A look at the global shift to open science, exploring how transparency, preregistration, and open data are becoming the new standard for credible research, benefiting scientists, funders and society.
Conducting systematic literature reviews is traditionally a laborious, manual process involving the extraction of distinct data points from hundreds of academic papers, but this presentation introduces a structured, multi-tool workflow using the …
`4authors-year-doi-url` is a CSL style designed to be as compact as possible while retaining the three most critical pieces of information for a reference: who (authors), when (year), and where to find it (DOI/URL).
The burgeoning field of third language (L3) acquisition has increasingly focused on intermediate stages of language development, aiming to establish the groundwork for comprehensive models of L3 learning that encompass the entire developmental …
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.
To err is human, but when it comes to creating research materials, mistakes can be reduced by sharing more of our work and by using some helpful tools. For instance, we can make our research materials FAIRer—that is, more Findable, Accessible, …
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.
I would like to ask for advice regarding a custom plugin for a serial reaction time task, that was created by @vekteo, and is available in Gorilla, where the code can be edited and tested. By default, trials are self-paced, but I would need them to time out after 2,000 ms. I am struggling to achieve this, and would be very grateful if someone could please advise me a bit.
An Excel workbook template with conditional formatting to facilitate planning, registration, and tracking of sessions in longitudinal studies involving multiple session conductors.
The best argument to motivate a preregistration may be that it doesn’t take any extra time. It just requires frontloading an important portion of the work. As a reward, the paper will receive greater trust from the reviewers and the readers at large. Preregistration is not perfect, but is a lesser evil that reduces the misuse of statistical analysis in science.
In the fast-paced world of scientific research, establishing minimum standards for the creation of research materials is essential. Whether it's stimuli, custom software for data collection, or scripts for statistical analysis, the quality and transparency of these materials significantly impact the reproducibility and credibility of research. This blog post explores the importance of adhering to FAIR (Findable, Accessible, Interoperable, Reusable) principles, and offers practical examples for researchers, with a focus on the cognitive sciences.
The result shows a varying delay of around 2 seconds on average. It would be very helpful for us if we could cut down this delay, as it adds up. To try to achieve this, I reduced the number of variables logged, from the default 363 to 34 important variables. Unfortunately, this change did not result in a reduction of the delay.
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.
Solution for randomly intermixing stimuli from two different loops in OpenSesame by distributing sentence words across columns and using conditional Run if statements to control presentation.
Implementation using position indices in a for-of loop to simultaneously sample from two variables in jsPsych, enabling parallel presentation of prime and target words with synchronized trial indexing.
Python inline script for OpenSesame that automatically loads participant-specific parameters from a CSV file, enabling complex counterbalancing schemes beyond the standard interface options.