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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.
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.
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.
While Information Systems Research exists at the individual and workgroup levels, research on IS at the enterprise level is less common. The potential synergies between the study of enterprise systems (ES) and related fields have been underexplored and often treated as separate entities. The ongoing challenge is to seamlessly integrate technological advances and align business processes across organizations. While systems integration within an organization is common, changes occur when industry and ecosystem perspectives come into play. The four selected papers address different facets of the future role of enterprise ecosystems, including implementation challenges, ecosystem boundaries, and B2B platform specifics.
Future ERP Systems
(2021)
This paper presents a research agenda on the current generation of ERP systems which was developed based on a literature review on current problems of ERP systems. The problems are presented following the ERP life cycle. In the next step, the identified problems are mapped on a reference architecture model of ERP systems that is an extension of the three-tier architecture model that is widely used in practice. The research agenda is structured according to the reference architecture model and addresses the problems identified regarding data, infrastructure, adaptation, processes, and user interface layer.