Non-parametric directionality analysis: extension for removal of a single common predictor and application to time series
(2016)
Journal Article
Halliday, D. M., Senik, M. H., Stevenson, C. W., & Mason, R. (2016). Non-parametric directionality analysis: extension for removal of a single common predictor and application to time series. Journal of Neuroscience Methods, 268, https://doi.org/10.1016/j.jneumeth.2016.05.008
BACKGROUND: The ability to infer network structure from multivariate neuronal signals is central to computational neuroscience. Directed network analyses typically use parametric approaches based on auto-regressive (AR) models, where networks are con... Read More about Non-parametric directionality analysis: extension for removal of a single common predictor and application to time series.