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Related Experiment Video

Updated: May 9, 2026

Technique and Considerations in the Use of 4x1 Ring High-definition Transcranial Direct Current Stimulation (HD-tDCS)

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Published on: July 14, 2013

Understanding DCM: ten simple rules for the clinician.

Joshua Kahan¹, Tom Foltynie

¹Sobell Department for Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, London, UK.

|July 16, 2013

Summary

Dynamic Causal Modelling (DCM) helps understand brain function. This guide clarifies DCM's purpose and jargon for neuroimaging and neuroscience researchers, simplifying complex analyses.

Area of Science:

Neuroimaging
Computational Neuroscience
Systems Neuroscience

Background:

Dynamic Causal Modelling (DCM) has been available for nearly a decade.
Confusion persists regarding the specific applications and terminology of DCM studies within the neuroimaging, neuroscience, and clinical fields.

Purpose of the Study:

To demystify Dynamic Causal Modelling (DCM) for a broader audience.
To clarify the underlying rationale and interpretation of DCM analyses in neuroimaging.
To provide a foundational understanding for non-technical researchers and clinicians.

Main Methods:

A "ten simple rules" approach is presented.
A theoretical example is included to illustrate DCM principles.
The content is designed as an introductory primer.

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Last Updated: May 9, 2026

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Main Results:

The study offers a clear explanation of what DCM analyses investigate.
It provides guidance on how to approach neuroimaging data within the context of DCM.
The jargon associated with DCM is addressed to reduce confusion.

Conclusions:

This primer aims to orient non-technical neuroscientists and clinicians.
It facilitates a better understanding of the technical aspects of DCM.
The goal is to make DCM more accessible and comprehensible for researchers and clinicians.