Enhancing oscillations in intracranial electrophysiological recordings with data-driven spatial filters.

ABSTRACT: In invasive electrophysiological recordings, a variety of neural oscillations can be detected across the cortex, with overlap in space and time. This overlap complicates measurement of neural oscillations using standard referencing schemes, like common average or bipolar referencing. Here, we illustrate the effects of spatial mixing on measuring neural oscillations in invasive electrophysiological recordings and demonstrate the benefits of using data-driven referencing schemes in order to improve measurement of neural oscillations. We discuss referencing as the application of a spatial filter. Spatio-spectral decomposition is used to estimate data-driven spatial filters, a computationally fast method which specifically enhances signal-to-noise ratio for oscillations in a frequency band of

SUBMITTER: Schaworonkow N 

PROVIDER: S-EPMC8407590 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature