Filtern
Dokumenttyp
- Wissenschaftlicher Artikel (9)
- Dissertation (2)
- Postprint (1)
Sprache
- Englisch (12) (entfernen)
Gehört zur Bibliographie
- ja (12) (entfernen)
Schlagworte
- ERP (12) (entfernen)
Institut
- Department Linguistik (12) (entfernen)
The comprehension of figurative language : electrophysiological evidence on the processing of irony
(2008)
This dissertation investigates the comprehension of figurative language, in particular the temporal processing of verbal irony. In six experiments using event-related potentials(ERP) brain activity during the comprehension of ironic utterances in relation to equivalent non-ironic utterances was measured and analyzed. Moreover, the impact of various language-accompanying cues, e.g., prosody or the use of punctuation marks, as well as non-verbal cues such as pragmatic knowledge has been examined with respect to the processing of irony. On the basis of these findings different models on figurative language comprehension, i.e., the 'standard pragmatic model', the 'graded salience hypothesis', and the 'direct access view', are discussed.
While it is widely acknowledged in the formal semantic literature that both the truth-functional focus particle only and it-clefts convey exhaustiveness, the nature and source of exhaustiveness effects with it-clefts remain contested. We describe a questionnaire study (n = 80) and an event-related brain potentials (ERP) study (n = 16) that investigated the violation of exhaustiveness in German only-foci versus it-clefts. The offline study showed that a violation of exhaustivity with only is less acceptable than the violation with it-clefts, suggesting a difference in the nature of exhaustivity interpretation in the two environments. The ERP-results confirm that this difference can be seen in online processing as well: a violation of exhaustiveness in only-foci elicited a centro-posterior positivity (600-800ms), whereas a violation in it-clefts induced a globally distributed N400 pattern (400-600ms). The positivity can be interpreted as a reanalysis process and more generally as a process of context updating. The N400 effect in it-clefts is interpreted as indexing a cancelation process that is functionally distinct from the only case. The ERP study is, to our knowledge, the first evidence from an online experimental paradigm which shows that the violation of exhaustiveness involves different underlying processes in the two structural environments.
The current study examines the neural correlates of 8-to-12-year-old children and adults producing inflected word forms, specifically regular vs. irregular past-tense forms in English, using a silent production paradigm. ERPs were time-locked to a visual cue for silent production of either a regular or irregular past-tense form or a 3rd person singular present tense form of a given verb (e.g., walked/sang vs. walks/sings). Subsequently, another visual stimulus cued participants for an overt vocalization of their response. ERP results for the adult group revealed a negativity 300-450 ms after the silent-production cue for regular compared to irregular past-tense forms. There was no difference in the present form condition. Children's brain potentials revealed developmental changes, with the older children demonstrating more adult-like ERP responses than the younger ones. We interpret the observed ERP responses as reflecting combinatorial processing involved in regular (but not irregular) past-tense formation.
In addition to sensory decline, age-related losses in auditory perception also reflect impairments in attentional modulation of perceptual saliency. Using an attention and intensity-modulated dichotic listening paradigm, we investigated electrophysiological correlates of processing conflicts between attentional focus and perceptual saliency in 25 younger and 26 older adults. Participants were instructed to attend to the right or left ear, and perceptual saliency was manipulated by varying the intensities of both ears. Attentional control demand was higher in conditions when attentional focus and perceptual saliency favored opposing ears than in conditions without such conflicts. Relative to younger adults, older adults modulated their attention less flexibly and were more influenced by perceptual saliency. Our results show, for the first time, that in younger adults a late negativity in the event-related potential (ERP) at fronto-central and parietal electrodes was sensitive to perceptual-attentional conflicts during auditory processing (N450 modulation effect). Crucially, the magnitude of the N450 modulation effect correlated positively with task performance. In line with lower attentional flexibility, the ERP waveforms of older adults showed absence of the late negativity and the modulation effect. This suggests that aging compromises the activation of the frontoparietal attentional network when processing the competing and conflicting auditory information.
In this thesis sentence processing was investigated using a psychophysiological measure known as pupillometry as well as Event-Related Potentials (ERP). The scope of the the- sis was broad, investigating the processing of several different movement constructions with native speakers of English and second language learners of English, as well as word order and case marking in German speaking adults and children. Pupillometry and ERP allowed us to test competing linguistic theories and use novel methodologies to investigate the processing of word order. In doing so we also aimed to establish pupillometry as an effective way to investigate the processing of word order thus broadening the methodological spectrum.
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.
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.