may also be helpful in the study of other languages, too. Most questions examine the availability of various complementisers and clause-typing operators, and in some cases the movement of verbs to the left periphery is also taken into account. The questionnaire is split into seven major parts according to the types of clauses under scrutiny.
All instructions were given in English and the individual questions either concern translations of given sentences from English into the target language, and/or they ask for specific details about the constructions in the target language.
The present document contains the questionnaire itself (together with the instructions given at the beginning of the questionnaire and at the beginning of the individual sections, as well as the questions asking for personal data), the sociolinguistic data of the speakers, and the actual results for the individual languages. Five Germanic languages are included: Dutch, Danish, Icelandic, Norwegian and Swedish. For each language, two informants were recruited. Given the small number of informants, the present study serves as a qualitative investigation and as a basis for further, quantitative and experimental studies.
We investigated online electrophysiological components of distributional learning, specifically of tones by listeners of a non tonal language. German listeners were presented with a bimodal distribution of syllables with lexical tones from a synthesized continuum based on Cantonese level tones. Tones were presented in sets of four standards (within-category tokens) followed by a deviant (across-category token). Mismatch negativity (MMN) was measured. Earlier behavioral data showed that exposure to this bimodal distribution improved both categorical perception and perceptual acuity for level tones [I]. In the present study we present analyses of the electrophysiological response recorded during this exposure, i.e., the development of the MMN response during distributional learning. This development over time is analyzed using Generalized Additive Mixed Models and results showed that the MMN amplitude increased for both within and across-category tokens, reflecting higher perceptual acuity accompanying category formation. This is evidence that learners zooming in on phonological categories undergo neural changes associated with more accurate phonetic perception.
The aim of this review is to provide a selective overview of priming studies which have employed the event-related brain potential (ERP) technique in order to investigate bilingual language processing. The priming technique can reveal an implicit memory effect in which exposure to one stimulus influences the processing of another stimulus. Behavioral approaches, such as measuring reaction times, may not always be enough for providing a full view on the exact mechanisms and the time-course of language comprehension. Instead, ERPs have a time-resolution of a millisecond and hence they offer a precise temporal overview of the underlying neural processes involved in language processing. In our review, we summarize experimental research that has combined priming with ERP measurements, thus creating a valuable tool for examining the neurophysiological correlates of language processing in the bilingual brain.
Moving beyond ERP components
(2018)
Relationships between neuroimaging measures and behavior provide important clues about brain function and cognition in healthy and clinical populations. While electroencephalography (EEG) provides a portable, low cost measure of brain dynamics, it has been somewhat underrepresented in the emerging field of model-based inference. We seek to address this gap in this article by highlighting the utility of linking EEG and behavior, with an emphasis on approaches for EEG analysis that move beyond focusing on peaks or "components" derived from averaging EEG responses across trials and subjects (generating the event-related potential, ERP). First, we review methods for deriving features from EEG in order to enhance the signal within single-trials. These methods include filtering based on user-defined features (i.e., frequency decomposition, time-frequency decomposition), filtering based on data-driven properties (i.e., blind source separation, BSS), and generating more abstract representations of data (e.g., using deep learning). We then review cognitive models which extract latent variables from experimental tasks, including the drift diffusion model (DDM) and reinforcement learning (RL) approaches. Next, we discuss ways to access associations among these measures, including statistical models, data-driven joint models and cognitive joint modeling using hierarchical Bayesian models (HBMs). We think that these methodological tools are likely to contribute to theoretical advancements, and will help inform our understandings of brain dynamics that contribute to moment-to-moment cognitive function.
Sensitivity to salience
(2018)
Sentence comprehension is optimised by indicating entities as salient through linguistic (i.e., information-structural) or visual means. We compare how salience of a depicted referent due to a linguistic (i.e., topic status) or visual cue (i.e., a virtual person's gaze shift) modulates sentence comprehension in German. We investigated processing of sentences with varying word order and pronoun resolution by means of self-paced reading and an antecedent choice task, respectively. Our results show that linguistic as well as visual salience cues immediately speeded up reading times of sentences mentioning the salient referent first. In contrast, for pronoun resolution, linguistic and visual cues modulated antecedent choice preferences less congruently. In sum, our findings speak in favour of a significant impact of linguistic and visual salience cues on sentence comprehension, substantiating that salient information delivered via language as well as the visual environment is integrated in the current mental representation of the discourse.
Variation in the speech signal as a window into the cognitive architecture of language production
(2018)
The pronunciation of words is highly variable. This variation provides crucial information about the cognitive architecture of the language production system. This review summarizes key empirical findings about variation phenomena, integrating corpus, acoustic, articulatory, and chronometric data from phonetic and psycholinguistic studies. It examines how these data constrain our current understanding of word production processes and highlights major challenges and open issues that should be addressed in future research.
Background: Event-related potentials (ERPs) are increasingly used in cognitive science. With their high temporal resolution, they offer a unique window into cognitive processes and their time course. In this paper, we focus on ERP experiments whose designs involve selecting participants and stimuli amongst many. Recently, Westfall et al. (2017) highlighted the drastic consequences of not considering stimuli as a random variable in fMRI studies with such designs. Most ERP studies in cognitive psychology suffer from the same drawback. New method: We advocate the use of the Quasi-F or Mixed-effects models instead of the classical ANOVA/by-participant F1 statistic to analyze ERP datasets in which the dependent variable is reduced to one measure per trial (e.g., mean amplitude). We combine Quasi-F statistic and cluster mass tests to analyze datasets with multiple measures per trial. Doing so allows us to treat stimulus as a random variable while correcting for multiple comparisons. Results: Simulations show that the use of Quasi-F statistics with cluster mass tests allows maintaining the family wise error rates close to the nominal alpha level of 0.05. Comparison with existing methods: Simulations reveal that the classical ANOVA/F1 approach has an alarming FWER, demonstrating the superiority of models that treat both participant and stimulus as random variables, like the Quasi-F approach. Conclusions: Our simulations question the validity of studies in which stimulus is not treated as a random variable. Failure to change the current standards feeds the replicability crisis.