Abstract
In recent years there has been an increase in the number of portable low-cost electroencephalographic (EEG) systems available to researchers. However, to date the validation of the use of low-cost EEG systems has focused on continuous recording of EEG data and/or the replication of large system EEG setups reliant on event-markers to afford examination of event-related brain potentials (ERP). Here, we demonstrate that it is possible to conduct ERP research without being reliant on event markers using a portable MUSE EEG system and a single computer. Specifically, we report the results of two experiments using data collected with the MUSE EEG system—one using the well-known visual oddball paradigm and the other using a standard reward-learning task. Our results demonstrate that we could observe and quantify the N200 and P300 ERP components in the visual oddball task and the reward positivity (the mirror opposite component to the feedback-related negativity) in the reward-learning task. Specifically, single sample t-tests of component existence (all p's < 0.05), computation of Bayesian credible intervals, and 95% confidence intervals all statistically verified the existence of the N200, P300, and reward positivity in all analyses. We provide with this research paper an open source website with all the instructions, methods, and software to replicate our findings and to provide researchers with an easy way to use the MUSE EEG system for ERP research. Importantly, our work highlights that with a single computer and a portable EEG system such as the MUSE one can conduct ERP research with ease thus greatly extending the possible use of the ERP methodology to a variety of novel contexts.
Highlights
In recent years there has been an almost explosive growth of low-cost electroencephalographic (EEG) recording systems
Following the analysis of the MUSE data, the event-related brain potential (ERP) components of interest were quantified in a manner identical to the reduced analysis
Due to the timing lag inherent with the Bluetooth connection, the MUSE grand average difference peak times lagged and were slightly different (N200: 260ms, P300: 381ms, reward positivity: 297 ms) from the reduced analysis peak times
Summary
In recent years there has been an almost explosive growth of low-cost (i.e., less than $500 USD) electroencephalographic (EEG) recording systems. While most of the systems on the market offer software developer kits allowing scientists to access the raw data for research purposes—only a small amount of work has been done to validate the effectiveness of these systems for event-related brain potential (ERP) research (e.g., Debener et al, 2012; Badcock et al, 2013; Duvinage et al, 2013; Gramann et al, 2014; Wascher et al, 2014; Badcock et al, 2015; Maskeliunas et al, 2016; Kuziek et al, 2017). The ERP methodology is difficult to implement in low-cost non-standard research grade equipment for several reasons. Two other key issues that are a cause for concern relate to the issue of experimental timing: first, how one can “mark” the data for subsequent ERP analysis, and second, the issue of non-standard electrode locations for analysis—ERP components are typically associated with analysis of specific electrode locations
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
