• MEG and EEG data analysis with...

Treffer: MEG and EEG data analysis with MNE-Python.

Title:
MEG and EEG data analysis with MNE-Python.
Authors:
Gramfort A; Institut Mines-Telecom, Telecom ParisTech, CNRS LTCI Paris, France ; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, and Harvard Medical School Charlestown MA, USA ; NeuroSpin, CEA Saclay Gif-sur-Yvette, France., Luessi M; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, and Harvard Medical School Charlestown MA, USA., Larson E; Institute for Learning and Brain Sciences, University of Washington Seattle WA, USA., Engemann DA; Institute of Neuroscience and Medicine - Cognitive Neuroscience (INM-3) Forschungszentrum Juelich, Germany ; Brain Imaging Lab, Department of Psychiatry, University Hospital Cologne, Germany., Strohmeier D; Institute of Biomedical Engineering and Informatics, Ilmenau University of Technology Ilmenau, Germany., Brodbeck C; Department of Psychology, New York University New York, NY, USA., Goj R; Psychological Imaging Laboratory, Psychology, School of Natural Sciences, University of Stirling Stirling, UK., Jas M; Department of Biomedical Engineering and Computational Science, Aalto University School of Science Espoo, Finland ; Brain Research Unit, O.V. Lounasmaa Laboratory, Aalto University School of Science Espoo, Finland., Brooks T; Department of Psychology, New York University New York, NY, USA., Parkkonen L; Department of Biomedical Engineering and Computational Science, Aalto University School of Science Espoo, Finland ; Brain Research Unit, O.V. Lounasmaa Laboratory, Aalto University School of Science Espoo, Finland., Hämäläinen M; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, and Harvard Medical School Charlestown MA, USA ; Brain Research Unit, O.V. Lounasmaa Laboratory, Aalto University School of Science Espoo, Finland.
Source:
Frontiers in neuroscience [Front Neurosci] 2013 Dec 26; Vol. 7, pp. 267. Date of Electronic Publication: 2013 Dec 26 (Print Publication: 2013).
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Frontiers Research Foundation Country of Publication: Switzerland NLM ID: 101478481 Publication Model: eCollection Cited Medium: Print ISSN: 1662-4548 (Print) Linking ISSN: 1662453X NLM ISO Abbreviation: Front Neurosci Subsets: PubMed not MEDLINE
Imprint Name(s):
Original Publication: Lausanne : Frontiers Research Foundation
References:
Comput Intell Neurosci. 2011;2011:852961. (PMID: 21437221)
Comput Intell Neurosci. 2011;2011:879716. (PMID: 21584256)
Comput Intell Neurosci. 2011;2011:156869. (PMID: 21253357)
Clin Neurophysiol. 2004 Oct;115(10):2292-307. (PMID: 15351371)
Neural Netw. 2000 May-Jun;13(4-5):411-30. (PMID: 10946390)
Neuroinformatics. 2012 Apr;10(2):141-58. (PMID: 22068921)
Neuroimage. 2013 Apr 15;70:410-22. (PMID: 23291276)
Hum Brain Mapp. 1999;8(4):194-208. (PMID: 10619414)
Neuron. 2000 Apr;26(1):55-67. (PMID: 10798392)
Front Neurosci. 2012 Oct 11;6:149. (PMID: 23087605)
Neuroimage. 2010 Oct 15;53(1):1-15. (PMID: 20547229)
Front Neuroinform. 2011 Aug 22;5:13. (PMID: 21897815)
Neuroimage. 2009 Feb 1;44(3):947-66. (PMID: 18602278)
Neuroimage. 2005 Apr 1;25(2):383-94. (PMID: 15784416)
Comput Intell Neurosci. 2011;2011:758973. (PMID: 21437174)
Neuroimage. 2014 Feb 1;86:446-60. (PMID: 24161808)
IEEE Trans Biomed Eng. 1997 Sep;44(9):867-80. (PMID: 9282479)
Med Biol Eng Comput. 1997 Mar;35(2):135-40. (PMID: 9136207)
Neuroimage. 2013 Jan 15;65:349-63. (PMID: 23046981)
Neuroimage. 1999 Feb;9(2):179-94. (PMID: 9931268)
Electroencephalogr Clin Neurophysiol. 1985 Jan;62(1):32-44. (PMID: 2578376)
IEEE Trans Biomed Eng. 1992 Jul;39(7):665-75. (PMID: 1516933)
Neuroimage. 2012 Oct 15;63(1):289-300. (PMID: 22796459)
Neuroimage. 2006 Jul 1;31(3):968-80. (PMID: 16530430)
Inf Process Med Imaging. 2011;22:600-11. (PMID: 21761689)
Cereb Cortex. 2004 Jan;14(1):11-22. (PMID: 14654453)
Neuroimage. 2012 Feb 1;59(3):2131-41. (PMID: 22037420)
Comput Intell Neurosci. 2011;2011:130714. (PMID: 21687590)
Phys Med Biol. 2012 Apr 7;57(7):1937-61. (PMID: 22421459)
J Neurosci Methods. 2007 Aug 15;164(1):177-90. (PMID: 17517438)
Med Biol Eng Comput. 1994 Jan;32(1):35-42. (PMID: 8182960)
Proc Natl Acad Sci U S A. 2001 Jan 16;98(2):694-9. (PMID: 11209067)
Biomed Eng Online. 2010 Sep 06;9:45. (PMID: 20819204)
Annu Rev Neurosci. 2009;32:209-24. (PMID: 19400723)
Neuroimage. 2012 Oct 1;62(4):2222-31. (PMID: 22366334)
Neuroimage. 2013 Jan 1;64:365-70. (PMID: 22974974)
Methods Find Exp Clin Pharmacol. 2002;24 Suppl D:5-12. (PMID: 12575463)
Neuroreport. 1997 Mar 24;8(5):1103-7. (PMID: 9175093)
Hum Brain Mapp. 2002 Jan;15(1):1-25. (PMID: 11747097)
Hum Brain Mapp. 2009 Jun;30(6):1857-65. (PMID: 19235884)
Neuroimage. 1999 Feb;9(2):195-207. (PMID: 9931269)
IEEE Trans Biomed Eng. 2010 May;57(5):1051-61. (PMID: 20142163)
J Neurosci Methods. 2004 Mar 15;134(1):9-21. (PMID: 15102499)
Grant Information:
R01 EB009048 United States EB NIBIB NIH HHS; S10 RR031599 United States RR NCRR NIH HHS
Contributed Indexing:
Keywords: electroencephalography (EEG); magnetoencephalography (MEG); neuroimaging; open-source; python; software
Entry Date(s):
Date Created: 20140117 Date Completed: 20140116 Latest Revision: 20220318
Update Code:
20250114
PubMed Central ID:
PMC3872725
DOI:
10.3389/fnins.2013.00267
PMID:
24431986
Database:
MEDLINE

