5.13: Key Takeaways and References
-
- Last updated
- Save as PDF
Key Takeaways
- Voltage is the potential for charges to flow from one location (the so-called active site) to another location (the so-called reference site). There is no such thing as the voltage at a single electrode site.
- When you’re looking at data from a channel that is labeled with the so-called active electrode site for that channel (e.g., Pz), the waveforms are impacted equally by activity the so-called active and so-called reference sites. If you don’t know what the reference was, you really don’t know what you’re looking at. You should always find out what reference was used before you spend time looking at ERP waveforms
- There is no “correct” reference location. No matter what you use, the data are impacted equally by the so-called reference and so-called active electrodes.
- The “best” reference is usually whatever is common in your subarea (because using the same reference facilitates comparisons across studies).
- To avoid falling into the trap of thinking that the waveform from a given channel is primarily a result of the so-called active electrode for that channel, it can be helpful to look at your data with multiple different reference sites. For this purpose, it is usually sufficient to re-reference the grand average ERPs.
- It is simple to re-reference data offline. In many cases, you can make one of your channels (or the average of a set of channels) the reference by simply subtracting it from the other channels (assuming that they all started with the same reference).
- You can avoid the reference issue altogether by converting your voltage waveforms into current density or global field power.
References
Dien, J. (1998). Issues in the application of the average reference: Review, critiques, and recommendations. Behavior Research Methods, Instruments & Computers , 30 , 34–43.
Dong, L., Li, F., Liu, Q., Wen, X., Lai, Y., Xu, P., & Yao, D. (2017). MATLAB Toolboxes for Reference Electrode Standardization Technique (REST) of Scalp EEG. Frontiers in Neuroscience , 11 . https://doi.org/10.3389/fnins.2017.00601
Files, B. T., Lawhern, V. J., Ries, A. J., & Marathe, A. R. (2016). A Permutation Test for Unbalanced Paired Comparisons of Global Field Power. Brain Topography , 29 , 345–357. https://doi.org/10.1007/s10548-016-0477-3
Hamburger, H. L., & Van der Burgt, M. A. G. (1991). Global Field Power measurement versus classical method in the determination of the latency of evoked potential components. Brain Topography , 3 (3), 391–396. https://doi.org/10.1007/BF01129642
Kappenman, E. S., Farrens, J. L., Zhang, W., Stewart, A. X., & Luck, S. J. (2021). ERP CORE: An Open Resource for Human Event-Related Potential Research. NeuroImage , 225 , 117465. https://doi.org/10.1016/j.neuroimage.2020.117465
Luck, S. J. (2014). An Introduction to the Event-Related Potential Technique, Second Edition . MIT Press.
Nunez, P. L. (1981). Electric Fields of the Brain . Oxford University Press.
Rossion, B., & Jacques, C. (2012). The N170: Understanding the time course of face perception in the human brain. In S. J. Luck & E. S. Kappenman (Eds.), The Oxford Handbook of Event-Related Potential Components (pp. 115–141). Oxford University Press.
Skrandies, W. (1989). Data reduction of multichannel fields: Global field power and Principal Component Analysis. Brain Topography , 2 (1), 73–80. https://doi.org/10.1007/BF01128845
Yao, D. (2017). Is the Surface Potential Integral of a Dipole in a Volume Conductor Always Zero? A Cloud Over the Average Reference of EEG and ERP. Brain Topography , 30 (2), 161–171. https://doi.org/10.1007/s10548-016-0543-x