TY - JOUR
T1 - Recording and analysis techniques for high-frequency oscillations
AU - Worrell, G. A.
AU - Jerbi, K.
AU - Kobayashi, K.
AU - Lina, J. M.
AU - Zelmann, R.
AU - Le Van Quyen, M.
N1 - Funding Information:
Because of the relatively limited number of centers performing epilepsy surgery, many researchers do not have access to adequate iEEG data sets required to address research questions. Similarly, because of the long time scales over which most animal models of epileptogenesis develop spontaneous seizures, weeks to months, it has not been the practice of researchers to store continuous EEG from these animals over the time course of epileptogenesis. However, it is clear that this is the kind of data (continuous wide-bandwidth electrophysiology from multiple epilepsy models and humans) required for research. Recently, there has been significant interest in development of shared databases and open source toolboxes. The Freiburg Seizure Prediction database ( https://epilepsy.uni-freiburg.de/freiburg-seizure-prediction-project/eeg-database ) is an excellent resource of human iEEG data from 21 patients, and has been used in multiple publications. There are now two large electrophysiology database projects, one funded by the European Union ( http://www.epilepsiae.eu/project_outputs/european_database_on_epilepsy ) and one funded by NIH to make human and animal electrophysology available ( http://ieeg.org ).
PY - 2012/9
Y1 - 2012/9
N2 - 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.
AB - 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.
KW - Human partial epilepsy
KW - Intracranial electrodes
KW - Microelectrodes
KW - Quantitative analysis
KW - Wide bandwidth acquisition
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U2 - 10.1016/j.pneurobio.2012.02.006
DO - 10.1016/j.pneurobio.2012.02.006
M3 - Review article
C2 - 22420981
AN - SCOPUS:84865380186
SN - 0301-0082
VL - 98
SP - 265
EP - 278
JO - Progress in Neurobiology
JF - Progress in Neurobiology
IS - 3
ER -