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Time, frequency, and time-varying Granger-causality measures in neuroscience
Sezen Cekic1, Didier Grandjean2, Olivier Renaud1
1Methodology and Data Analysis, Department of Psychology, University of Geneva, Geneva, Switzerland.
Statistics in Medicine
|March 16, 2018
Summary
This review critically examines methods for calculating Granger-causality statistics in neuroscience. It provides a framework for understanding time, frequency, and time-varying causality measures crucial for brain signal analysis.
Area of Science:
- Neuroscience
- Computational Neuroscience
- Signal Processing
Background:
- Causal links between brain signals are of primary interest to neuroscientists.
- Existing methods for deriving Granger-causality statistics are complex and varied.
- A systematic review is needed to clarify these methodologies.
Purpose of the Study:
- To provide a systematic methodological review and objective criticism of existing Granger-causality statistics in neuroscience.
- To present a framework for comparing time, frequency, and time-varying Granger-causality methods.
- To discuss the estimation and distributional properties of these statistics.
Main Methods:
- Systematic methodological review of Granger-causality derivation techniques.
- Presentation of a general framework for comparing time-domain Granger-causality and transfer entropy.
- Discussion of spectral and time-varying extensions, including estimation and distributional properties.
Main Results:
- A comprehensive overview and critique of current Granger-causality methods in neuroscience.
- A framework for understanding the relationships between different Granger-causality measures.
- Insights into the methodological complexities and properties of these statistics.
Conclusions:
- The review clarifies complex methodologies for Granger-causality analysis in neuroscience.
- Understanding these methods is essential for accurately inferring causal relationships from brain signals.
- This work serves as a guide for researchers utilizing Granger-causality in neuroscience studies.
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