Methods

The human brain comprises billions of neurons, small nerve cells that communicate with each other through weak electromagnetic signals. These signals vary depending on what we see, hear, or do, as different brain regions interact to process information. An electroencephalogram (EEG) is a non-invasive technique that detects these electrical signals using small electrodes placed on the scalp. By recording changes in the signals over time, the EEG helps identify when and where brain activity occurs. The data collected is then analysed with computer software and linked to observed behaviours or sensory stimuli.
The EEG is the ideal tool for our investigations. It provides excellent temporal resolution and is sensitive to subtle changes in neural activity, even those that may not be overtly reflected in behaviour. In our studies, we specifically measure event-related potentials (ERPs), which are specific changes in the EEG signal triggered by particular stimuli or events.

FaceReader is a software tool for the automated analysis of facial expressions. Using video recordings, the software detects and analyses changes in facial movements, making it possible to track emotional responses over time.

In our studies, we use FaceReader specifically to identify a particular facial movement associated with the so-called Duchenne smile (also known as a genuine or joyful smile). This allows us to investigate when and to what extent this response occurs during our experiments.