Optimal referencing for stereo-electroencephalographic (SEEG) recordings
| Autor: | Liang Chen, Meng Wang, Guangye Li, Dingguo Zhang, Gerwin Schalk, Zehan Wu, Sivylla E. Paraskevopoulou, Yang Xu, Shize Jiang |
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| Rok vydání: | 2018 |
| Předmět: |
Adult
Computer science Cognitive Neuroscience Motor Activity Signal Article 050105 experimental psychology Stereoelectroencephalography Entire brain Stereotaxic Techniques White matter 03 medical and health sciences 0302 clinical medicine medicine Humans 0501 psychology and cognitive sciences Gray Matter Epilepsy Electromyography business.industry 05 social sciences Brain Signal Processing Computer-Assisted Pattern recognition Brain Waves White Matter Sample (graphics) medicine.anatomical_structure Neurology Electrocorticography Artificial intelligence business 030217 neurology & neurosurgery |
| Zdroj: | NeuroImage. 183:327-335 |
| ISSN: | 1053-8119 |
| Popis: | Stereo-electroencephalography (SEEG) is an intracranial recording technique in which depth electrodes are inserted in the brain as part of presurgical assessments for invasive brain surgery. SEEG recordings can tap into neural signals across the entire brain and thereby sample both cortical and subcortical sites. However, even though signal referencing is important for proper assessment of SEEG signals, no previous study has comprehensively evaluated the optimal referencing method for SEEG. In our study, we recorded SEEG data from 15 human subjects during a motor task, referencing them against the average of two white matter contacts (monopolar reference). We then subjected these signals to 5 different re-referencing approaches: common average reference (CAR), gray-white matter reference (GWR), electrode shaft reference (ESR), bipolar reference, and Laplacian reference. The results from three different signal quality metrics suggest the use of the Laplacian re-reference for study of local population-level activity and low-frequency oscillatory activity. |
| Databáze: | OpenAIRE |
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