Welcome to the GlascherLab Wiki!

This Wiki provides detailed information about using experimental equipment, running experiments, organizing project folders and other useful stuff in the GlascherLab.

Please use the links below to access the different sections in a logical order or the side cars on the right for direct access to individual pages.

New Lab Members

A new work environment aways has a lot of new organizational issues and procedures in place that you are not aware of yet. This section provides some information on how to get started with your work in the lab. This information provided here is a supplement to the institute's (ISN) wiki found here

• First Steps
• Setting up your workspace

Participant Recruitment

Over the years, we have developed some procedures for recruiting study participants for behavioral, EEG, and fMRI studies. The recommendations partially overlap with the general rules for ISN.

• General procedure and tips

Project organization

A big part of a research projects pertains to preprocessing and analyzing data. In order to make this efficient and to also document the workflow of a project (i.e. the provenance), you can find some recommendations and tips below.

0. Project location and backup policy
1. Creating a project folder
2. Journaling a project with DataLad
3. Organizing folder and files with BIDS
4. Mirroring a project to GIN
5. Using computational notebooks
6. Backup of a project

EEG

Preparing and measuring EEG

1. EEG hardware and setup
2. Preparing an EEG measurement
3. Running an experiment / Lab Streaming layer
4. Post-experimental procedures

Analyzing EEG data

1. EEG Preprocessing
2. ERPs
3. Time-Frequency analyses
4. model-based EEG analyses
5. Hyperscanning analyses

Running online behavioral experiments

Single-player experiments

Multi-player experiments

Gathering online behavioral data requires the following 3 steps:

1. Coding interactive experiments using oTree / HTML / Javascript

Infrastructure for hosting experiments and subject recruitment

1. Using Prolific for recruitment/payment of online participants
2. Hosting the experiment on Heroku and creating a database for the experimental data
3. hosting an experiment on Pavlovia

Eye-Tracking

1. Setting up the Pupil Lab eye-trackers
2. screen-based tracking
3. social interactive eye-tracking

Dyadic Interaction Platform (DIP)

DIP is an integrated system designed for interactive experiments. The system—often referred to as DIPc—combines multiple hardware components such as ultra-short throw projectors, interactive touch panels, cameras, and head-mounted eye trackers with custom software tools. This setup is particularly optimized for research and educational experiments, especially those involving child–child and adult–child social interactions. It is also used for animal monkey-to-monkey or human-monkey experiments. The DIP environment leverages both specialized hardware and software (including frameworks like Psychopy) to deliver synchronized, high-quality projections and interactive experiences.

DIP projector alignment

Computational Modeling

A very accessible and rather concise description of the workflow of a cognitive modeling study can be found in the Wilson & Collins 10 rules paper. Below you find some specific information about the different steps and some hints and solutions to common problems.

1. Model estimation
2. Model comparison / Model selection
3. Parameter and model recovery
4. Posterior predictive check