Dynamic causal modeling and Granger causality Comments on: The identification of interacting networks in the brain using fMRI: Model selection, causality and deconvolution
2009
Comments on Dynamic Causal Modeling and Granger Causality
publication
Author Information
Author(s): Friston Karl
Primary Institution: The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, UCL
Conclusion
The paper discusses the limitations and considerations of using Granger causality and dynamic causal modeling in fMRI studies.
Supporting Evidence
- The paper critiques the use of Granger causality in fMRI connectivity analysis.
- It emphasizes the importance of model comparison in understanding brain connectivity.
- The author discusses the limitations of dynamic causal modeling in accurately estimating brain connectivity.
Takeaway
This study talks about how scientists use different models to understand brain connections, and it points out some problems with those models.
Limitations
The paper highlights the challenges of model selection and the potential for overfitting in dynamic causal modeling.
Digital Object Identifier (DOI)
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