Non-parametric directionality analysis - Extension for removal of a single common predictor and application to time series
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- 作者：David M. Hallidaya ; david.halliday@york.ac.uk" class="auth_mail" title="E-mail the corresponding author ; Mohd Harizal Senikb ; Carl W. Stevensonc ; Rob Masonb
- 关键词：Directionality ; Partial coherence ; Non-parametric ; Time series ; Point process ; Conditional independence ; Granger causality
- 刊名：Journal of Neuroscience Methods
- 出版年：2016
- 出版时间：1 August 2016
- 年：2016
- 卷：268
- 期：Complete
- 页码：87-97
- 全文大小：2137 K
文摘
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We describe non-parametric estimates of conditional directionality between signals.
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Scalar metrics decompose the conditional product moment correlation by direction.
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Additional functions decompose the partial coherence estimate by direction.
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Method is applied to simulated (cortical neuron) and real (hippocampal LFP) data.
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Framework can be applied to time series and spike train data.