ArticleFrontiers in neuroscience2019
The Influence of EEG References on the Analysis of Spatio-Temporal Interrelation Patterns.
Article in Frontiers in neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed.
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- Irreversible functional network deformation induced by preprocessing scheme order in multivariate EEG recordings.Frontiers in neuroinformatics · 2026Article
- An automated extraction of spectral-temporal and spatial-temporal features of EEG for emotion detection.Brain informatics · 2025Article
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- EEG functional brain connectivity strengthens with age during attentional processing to faces in children.Frontiers in network physiology · 2022Article
- Yijinjing Qigong intervention shows strong evidence on clinical effectiveness and electroencephalography signal features for early poststroke depression: A randomized, controlled trial.Frontiers in aging neuroscience · 2022Article
- Inducing neuroplasticity through intracranial θ-burst stimulation in the human sensorimotor cortex.Journal of neurophysiology · 2021Article
- Speech-Brain Frequency Entrainment of Dyslexia with and without Phonological Deficits.Brain sciences · 2020Article
- Distinguishing Epileptiform Discharges From Normal Electroencephalograms Using Scale-Dependent Lyapunov Exponent.Frontiers in bioengineering and biotechnology · 2020Article
- Distinguishing Epileptiform Discharges From Normal Electroencephalograms Using Adaptive Fractal and Network Analysis: A Clinical Perspective.Frontiers in physiology · 2020Article
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11 authors.
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Abstract
The characterization of the functional network of the brain dynamics has become a prominent tool to illuminate novel aspects of brain functioning. Due to its excellent time resolution, such research is oftentimes based on electroencephalographic recordings (EEG). However, a particular EEG-reference might cause crucial distortions of the spatiotemporal interrelation pattern and may induce spurious correlations as well as diminish genuine interrelations originally present in the dataset. Here we investigate in which manner correlation patterns are affected by a chosen EEG reference. To this end we evaluate the influence of 7 popular reference schemes on artificial recordings derived from well controlled numerical test frameworks. In this respect we are not only interested in the deformation of spatial interrelations, but we test additionally in which way the time evolution of the functional network, estimated via some bi-variate interrelation measures, gets distorted. It turns out that the median reference as well as the global average show the best performance in most situations considered in the present study. However, if a collective brain dynamics is present, where most of the signals get correlated, these schemes may also cause crucial deformations of the functional network, such that the parallel use of different reference schemes seems advisable.
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