ELAN: A Software Package for Analysis and Visualization of MEG, EEG, and LFP Signals

被引:114
|
作者
Aguera, Pierre-Emmanuel [1 ,2 ]
Jerbi, Karim [1 ,2 ]
Caclin, Anne [1 ,2 ]
Bertrand, Olivier [1 ,2 ]
机构
[1] Ctr Hosp Le Vinatier, Lyon Neurosci Res Ctr, CNRS, INSERM,Brain Dynam & Cognit Team,UMR5292,U1028, F-69500 Bron, France
[2] Univ Lyon 1, F-69000 Lyon, France
关键词
SYNCHRONY; RESPONSES; AREAS; HZ;
D O I
10.1155/2011/158970
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
The recent surge in computational power has led to extensive methodological developments and advanced signal processing techniques that play a pivotal role in neuroscience. In particular, the field of brain signal analysis has witnessed a strong trend towards multidimensional analysis of large data sets, for example, single-trial time-frequency analysis of high spatiotemporal resolution recordings. Here, we describe the freely available ELAN software package which provides a wide range of signal analysis tools for electrophysiological data including scalp electroencephalography (EEG), magnetoencephalography (MEG), intracranial EEG, and local field potentials (LFPs). The ELAN toolbox is based on 25 years of methodological developments at the Brain Dynamics and Cognition Laboratory in Lyon and was used in many papers including the very first studies of time-frequency analysis of EEG data exploring evoked and induced oscillatory activities in humans. This paper provides an overview of the concepts and functionalities of ELAN, highlights its specificities, and describes its complementarity and interoperability with other toolboxes.
引用
收藏
页数:11
相关论文
共 50 条
  • [1] Software package for visualization and analysis of biomedical and physical signals
    Dziuda, Lukasz
    Rozanowski, Krzysztof
    Krej, Mariusz
    Skibniewski, Franciszek
    [J]. EUROCON 2007: THE INTERNATIONAL CONFERENCE ON COMPUTER AS A TOOL, VOLS 1-6, 2007, : 1714 - 1719
  • [2] High-Throughput Analysis of in-vitro LFP Electrophysiological Signals: A validated workflow/software package
    Tsakanikas, P.
    Sigalas, C.
    Rigas, P.
    Skaliora, I.
    [J]. SCIENTIFIC REPORTS, 2017, 7
  • [3] High-Throughput Analysis of in-vitro LFP Electrophysiological Signals: A validated workflow/software package
    P. Tsakanikas
    C. Sigalas
    P. Rigas
    I. Skaliora
    [J]. Scientific Reports, 7
  • [4] Multimodal Modeling of Neural Network Activity: Computing LFP, ECoG, EEG, and MEG Signals With LFPy 2.0
    Hagen, Espen
    Naess, Solveig
    Ness, Torbjorn, V
    Einevoll, Gaute T.
    [J]. FRONTIERS IN NEUROINFORMATICS, 2018, 12
  • [5] CORSA - A SOFTWARE PACKAGE FOR RESPIRATORY SIGNALS ANALYSIS
    ROMANO, S
    MAZZOLA, S
    SANCI, S
    [J]. BULLETIN EUROPEEN DE PHYSIOPATHOLOGIE RESPIRATOIRE-CLINICAL RESPIRATORY PHYSIOLOGY, 1987, 23 : S417 - S417
  • [6] Editorial: From Raw MEG/EEG to Publication: How to Perform MEG/EEG Group Analysis With Free Academic Software
    Delorme, Arnaud
    Oostenveld, Robert
    Tadel, Francois
    Gramfort, Alexandre
    Nagarajan, Srikantan
    Litvak, Vladimir
    [J]. FRONTIERS IN NEUROSCIENCE, 2022, 16
  • [7] Comparison of wavelet transform and matching pursuit in the analysis of EEG and MEG signals
    Gratkowski, M.
    Haueisen, J.
    Sehack, B.
    Arendt-Nielsen, L.
    Chen, A.
    Zanow, F.
    [J]. Biomedizinische Technik, 2003, 48 (s1): : 186 - 187
  • [8] Classification methods for ongoing EEG and MEG signals
    Besserve, Michel
    Jerbi, Karim
    Laurent, Francois
    Baillet, Sylvain
    Martinerie, Jacques
    Garnero, Line
    [J]. BIOLOGICAL RESEARCH, 2007, 40 (04) : 415 - 437
  • [9] Mean-field based framework for forward modeling of LFP and MEG signals
    Tesler, Federico
    Tort-Colet, Nuria
    Depannemaecker, Damien
    Carlu, Mallory
    Destexhe, Alain
    [J]. FRONTIERS IN COMPUTATIONAL NEUROSCIENCE, 2022, 16
  • [10] Mean-field based framework for forward modeling of LFP and MEG signals
    Tesler, Federico
    Tort-Colet, Núria
    Depannemaecker, Damien
    Carlu, Mallory
    Destexhe, Alain
    [J]. Frontiers in Computational Neuroscience, 2022, 16