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Pesaran, Bijan, Vinck, Martin, Einevoll, Gaute T., Sirota, Anton ORCID logoORCID: https://orcid.org/0000-0002-4700-6587, Fries, Pascal, Siegel, Markus, Truccolo, Wilson, Schroeder, Charles E. and Srinivasan, Ramesh (May 2018): Investigating large-scale brain dynamics using field potential recordings: Analysis and interpretation. In: Nature Neuroscience, Vol. 21, No. 7: pp. 903-919 [PDF, 363kB]


New technologies to record electrical activity from the brain on a massive scale offer tremendous opportunities for discovery. Electrical measurements of large-scale brain dynamics, termed field potentials, are especially important to understanding and treating the human brain. Here, our goal is to provide best practices on how field potential recordings (EEG, MEG, ECoG and LFP) can be analyzed to identify large-scale brain dynamics, and to highlight critical issues and limitations of interpretation in current work. We focus our discussion of analyses around the broad themes of activation, correlation, communication and coding. We provide best-practice recommendations for the analyses and interpretations using a forward model and an inverse model. The forward model describes how field potentials are generated by the activity of populations of neurons. The inverse model describes how to infer the activity of populations of neurons from field potential recordings. A recurring theme is the challenge of understanding how field potentials reflect neuronal population activity given the complexity of the underlying brain systems.

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