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 …
Reducing the impedance in electroencephalography (EEG) is crucial for capturing high-quality brain activity signals. This process involves ensuring that electrodes make optimal contact with the skin without harming the participant. Below are a few tips to achieve this using a blunt needle, electrolyte gel and gentle wiggling.
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 …
Say, you need to set up a makeshift EEG lab in an office? Easy-peasy---only, try to move the hardware as little as possible, especially laptops with dongles sticking out. The rest is a trail of snapshots devoid of captions, a sink, a shower room and other paraphernalia, as this is only an ancillary, temporary, extraordinary little lab, and all those staples are within reach in our mainstream lab (see Ledwidge et al., 2018; Luck, 2014).
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.
We are seeking to appoint a part-time research assistant to help us recruit participants and conduct an experiment. In the current project, led by Jorge González Alonso and funded by the Research Council of Norway, we investigate language learning and the neurophysiological basis of multilingualism. To this end, we are conducting an electroencephalography (EEG) experiment.
Your work as a research assistant will be mentored and supervised primarily by Pablo Bernabeu, and secondarily by the head of our project and the directors of our lab.
Ved å delta i vårt eksperiment og gjøre noen enkle oppgaver på en datamaskin, kan du bidra til forskning og tjene 250 kr i timen (gavekort). EEG er helt smertefritt.
Eksperimentet foregår i Tromsø, ved UiT Norges Arktiske Universitet.
Vi ser etter deltakere med følgende egenskaper:
☑ Alder 18–45 år;
☑ Snakker norsk som førstespråk og engelsk flytende. Utenom disse språkene, kan deltakerne også snakke svensk og dansk, men ikke andre språk (utover noen få ord);
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?
I'm sending the triggers in a binary format because Python requires this. For instance, to send the trigger 1, I run the code serialport.write(b'1'). I have succeeded in sending triggers in this way. However, I encounter two problems. First, the triggers are converted in a way I cannot entirely decipher. For instance, when I run the code serialport.write(b'1'), the trigger displayed in BrainVision Recorder is S 49, not S 1 as I would hope (please see Appendix below). Second, I cannot send two triggers with the same code one after the other. For instance, if I run serialport.write(b'1'), a trigger appears in BrainVision Recorder, but if I run the same afterwards (no matter how many times), no trigger appears. I tried to solve these problems by opening the parallel port in addition to the serial port, but the problems persist.
Event-related potentials (ERPs) offer a unique insight in the study of human cognition. Let's look at their reason-to-be for the purposes of research, and how they are defined and processed. Most of this content is based on my master's thesis, which I could fortunately conduct at the Max Planck Institute for Psycholinguistics (see thesis or conference paper).
Electroencephalography The brain produces electrical activity all the time, which can be measured via electrodes on the scalp—a method known as electroencephalography (EEG).
The engagement of sensory brain regions during word recognition is widely documented, yet its precise relevance is less clear. It would constitute perceptual simulation only if it has a functional role in conceptual processing. We investigated this …
Most of the recordings are perfectly fine, but a few present a big error. Out of 64 original electrodes, only two appear. These are the right mastoid (RM) and the left eye sensor (LEOG). Both are bipolar electrodes. RM is to be re-referenced to the online reference electrode, while LEOG is to be re-referenced to the right eye electrode.