title: Recording and analysis techniques for high-frequency oscillations.
abstract: In recent years, new recording technologies have advanced such that, at high temporal and spatial resolutions, high-frequency oscillations (HFO) can be recorded in human partial epilepsy. However, because of the deluge of multichannel data generated by these experiments, achieving the full potential of parallel neuronal recordings depends on the development of new data mining techniques to 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 HFO 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.
authors.affiliation: Mayo Systems Electrophysiology Laboratory, Divisions of Epilepsy and Neurophysiology, Department of Neurology, Mayo Clinic, Rochester, MN, USA.
authors.forename: G A
authors.initials: GA
authors.lastname: Worrell
authors.forename: K
authors.initials: K
authors.lastname: Jerbi
authors.forename: K
authors.initials: K
authors.lastname: Kobayashi
authors.forename: J M
authors.initials: JM
authors.lastname: Lina
authors.forename: R
authors.initials: R
authors.lastname: Zelmann
authors.forename: M
authors.initials: M
authors.lastname: Le Van Quyen
mesh_terms: D000465:Algorithms; D000818:Animals; D001683:Biological Clocks; D001921:Brain / Q000503:physiopathology*; D003936:Diagnosis, Computer-Assisted / Q000379:methods; D004569:Electroencephalography / Q000379:methods*; D004827:Epilepsy / Q000175:diagnosis / Q000503:physiopathology*; D006801:Humans; D015225:Magnetoencephalography / Q000379:methods*; D009991:Oscillometry / Q000379:methods*