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citations.nbib
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PMID- 21403915
OWN - NLM
STAT- MEDLINE
DA - 20110315
DCOM- 20120213
LR - 20140821
IS - 1687-5273 (Electronic)
VI - 2011
DP - 2011
TI - LIMO EEG: a toolbox for hierarchical LInear MOdeling of ElectroEncephaloGraphic
data.
PG - 831409
LID - 10.1155/2011/831409 [doi]
AB - Magnetic- and electric-evoked brain responses have traditionally been analyzed by
comparing the peaks or mean amplitudes of signals from selected channels and
averaged across trials. More recently, tools have been developed to investigate
single trial response variability (e.g., EEGLAB) and to test differences between
averaged evoked responses over the entire scalp and time dimensions (e.g., SPM,
Fieldtrip). LIMO EEG is a Matlab toolbox (EEGLAB compatible) to analyse evoked
responses over all space and time dimensions, while accounting for single trial
variability using a simple hierarchical linear modelling of the data. In
addition, LIMO EEG provides robust parametric tests, therefore providing a new
and complementary tool in the analysis of neural evoked responses.
FAU - Pernet, Cyril R
AU - Pernet CR
AD - Division of Clinical Neurosciences, SFC Brain Imaging Research Centre, SINAPSE
Collaboration, University of Edinburgh, Western General Hospital, Edinburgh EH4
2XU, UK. [email protected]
FAU - Chauveau, Nicolas
AU - Chauveau N
FAU - Gaspar, Carl
AU - Gaspar C
FAU - Rousselet, Guillaume A
AU - Rousselet GA
LA - eng
PT - Journal Article
PT - Research Support, Non-U.S. Gov't
DEP - 20110221
PL - United States
TA - Comput Intell Neurosci
JT - Computational intelligence and neuroscience
JID - 101279357
SB - IM
MH - Brain/*physiology
MH - Electroencephalography/*methods
MH - Evoked Potentials/*physiology
MH - Humans
MH - *Linear Models
MH - *Signal Processing, Computer-Assisted
MH - Software/*standards
PMC - PMC3049326
OID - NLM: PMC3049326
EDAT- 2011/03/16 06:00
MHDA- 2012/02/14 06:00
CRDT- 2011/03/16 06:00
PHST- 2010/09/21 [received]
PHST- 2010/11/23 [revised]
PHST- 2010/12/31 [accepted]
PHST- 2011/02/21 [epublish]
AID - 10.1155/2011/831409 [doi]
PST - ppublish
SO - Comput Intell Neurosci. 2011;2011:831409. doi: 10.1155/2011/831409. Epub 2011 Feb
21.
PMID- 25128255
OWN - NLM
STAT- In-Process
DA - 20150613
LR - 20150808
IS - 1872-678X (Electronic)
IS - 0165-0270 (Linking)
VI - 250
DP - 2015 Jul 30
TI - Cluster-based computational methods for mass univariate analyses of event-related
brain potentials/fields: A simulation study.
PG - 85-93
LID - 10.1016/j.jneumeth.2014.08.003 [doi]
LID - S0165-0270(14)00287-8 [pii]
AB - BACKGROUND: In recent years, analyses of event related potentials/fields have
moved from the selection of a few components and peaks to a mass-univariate
approach in which the whole data space is analyzed. Such extensive testing
increases the number of false positives and correction for multiple comparisons
is needed. METHOD: Here we review all cluster-based correction for multiple
comparison methods (cluster-height, cluster-size, cluster-mass, and threshold
free cluster enhancement - TFCE), in conjunction with two computational
approaches (permutation and bootstrap). RESULTS: Data driven Monte-Carlo
simulations comparing two conditions within subjects (two sample Student's
t-test) showed that, on average, all cluster-based methods using permutation or
bootstrap alike control well the family-wise error rate (FWER), with a few
caveats. CONCLUSIONS: (i) A minimum of 800 iterations are necessary to obtain
stable results; (ii) below 50 trials, bootstrap methods are too conservative;
(iii) for low critical family-wise error rates (e.g. p=1%), permutations can be
too liberal; (iv) TFCE controls best the type 1 error rate with an attenuated
extent parameter (i.e. power<1).
CI - Crown Copyright (c) 2014. Published by Elsevier B.V. All rights reserved.
FAU - Pernet, C R
AU - Pernet CR
AD - Centre for Clinical Brain Sciences, Neuroimaging Sciences, University of
Edinburgh, Edinburgh, UK. Electronic address: [email protected].
FAU - Latinus, M
AU - Latinus M
AD - Institut de Neurosciences de la Timone UMR 7289, Aix Marseille Universite, CNRS,
13385 Marseille, France.
FAU - Nichols, T E
AU - Nichols TE
AD - Department of Statistics, Warwick University, Coventry, UK.
FAU - Rousselet, G A
AU - Rousselet GA
AD - Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, UK.
LA - eng
GR - 100309/Wellcome Trust/United Kingdom
GR - BB/K01420X/1/Biotechnology and Biological Sciences Research Council/United
Kingdom
GR - BB/K014218/1/Biotechnology and Biological Sciences Research Council/United
Kingdom
PT - Journal Article
PT - Research Support, Non-U.S. Gov't
DEP - 20140813
PL - Netherlands
TA - J Neurosci Methods
JT - Journal of neuroscience methods
JID - 7905558
SB - IM
PMC - PMC4510917
OID - NLM: PMC4510917
OTO - NOTNLM
OT - Cluster-based statistics
OT - ERP
OT - Family-wise error rate
OT - Monte-Carlo simulations
OT - Multiple comparison correction
OT - Threshold free cluster enhancement
EDAT- 2014/08/17 06:00
MHDA- 2014/08/17 06:00
CRDT- 2014/08/17 06:00
PHST- 2014/05/26 [received]
PHST- 2014/07/16 [revised]
PHST- 2014/08/05 [accepted]
PHST- 2014/08/13 [aheadofprint]
AID - S0165-0270(14)00287-8 [pii]
AID - 10.1016/j.jneumeth.2014.08.003 [doi]
PST - ppublish
SO - J Neurosci Methods. 2015 Jul 30;250:85-93. doi: 10.1016/j.jneumeth.2014.08.003.
Epub 2014 Aug 13.