Mental simulation theories of language comprehension propose that people automatically create mental representations of objects mentioned in sentences. Mental representation is often measured with the sentence-picture verification task, wherein …
Unlike children acquiring their first language (L1), L2/Ln learners can draw on existing grammatical knowledge to ease the task, at least for those properties where the grammars align. This means that, in addition to statistical learning, there might …
The acquisition of a third language (L3) often involves the transfer of morphosyntactic structures from the first language and/or the second language to the developing L3 grammar, allowing the recycling of previously acquired knowledge (Rothman et …
Electroencephalography (EEG) has become a cornerstone for understanding the intricate workings of the human brain in the field of neuroscience. However, EEG software and hardware come with their own set of constraints, particularly in the management of markers, also known as triggers. This article aims to shed light on these limitations and future prospects of marker management in EEG studies, while also introducing R functions that can help deal with vmrk files from BrainVision.
Electroencephalographic (EEG) signals are often contaminated by muscle artifacts such as blinks, jaw clenching and (of course) yawns, which generate electrical activity that can obscure the brain signals of interest. These artifacts typically manifest as large, abrupt changes in the EEG signal, complicating data interpretation and analysis. To mitigate these issues, participants can be instructed during the preparatory phase of the session to minimize blinking and to keep their facial muscles relaxed. Additionally, researchers can emphasize the importance of staying still and provide practice sessions to help participants become aware of their movements, thereby reducing the likelihood of muscle artifacts affecting the EEG recordings.
The OpenSesame user base is skyrocketing but—of course—remains small in comparison to many other user bases that we are used to. Therefore, when developing an experiment in OpenSesame, there are still many opportunities to break the mould. When you need to do something beyond the standard operating procedure, it may take longer to find suitable resources than it takes when a more widespread tool is used. So, why would you still want to use OpenSesame?
Critical examination of Liu et al. (2018) claims about methodological inconsistencies in ERP studies of conceptual modality switching, arguing that their conclusions overlook theoretical and methodological justifications for varying analytical approaches.
Overview of event-related potentials as a research method, covering electroencephalography fundamentals, ERP definitions and processing, and their application to studying the time course of cognitive processes like conceptual processing.
We tested whether conceptual processing is modality-specific by tracking the time course of the Conceptual Modality Switch effect. Forty-six participants verified the relation between property words and concept words. The conceptual modality of …
Event-related potential experiment investigating conceptual modality switching, finding early-onset negativity effects (160-750 ms) that increase over time, suggesting sensory regions have a functional role in conceptual processing and supporting the compatibility of distributional and embodied processing.