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  Investigating large-scale brain dynamics using field potential recordings: analysis and interpretation

Pesaran, B., Vinck, M., Einevoll, G. T., Sirota, A., Fries, P., Siegel, M., et al. (2018). Investigating large-scale brain dynamics using field potential recordings: analysis and interpretation. Nature Neuroscience, 21(7), 903-919. doi:10.1038/s41593-018-0171-8.

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Pesaran_2018_InvestigatingLarge-scale.pdf (Publisher version), 3MB
 
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2018
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 Creators:
Pesaran, Bijan, Author
Vinck, Martin1, 2, Author                 
Einevoll, Gaute T., Author
Sirota, Anton, Author
Fries, Pascal1, 3, Author                 
Siegel, Markus, Author
Truccolo, Wilson, Author
Schroeder, Charles E., Author
Srinivasan, Ramesh, Author
Affiliations:
1Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Max Planck Society, Deutschordenstr. 46, 60528 Frankfurt, DE, ou_2074314              
2Vinck Lab, Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Max Planck Society, Deutschordenstraße 46, 60528 Frankfurt, DE, ou_3381242              
3Fries Lab, Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Max Planck Society, Deutschordenstraße 46, 60528 Frankfurt, DE, ou_3381216              

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Free keywords: Action Potentials/*physiology Animals Brain/*physiology Electroencephalography/*methods Humans Nerve Net/*physiology Neurons/*physiology
 Abstract: 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 (electroencephalograms, magnetoencephalograms, electrocorticograms and local field potentials) 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 recommendations for interpreting the data using forward and inverse models. 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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 Dates: 2016-12-012018-05-012018-06-252018
 Publication Status: Issued
 Pages: -
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 Rev. Type: Peer
 Identifiers: DOI: 10.1038/s41593-018-0171-8
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Title: Nature Neuroscience
  Other : Nat. Neurosci.
Source Genre: Journal
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Publ. Info: New York, NY : Nature America Inc.
Pages: - Volume / Issue: 21 (7) Sequence Number: - Start / End Page: 903 - 919 Identifier: ISSN: 1097-6256
CoNE: https://pure.mpg.de/cone/journals/resource/954925610931