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Dissociating neuronal gamma-band activity from cranial and ocular muscle activity in EEG

EEG is the most common technique for studying neuronal dynamics of the human brain. However, electromyogenic artifacts from cranial muscles and ocular muscles executing involuntary microsaccades compromise estimates of neuronal activity in the gamma band (>30 Hz). Yet, the relative contributions...

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Detalles Bibliográficos
Autores principales: Hipp, Joerg F., Siegel, Markus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3706727/
https://www.ncbi.nlm.nih.gov/pubmed/23847508
http://dx.doi.org/10.3389/fnhum.2013.00338
Descripción
Sumario:EEG is the most common technique for studying neuronal dynamics of the human brain. However, electromyogenic artifacts from cranial muscles and ocular muscles executing involuntary microsaccades compromise estimates of neuronal activity in the gamma band (>30 Hz). Yet, the relative contributions and practical consequences of these artifacts remain unclear. Here, we systematically dissected the effects of these different artifacts on studying visual gamma-band activity with EEG on the sensor and source level, and show strategies to cope with these confounds. We found that cranial muscle activity prevented a direct investigation of neuronal gamma-band activity at the sensor level. Furthermore, we found prolonged microsaccade-related artifacts beyond the well-known transient EEG confounds. We then show that if electromyogenic artifacts are carefully accounted for, the EEG nonetheless allows for studying visual gamma-band activity even at the sensor level. Furthermore, we found that source analysis based on spatial filtering does not only map the EEG signals to the cortical space of interest, but also efficiently accounts for cranial and ocular muscle artifacts. Together, our results clarify the relative contributions and characteristics of myogenic artifacts confounding visual gamma-band activity in EEG, and provide practical guidelines for future experiments.