Frontiers in Neuroscience · 2018 · 136 citations · 29 references
EngineeringNeurologyNeuroscienceComputational NeuroscienceElectrophysiologyNeurophysiologyBrain-computer InterfacesContinuous ElectroencephalographyElectroencephalogram AnalysisElectroencephalogram Signal ProcessingElectroencephalographyNeural Recording TechnologiesAutomated Eeg AnalysisBatch Data ProcessingEeg Signal ProcessingElectroencephalogram AcquisitionElectroencephalogram PreprocessingElectroencephalogram SegmentationElectroencephalogram Signal AnalysisElectroencephalography Instrumentation
Electroencephalography (EEG) offers information about brain function relevant to a variety of neurologic and neuropsychiatric disorders. EEG contains complex, high-temporal-resolution information, and computational assessment maximizes our potential to glean insight from this information. Here we present the Batch EEG Automated Processing Platform (BEAPP), an automated, flexible EEG processing platform incorporating freely available software tools for batch processing of multiple EEG files across multiple processing steps. BEAPP does not prescribe a specified EEG processing pipeline; instead, it allows users to choose from a menu of options for EEG processing, including steps to manage EEG files collected across multiple acquisition setups (e.g., for multisite studies), minimize artifact, segment continuous and/or event-related EEG, and perform basic analyses. Overall, BEAPP aims to streamline batch EEG processing, improve accessibility to computational EEG assessment, and increase reproducibility of results.
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Spectrum estimation and harmonic analysis
David J. Thomson · Proceedings of the IEEE · 1982 · 4.5K citations
MEG and EEG data analysis with MNE-Python
Alexandre Gramfort · Frontiers in Neuroscience · 2013 · 4K citations · Full text