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Response conflicts play a prominent role in the flexible adaptation of behavior as they represent context-signals that indicate the necessity for the recruitment of cognitive control. Previous studies have highlighted the functional roles of the affectively aversive and arousing quality of the conflict signal in triggering the adaptation process. To further test this potential link with arousal, participants performed a response conflict task in two separate sessions with either transcutaneous vagus nerve stimulation (tVNS), which is assumed to activate the locus coeruleus-noradrenaline (LC-NE) system, or with neutral sham stimulation. In both sessions the N2 and P3 event-related potentials (ERP) were assessed. In line with previous findings, conflict interference, the N2 and P3 amplitude were reduced after conflict. Most importantly, this adaptation to conflict was enhanced under tVNS compared to sham stimulation for conflict interference and the N2 amplitude. No effect of tVNS on the P3 component was found. These findings suggest that tVNS increases behavioral and electrophysiological markers of adaptation to conflict. Results are discussed in the context of the potentially underlying LC-NE and other neuromodulatory (e.g., GABA) systems. The present findings add important pieces to the understanding of the neurophysiological mechanisms of conflict-triggered adjustment of cognitive control.
Language processing requires memory retrieval to integrate current input with previous context and making predictions about upcoming input. We propose that prediction and retrieval are two sides of the same coin, i.e. functionally the same, as they both activate memory representations. Under this assumption, memory retrieval and prediction should interact: Retrieval interference can only occur at a word that triggers retrieval and a fully predicted word would not do that. The present study investigated the proposed interaction with event-related potentials (ERPs) during the processing of sentence pairs in German. Predictability was measured via cloze probability. Memory retrieval was manipulated via the position of a distractor inducing proactive or retroactive similarity-based interference. Linear mixed model analyses provided evidence for the hypothesised interaction in a broadly distributed negativity, which we discuss in relation to the interference ERP literature. Our finding supports the proposal that memory retrieval and prediction are functionally the same.
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.
Language can strongly influence the emotional state of the recipient. In contrast to the broad body of experimental and neuroscientific research on semantic information and prosodic speech, the emotional impact of grammatical structure has rarely been investigated. One reason for this might be, that measuring effects of syntactic structure involves the use of complex stimuli, for which the emotional impact of grammar is difficult to isolate. In the present experiment we examined the emotional impact of structural parallelisms, that is, repetitions of syntactic features, on the emotion-sensitive "late positive potential" (LPP) with a cross-modal priming paradigm. Primes were auditory presented nonsense sentences which included grammatical-syntactic parallelisms. Visual targets were positive, neutral, and negative faces, to be classified as emotional or non-emotional by the participants. Electrophysiology revealed diminished LPP amplitudes for positive faces following parallel primes. Thus, our findings suggest that grammatical structure creates an emotional context that facilitates processing of positive emotional information.
A large body of research now supports the presence of both syntactic and lexical predictions in sentence processing. Lexical predictions, in particular, are considered to indicate a deep level of predictive processing that extends past the structural features of a necessary word (e.g. noun), right down to the phonological features of the lexical identity of a specific word (e.g. /kite/; DeLong et al., 2005). However, evidence for lexical predictions typically focuses on predictions in very local environments, such as the adjacent word or words (DeLong et al., 2005; Van Berkum et al., 2005; Wicha et al., 2004). Predictions in such local environments may be indistinguishable from lexical priming, which is transient and uncontrolled, and as such may prime lexical items that are not compatible with the context (e.g. Kukona et al., 2014). Predictive processing has been argued to be a controlled process, with top-down information guiding preactivation of plausible upcoming lexical items (Kuperberg & Jaeger, 2016). One way to distinguish lexical priming from prediction is to demonstrate that preactivated lexical content can be maintained over longer distances.
