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Outputs (3)

Improved functional connectivity network estimation for brain networks using multivariate partial coherence (2020)
Journal Article
Halliday, D. M., Senik, M. H., Makhtar, S. N., Stevenson, C. W., & Mason, R. (2020). Improved functional connectivity network estimation for brain networks using multivariate partial coherence. Journal of Neural Engineering, 17(2), Article 026013. https://doi.org/10.1088/1741-2552/ab7a50

Objective: Graphical networks and network metrics are widely used to understand and char-acterise brain networks and brain function. These methods can be applied to a range of electro-physiological data including electroencephalography, local field p... Read More about Improved functional connectivity network estimation for brain networks using multivariate partial coherence.

Adaptive spectral tracking for coherence estimation: the z-tracker (2018)
Journal Article
Halliday, D. M., Brittain, J., Stevenson, C. W., & Mason, R. (2018). Adaptive spectral tracking for coherence estimation: the z-tracker. Journal of Neural Engineering, 15(2), https://doi.org/10.1088/1741-2552/aaa3b4

Objective: A major challenge in non-stationary signal analysis is reliable estimation of correlation. Neurophysiological recordings can be many minutes in duration with data that exhibits correlation which changes over different time scales. Local sm... Read More about Adaptive spectral tracking for coherence estimation: the z-tracker.

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.