Analysis of dynamic brain oscillations: methodological advances.
In recent years, new recording technologies have advanced such that, at high temporal and spatial resolutions, oscillations of neuronal networks can be identified from simultaneous, multisite recordings. However, because of the deluge of multichannel data generated by these experiments, achieving the full potential of parallel neuronal recordings also depends on the development of new mathematical methods that can extract meaningful information relating to time, frequency and space. Here, we aim to bridge this gap by focusing on up-to-date recording techniques for measurement of network oscillations and new analysis tools for their quantitative assessment. In particular, we emphasize how these methods can be applied, what property might be inferred from neuronal signals and potentially productive future directions. This review is part of the INMED and TINS special issue, Physiogenic and pathogenic oscillations: the beauty and the beast, derived from presentations at the annual INMED and TINS symposium (http://inmednet.com).
Le Van Quyen
Michel
M
LENA-CNRS UPR640, Université Pierre et Marie Curie, Hôpital de la Salpêtrière, 75651 Paris Cedex 13, France. lenalm@ext.jussieu.fr
Bragin
Anatol
A
D000818:Animals; D001683:Biological Clocks / Q000502:physiology*; D001921:Brain / Q000166:cytology / Q000502:physiology*; D001931:Brain Mapping; D001330:Electronic Data Processing; D006801:Humans; D009415:Nerve Net / Q000502:physiology*; D009474:Neurons / Q000502:physiology; D013057:Spectrum Analysis