You can check this by visualizing the returned results in the software where you run your analysis, after altering corresponding preprocessing steps or parameters. Most certainly, you will find valuable advice in scientific research papers or even in the “lab traditions” of your team.īy making sure that the methods of choice return the desired outcomes, you are able to maximize scientific research standards such as objectivity, reliability, and validity. The phrase “making informed decisions” is the key – if you are hesitant about which methods to choose, check out well cited existing literature. All signal processing techniques alter the data to some extent and being aware of their impact on the data definitely helps to pick the right ones. Low impedance values imply high recording quality (low impedances indicate that the recorded signal reflects the processes inside of the head rather than artifactual processes from the surroundings).Ĭlean data allows clean responses to your research questions! 3) Make informed decisionsĮEG data can be recorded and analyzed in a lot of different ways, and not only the processing steps themselves but also their sequence matters (One example of the significance of pre-processing steps’ sequence is described in Bigdely-Shamlo et al., 2015). Therefore, always start with properly recorded data.ĮEG systems generally offer soft- or hardware-based quality indicators such as impedance panels where the impedance of each electrode is visualized graphically. To this day, there is no algorithm that is able to decontaminate poorly recorded data, and you simply cannot clean up or process data in a way that magically alters the signal. Steve Luck (UC Irvine) that you should keep in mind whenever you record and pre-process EEG data in order to extract metrics of interest. 2) “There is no substitute for clean data” Once you have crossed those questions off your list, you are all set to start with the actual data collection and analysis. Do participants understand the instructions?.Are the stimuli presented in the right order?.You certainly do not want your EEG experiment to fail mid-test, so before carrying out a full study with 100 participants start small and run some pilot sessions in order to check if everything is working properly. You need to prepare the participants, spend some time on setting up the equipment and run initial tests. 2) “There is no substitute for clean data”ĮEG experiments require careful preparation.
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