ArticleScientific reports2023
EEG is better left alone.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 86 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
86 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Preprocessing choices for P3 analyses with mobile EEG: A systematic literature review and interactive exploration.Psychophysiology · 2025Pooled it
- The Effects of Neuroinflammation Induced by Typhoid Vaccine on Resting and Task-Based Electroencephalography.Brain and behavior · 2025Trial
- Exploring the mechanisms of biofield therapy through joint electrophysiological recordings in humans and mice.IBRO neuroscience reports · 2026Article
- SSDLabeler: realistic semi-synthetic data generation for multi-label artifact classification in EEG.Scientific reports · 2026Article
- Advancing Stroke Recovery Through Operant Conditioning of Corticomuscular Coherence.Restorative neurology and neuroscience · 2026Review
- Creating an engaging brain computer interface, electrical stimulation therapy for children with hemiparesis: a pilot study.Journal of neuroengineering and rehabilitation · 2026Article
- Clinical utility and prospective of TMS-EEG: Updated review from an international expert group.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2026Review
- The neurocognitive efficiency score: Derivation, validation, and application of a novel combination of concurrent electrophysiological and behavioral data.Cognitive, affective & behavioral neuroscience · 2026Article
- Working memory load and search efficiency in conventional monitor-based 2D versus 3D virtual settings: analysis of response times and parietal induced alpha activity in a modified Sternberg task.Experimental brain research · 2026Article
- Shared Neural Codes for Emotion Recognition in Emoji and Human Faces.Psychophysiology · 2026Article
- Spatial Distance and Temporal Attentional Focus Modulate Voluntary Action Preparation and Awareness.Psychophysiology · 2026Article
- Comparing Simultaneous Scalp EEG Recordings from the OpenBCI Cyton and Brain Products BrainAmp.Sensors (Basel, Switzerland) · 2026Article
- Balancing noise reduction and neural signature preservation in EEG biometrics.Scientific reports · 2026Article
- Evaluating haptic experience using EEG and deep learning across multiple modalities: linking stimulus and self-reports.Frontiers in neuroscience · 2026Article
- Artificial intelligence-based analysis of visual electrophysiological signals for clinical interpretation support.Frontiers in neuroscience · 2026Review
- Physiological sensing for situational awareness: a theory-driven integrative review of multimodal and unsupervised approaches for visual search and human-autonomy teaming.Frontiers in neuroergonomics · 2026Review
- Regional and cannabis-related differences in prefrontal multiscale entropy of resting-state EEG.Clinical neurophysiology practice · 2026Article
- Identifying Neurobehavioral Biomarkers of Anxiety and Treatment Response Using Virtual Reality, Electroencephalography, Magnetic Resonance Imaging, and Related Multimodal Assessments: A Longitudinal Study Protocol.Journal of clinical medicine · 2025Article
- Shared neural dynamics of facial expression processing.Cognitive neurodynamics · 2025Article
- EEG entropy modulation as a biomarker of emotion regulation and resilience.IBRO neuroscience reports · 2025Review
26 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
Automated preprocessing methods are critically needed to process the large publicly-available EEG databases, but the optimal approach remains unknown because we lack data quality metrics to compare them. Here, we designed a simple yet robust EEG data quality metric assessing the percentage of significant channels between two experimental conditions within a 100 ms post-stimulus time range. Because of volume conduction in EEG, given no noise, most brain-evoked related potentials (ERP) should be visible on every single channel. Using three publicly available collections of EEG data, we showed that, with the exceptions of high-pass filtering and bad channel interpolation, automated data corrections had no effect on or significantly decreased the percentage of significant channels. Referencing and advanced baseline removal methods were significantly detrimental to performance. Rejecting bad data segments or trials could not compensate for the loss in statistical power. Automated Independent Component Analysis rejection of eyes and muscles failed to increase performance reliably. We compared optimized pipelines for preprocessing EEG data maximizing ERP significance using the leading open-source EEG software: EEGLAB, FieldTrip, MNE, and Brainstorm. Only one pipeline performed significantly better than high-pass filtering the data.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.