Response to commentaries on our paper: Critical comments on dynamic causal modelling

Area of Science:

• Neuroscience
• Computational Neuroscience
• Cognitive Neuroscience

Background:

• Dynamic Causal Modelling (DCM) has been a subject of extensive research and application for many years.
• Recent discussions have raised questions regarding the validity and interpretation of DCM findings.
• This context necessitates a direct response to ongoing scientific debates.

Purpose of the Study:

• To address and respond to critical comments regarding the validity of Dynamic Causal Modelling (DCM).
• To engage with the scientific community's debate on DCM, particularly concerning critiques from Friston et al. and Breakspear.
• To reaffirm the established utility and interpretability of DCM in the field.

Main Methods:

• A detailed response to specific points raised by Friston et al. and Breakspear.
• Re-evaluation of core principles and assumptions underlying Dynamic Causal Modelling.
• Discussion of empirical and theoretical evidence supporting DCM's validity.

Main Results:

• The paper clarifies the robustness of Dynamic Causal Modelling (DCM) despite recent critiques.
• Key aspects of DCM methodology and interpretation are defended against specific challenges.
• The ongoing scientific discourse highlights the importance of rigorous methodological validation.

Conclusions:

• The authors welcome the debate on DCM validity as a necessary step for scientific progress.
• The response aims to provide clarity and reinforce the foundational principles of DCM.
• Continued critical evaluation is encouraged to further refine and validate neuroimaging analysis techniques.