Analysis and visualization of single‐trial event‐related potentials
By Tzyy-Ping Jung, Scott Makeig, Marissa Westerfield, Jeanne Townsend, Eric Courchesne, Terrence J. Sejnowski. Human Brain Mapping, 2001
698 citations recorded by the source corpus.
Subfields: Cognitive Neuroscience, Signal Processing
View Paper: https://www.semanticscholar.org/paper/b97152fc8c687d615c7708a0193787cd9361a1e5
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cognitive Neuroscience
- Scott Makeig
- Arnaud Delorme
- Julie Anne Onton
- Tzyy-Ping Jung
- Terrence J. Sejnowski
- Klaus Gramann
- Joseph T. Gwin
- Daniel P. Ferris
In Signal Processing
- Scott Makeig
- Arnaud Delorme
- Julie Anne Onton
- Terrence J. Sejnowski
- Tzyy-Ping Jung
- Klaus Gramann
- Daniel P. Ferris
- Joseph T. Gwin
Citations in the corpus
- Imaging brain dynamics using independent component analysis (2001, methodology): “ICA thus may help researchers to take fuller advantage of what until now has been an only partially realized strength of event-related paradigms—the ability to examine systematic relationships between single trials within subjects [29], [32], [ 45 ], [48].”
- EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. (2004, background): “…(Pfurtscheller and Aranibar, 1979; Bressler and Freeman, 1980; Makeig, 1993; Neuenschwander and Varela, 1993; Tallon-Baudry et al., 1996; Weiss and Rappelsberger, 1996) and Independent Component Analysis (ICA) (Makeig et al., 1996; Makeig et al., 1997; Makeig et al., 1999; Jung et al., 2001).”
- Decomposing EEG data into space-time-frequency components using Parallel Factor Analysis (2004, neutral): “It avoids the arbitrary choice of rotation (Jung et al., 2001).”
- Information-based modeling of event-related brain dynamics. (2006, background): “Furthermore, the ERP-image plots (right) (Makeig et al., 1999; Jung et al., 2001) of the activities of these components in single trials show consistent patterns of activity time-locked to experimental stimuli of interest.”
- EEG-based drowsiness estimation for safety driving using independent component analysis (2005, background): “2) The signal source of muscle activity, eye, and cardiac signals are not time locked to the sources of EEG activity which is regarded as reflecting synaptic activity of cortical neurons [45]–[ 48 ].”
- Electrocortical activity is coupled to gait cycle phase during treadmill walking (2011, methodology): “Next, electrocortical sources were clustered across subjects using EEGLAB routines implementing k-means clustering on vectors jointly coding differences in equivalent dipole locations and power spectra; the resulting joint vector was reduced to 10 principal dimensions using principal component analy”
- An improved P300-based brain-computer interface (2005, methodology): “[37], [38] the ICA algorithm was used on ERP data recorded from more than 30 electrodes.”
- Handbook of Blind Source Separation: Independent Component Analysis and Applications (2010, neutral): “46 5”
- Across-trial averaging of event-related EEG responses and beyond. (2008, background): “The result is a marked increase in signal-tonoise ratio allowing a more robust single-trial estimate of ERPs [39,40].”