ArticleJournal of neural engineering2015
The effects of spatial filtering and artifacts on electrocorticographic signals.
Article in Journal of neural engineering, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
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Who cites it
37 citing papers in PubMed.
- Pilot Trial of Perampanel on Peritumoral Hyperexcitability in Newly Diagnosed High-grade Glioma.Clinical cancer research : an official journal of the American Association for Cancer Research · 2024Trial
- Spatio-Temporal Progression of Cortical Activity Related to Continuous Overt and Covert Speech Production in a Reading Task.PloS one · 2016Trial
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- Intracranial EEG referencing for large-scale category-selective mapping in the human ventral occipito-temporal cortex.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Effect of Electrode Distance and Size on Electrocorticographic Recordings in Human Sensorimotor Cortex.Neuroinformatics · 2024Article
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- Assessing expert reliability in determining intracranial EEG channel quality and introducing the automated bad channel detection algorithm.Journal of neural engineering · 2024Article
- Novel Cyclic Homogeneous Oscillation Detection Method for High Accuracy and Specific Characterization of Neural Dynamics.bioRxiv : the preprint server for biology · 2024Article
- Macroscopic resting-state brain dynamics are best described by linear models.Nature biomedical engineering · 2024Article
- A supervised data-driven spatial filter denoising method for speech artifacts in intracranial electrophysiological recordings.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Single-pulse electrical stimulation artifact removal using the novel matching pursuit-based artifact reconstruction and removal method (MPARRM).Journal of neural engineering · 2023Article
- High gamma coherence between task-responsive sensory-motor cortical regions in a motor reaction-time task.Journal of neurophysiology · 2023Article
- Music can be reconstructed from human auditory cortex activity using nonlinear decoding models.PLoS biology · 2023Article
- Slow-wave modulation analysis during states of unconsciousness using the novel tau-modulation method.Journal of neural engineering · 2023Article
- Unexpected sound omissions are signaled in human posterior superior temporal gyrus: an intracranial study.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
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- Automated intraoperative central sulcus localization and somatotopic mapping using median nerve stimulation.Journal of neural engineering · 2022Article
- The precedence effect in spatial hearing manifests in cortical neural population responses.BMC biology · 2022Article
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- Subthalamic-Cortical Network Reorganization during Parkinson's Tremor.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
objectiveElectrocorticographic (ECoG) signals contain noise that is common to all channels and noise that is specific to individual channels. Most published ECoG studies use common average reference (CAR) spatial filters to remove common noise, but CAR filters may introduce channel-specific noise into other channels. To address this concern, scientists often remove artifactual channels prior to data analysis. However, removing these channels depends on expert-based labeling and may also discard useful data. Thus, the effects of spatial filtering and artifacts on ECoG signals have been largely unknown. This study aims to quantify these effects and thereby address this gap in knowledge. APPROACH: In this study, we address these issues by exploring the effects of application of two types of unsupervised spatial filters and three methods of detecting signal artifacts using a large ECoG data set (20 subjects, four task conditions in each subject). MAIN
resultsOur results confirm that spatial filtering improves performance, i.e., it reduces ECoG signal variance that is not related to the task. They also show that removing artifactual channels automatically (using quantitatively defined rejection criteria) or manually (using expert opinion) does not increase the total amount of task-related information, but does avoid potential contamination from one or more noisy channels. Finally, applying a novel 'median average reference' filter does not require the elimination of artifactual channels prior to spatial filtering and still mitigates the influence of channels with channel-specific noise. Thus, it allows the investigator to retain more potentially useful task-related data. SIGNIFICANCE: In summary, our results show that appropriately designed spatial filters that account for both common noise and channel-specific noise greatly improve the quality of ECoG signal analyses, and that artifacts in only a single channel can result in profound and undesired effects on all other channels.
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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.