ADJUST: An automatic EEG artifact detector based on the joint use of spatial and temporal features.

By A. Mognon, Jorge Jovicich, Lorenzo Bruzzone, Marco Buiatti. Psychophysiology, 2011

1,264 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Signal Processing

View Paper: https://www.semanticscholar.org/paper/284636fc53503d4fb192b77e941dc1edf9359789

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Citations in the corpus

The Harvard Automated Processing Pipeline for Electroencephalography (HAPPE): Standardized Processing Software for Developmental and High-Artifact Data (2018, methodology): “…et al., 2014, SASICA, Chaumon et al., 2015), but they have largely been developed and tested on healthy adult EEG data with low levels of artifact contamination (Nolan et al., 2010; Mognon et al., 2011; Mullen et al., 2013; Bigdely-Shamlo et al., 2015; Chaumon et al., 2015; Hatz et al., 2015).”
Robust artifactual independent component classification for BCI practitioners (2014, methodology): “Unsupervised methods successfully circumvent this problem for example by reverting to automatic thresholding strategies [29].”
Decoding Dynamic Brain Patterns from Evoked Responses: A Tutorial on Multivariate Pattern Analysis Applied to Time Series Neuroimaging Data (2016, methodology): “…analyses trials containing such artifacts are manually in-spected and excluded from the analysis, or independent component analysis is used to separate out these artifacts into their own components, which are then removed manually or automatically (Mognon, Jovicich, Bruzzone, & Buiatti, 2011).”
Predicting Advertising success beyond Traditional Measures: New Insights from Neurophysiological Methods and Market Response Modeling (2015, methodology): “Artifacts (horizontal eye movement, vertical eye movement, eye blinks, and general discontinuities) were automatically detected and removed using ADJUST 1.1, an independent plug-in for EEGLAB (Mognon et al. 2011).”
The PREP pipeline: standardized preprocessing for large-scale EEG analysis (2015, methodology): “ADJUST (Mognon et al., 2011) uses ICA to remove features associated with various stereotypical artifacts, particularly eye blinks, eye movements, and discontinuities.”
Neural Oscillatory Markers of Voluntary Task Switching: Proactive Engagement of Self‐Directed Control in Children and Adults (2025, unknown): “Eye-blinks and other eye-movement artefacts were corrected through an independent component analysis (ICA) using ADJUST (Mognon et al. 2011).”
Neural correlates involved in perspective-taking in early childhood (2024, methodology): “We then used ADJUST, an EEGLAB plugin for automatized EEG artifact detection (Mognon et al., 2011) and visual inspection to identify independent components containing artifacts, which were subsequently removed from the original dataset.”
How to refocus attention on working memory representations following interruptions—Evidence from frontal theta and posterior alpha oscillations (2021, methodology): “Independent components (ICs) related to artefacts such as eye movements, eye blinks or generic data discontinuities were identified using the ADJUST algorithm (Mognon et al., 2011).”
Neural signatures of syntactic variation in speech planning (2021, methodology): “The SASICA and ADJUST algorithms [115,116] were used to identify artifactual components (number of rejected independent components: mean = 32.”