کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6035201 | 1188762 | 2011 | 8 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Technical NoteGranger causality with signal-dependent noise Technical NoteGranger causality with signal-dependent noise](/preview/png/6035201.png)
It is generally believed that the noise variance in in vivo neuronal data exhibits time-varying volatility, particularly signal-dependent noise. Despite a widely used and powerful tool to detect causal influences in various data sources, Granger causality has not been well tailored for time-varying volatility models. In this technical note, a unified treatment of the causal influences in both mean and variance is naturally proposed on models with signal-dependent noise in both time and frequency domains. The approach is first systematically validated on toy models, and then applied to the physiological data collected from Parkinson patients, where a clear advantage over the classical Granger causality is demonstrated.
⺠Granger causality has been extended to models with signal-dependent noise. ⺠Granger causality in conditional mean and conditional variance has been unified. ⺠Causality is analyzed in both the time and the frequency domains. ⺠Feedback from tremor to brain has been revealed for Parkinson patients.
Journal: NeuroImage - Volume 57, Issue 4, 15 August 2011, Pages 1422-1429