In this dissertation, separable German particle verbs are used to demonstrate that preactivation of lexical items can be maintained over multi-word distances. A self-paced reading time and an eye tracking experiment provide some support for the idea that particle preactivation triggered by a verb and its context can be observed by holding the sentence context constant and manipulating the predictabilty of the particle. Although evidence of an effect of particle predictability was only seen in eye tracking, this is consistent with previous evidence suggesting that predictive processing facilitates only some eye tracking measures to which the self-paced reading modality may not be sensitive (Staub, 2015; Rayner1998). Interestingly, manipulating the distance between the verb and the particle did not affect reading times, suggesting that the surprisal-predicted faster reading times at long distance may only occur when the additional distance is created by information that adds information about the lexical identity of a distant element (Levy, 2008; Grodner & Gibson, 2005). Furthermore, the results provide support for models proposing that temporal decay is not major influence on word processing (Lewandowsky et al., 2009; Vasishth et al., 2019).
In the third and fourth experiments, event-related potentials were used as a method for detecting specific lexical predictions. In the initial ERP experiment, we found some support for the presence of lexical predictions when the sentence context constrained the number of plausible particles to a single particle. This was suggested by a frontal post-N400 positivity (PNP) that was elicited when a lexical prediction had been violated, but not to violations when more than one particle had been plausible. The results of this study were highly consistent with previous research suggesting that the PNP might be a much sought-after ERP marker of prediction failure (DeLong et al., 2011; DeLong et al., 2014; Van Petten & Luka, 2012; Thornhill & Van Petten, 2012; Kuperberg et al., 2019). However, a second experiment in a larger sample experiment failed to replicate the effect, but did suggest the relationship of the PNP to predictive processing may not yet be fully understood. Evidence for long-distance lexical predictions was inconclusive.
The conclusion drawn from the four experiments is that preactivation of the lexical entries of plausible upcoming particles did occur and was maintained over long distances. The facilitatory effect of this preactivation at the particle site therefore did not appear to be the result of transient lexical priming. However, the question of whether this preactivation can also lead to lexical predictions of a specific particle remains unanswered. Of particular interest to future research on predictive processing is further characterisation of the PNP. Implications for models of sentence processing may be the inclusion of long-distance lexical predictions, or the possibility that preactivation of lexical material can facilitate reading times and ERP amplitude without commitment to a specific lexical item.
Comprehension of transitive sentences relies on different kinds of information, like word order, case marking, and animacy contrasts between arguments. When no formal cues like case marking or number congruency are available, a contrast in animacy helps the parser to decide which argument is the grammatical subject and which the object. Processing costs are enhanced when neither formal cues nor animacy contrasts are available in a transitive sentence. We present an ERP study on the comprehension of grammatical transitive German sentences, manipulating animacy contrasts between subjects and objects as well as the verbal case marking pattern. Our study shows strong object animacy effects even in the absence of violations, and in addition suggests that this effect of object animacy is modulated by the verbal case marking pattern.
Neural signatures of temporal regularity and recurring patterns in random tonal sound sequences
(2021)
The auditory system is highly sensitive to recurring patterns in the acoustic input - even in otherwise unstructured material, such as white noise or random tonal sequences. Electroencephalography (EEG) research revealed a characteristic negative potential to periodically recurring auditory patterns - a response, which has been interpreted as memory trace-related and specific, rather than as a sign of periodicity-driven entrainment. Here, we aim to disentangle these two possible contributions by investigating the influence of a periodic sound sequence's inherent temporal regularity on event-related potentials. Participants were presented continuous sequences of short tones of random pitch, with some sequences containing a recurring pattern, and asked to indicate whether they heard a repetition. Patterns were either spaced equally across the random sequence (isochronous condition) or with a temporal jitter (jittered condition), which enabled us to differentiate between event-related potentials (and thus processing operations associated with a memory trace for a repeated pattern) and the periodic nature of the repetitions. A negative recurrence-related component could be observed independently of temporal regularity, was pattern-specific, and modulated by across trial repetition of the pattern. Critically, isochronous pattern repetition induced an additional early periodicity-related positive component, which started to build up already before the pattern onset and which was elicited undampedly even when the repeated pattern was occasionally not presented. This positive component likely reflects a sensory driven entrainment process that could be the foundation of a behavioural benefit in detecting temporally regular repetitions.
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.