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Is sensor space analysis good enough? Spatial patterns as a tool for assessing spatial mixing of EEG/MEG rhythms - ScienceDirect
Source: gfbic253cb3a601b84ef2s0b6bw0c9n6ux6w9ufiac.eds.tju.edu.cn
Article summary:
1. This article examines the implications of volume conduction on sensor space analysis of EEG/MEG recordings.
2. It illustrates how different types of activity overlap on the level of individual sensors, and shows spatial mixing in the context of alpha rhythms.
3. The article outlines specific consequences of signal mixing for frequently used assessments such as power, power ratios and connectivity profiles in basic research and neurofeedback applications.
Article analysis:
The article is generally reliable and trustworthy, as it provides a comprehensive overview of the implications of volume conduction on sensor space analysis of EEG/MEG recordings. The authors provide evidence to support their claims, such as simulations with a realistic 3D head model and lead field, and data analysis from a large resting-state EEG dataset. Additionally, they provide practical illustrations to help readers evaluate whether sensor space is an appropriate choice for their topic of investigation.
The article does not appear to be biased or one-sided in its reporting; it presents both sides equally by outlining both the advantages and disadvantages of sensor space analysis. Furthermore, there are no unsupported claims or missing points of consideration; all claims are backed up by evidence from simulations or data analysis. There are also no unexplored counterarguments or promotional content present in the article.
The only potential issue with this article is that it does not mention any possible risks associated with sensor space analysis; however, this is likely due to the fact that this was not the focus of the paper.