Weitere Informationen

Magnetoencephalography and electroencephalography (M/EEG) measure the weak electromagnetic signals generated by neuronal activity in the brain. Using these signals to characterize and locate neural activation in the brain is a challenge that requires expertise in physics, signal processing, statistics, and numerical methods. As part of the MNE software suite, MNE-Python is an open-source software package that addresses this challenge by providing state-of-the-art algorithms implemented in Python that cover multiple methods of data preprocessing, source localization, statistical analysis, and estimation of functional connectivity between distributed brain regions. All algorithms and utility functions are implemented in a consistent manner with well-documented interfaces, enabling users to create M/EEG data analysis pipelines by writing Python scripts. Moreover, MNE-Python is tightly integrated with the core Python libraries for scientific comptutation (NumPy, SciPy) and visualization (matplotlib and Mayavi), as well as the greater neuroimaging ecosystem in Python via the Nibabel package. The code is provided under the new BSD license allowing code reuse, even in commercial products. Although MNE-Python has only been under heavy development for a couple of years, it has rapidly evolved with expanded analysis capabilities and pedagogical tutorials because multiple labs have collaborated during code development to help share best practices. MNE-Python also gives easy access to preprocessed datasets, helping users to get started quickly and facilitating reproducibility of methods by other researchers. Full documentation, including dozens of examples, is available at http://martinos.org/mne.