Topographic ERP Analyses: A Step-by-Step Tutorial Review

By Micah M. Murray, Denis Brunet, C. Michel. Brain Topography, 2008

1,094 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/d52b8bf66a132e4859b75d94bb8089056f50f074

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In Cellular and Molecular Neuroscience

In Cognitive Neuroscience

Citations in the corpus

Capturing the spatiotemporal dynamics of self-generated, task-initiated thoughts with EEG and fMRI (2019, neutral): “This improves confidence in the right estimation of the optimal number of clusters, as compared to previous work relying on a single criterion only (i.e. Cross-Validation criterion (Pascual-Marqui et al., 1995) or the Krzanowski-Lai Index (Murray et al., 2008)).”
Looming Signals Reveal Synergistic Principles of Multisensory Integration (2012, methodology): “The optimal number of temporally stable ERP clusters (i.e., the minimal number of maps that accounts for the greatest variance of the dataset) was determined using a modified Krzanowski-Lai criterion (Murray et al., 2008).”
EEG microstate sequences in healthy humans at rest reveal scale-free dynamics (2010, methodology): “We computed the spatial correlation between the four templatemaps and the instantaneous EEG (77) using a temporal constraint criterion of 32 ms.”
The efficacy of single-trial multisensory memories. (2013, methodology): “Finally, we used electrical neuroimaging analyses of event-related potentials (e.g. Michel et al., 2004; Murray et al., 2008; Michel and Murray, 2012; Tzovara et al., 2012a,b) to provide adequate spatio-temporal resolution to garner information concerning when and where such effects first occur…”
EEG microstates as a tool for studying the temporal dynamics of whole‐brain neuronal networks: A review (2017, background): “cluster or factor analysis can be used to determine the most dominant spatial components in map series, such as agglomerative hierarchical clustering (Murray et al., 2008), principal component analysis (Pourtois et al.”
Contextual factors multiplex to control multisensory processes (2016, methodology): “, the minimal number of maps that accounts for the greatest variance of the dataset) was determined using a modified Krzanowski-Lai criterion [Murray et al., 2008].”
Electroencephalographic Resting-State Networks: Source Localization of Microstates (2017, neutral): “…and Bouldin, Dunn, Frey and Van Groenewoud, Hartigan (its ﬁrst derivative), Krzanowski-Lai Index, Marriott, Point-Biserial, Tau, and Trace (W) (its second derivative) (Charrad et al., 2014; Krzanowski and Lai, 1988; Milligan and Cooper, 1985; Murray et al., 2008; Pascual-Marqui et al., 1995).”
Top-down control and early multisensory processes: chicken vs. egg (2015, background): “…of the eMSI is further complicated by the fact that the overwhelming Frontiers in Integrative Neuroscience www.frontiersin.org March 2015 | Volume 9 | Article 17 | 3 majority of the human EEG studies have used relative, reference-dependent measures of amplitude (cf., Murray et al., 2008).”
Electrical neuroimaging of memory discrimination based on single-trial multisensory learning (2012, methodology): “the minimal number of maps that accounts for the greatest variance of the dataset) was determined using a modified Krzanowski-Lai criterion (Murray et al., 2008).”
Towards the utilization of EEG as a brain imaging tool (2012, methodology): “(D) Global dissimilarity between conditions was statistically tested via a permutation test (detailed in Murray et al., 2008).”
The role of auditory cortices in the retrieval of single‐trial auditory–visual object memories (2015, methodology): “Third, the collective post-stimulus group-average ERPs were subjected to a topographic analysis based on a hierarchical clustering algorithm (Murray et al., 2008).”
The multisensory function of the human primary visual cortex. (2016, background): “From a more mechanistic standpoint, the analyses falling under the umbrella-term of electrical neuroimaging (e.g. Murray et al., 2008) can reveal whether and, if so, when multisensory stimuli engage distinct configurations of brain regions and/or modulate the gain of regions already active under…”
Identifying and Quantifying Multisensory Integration: A Tutorial Review (2014, methodology): “This technique is based on reference-independent measures of the global electric field at the scalp to differentiate between modulations in response strength, topography, and latency (Murray et al. 2008; Michel et al. 2004, 2009).”
Spatiotemporal Analysis of Multichannel EEG: CARTOOL (2011, methodology): “The TANOVA described above can easily be extended to multivariate measures [42].”
The Multivariate Temporal Response Function (mTRF) Toolbox: A MATLAB Toolbox for Relating Neural Signals to Continuous Stimuli (2016, background): “GFP constitutes a reference-independent measure of response strength across the entire scalp at each time lag (Lehmann and Skrandies, 1980; Murray et al., 2008).”