Analyzing effective connectivity with functional magnetic resonance imaging
Open accessAbstract
Functional neuroimaging techniques are used widely in cognitive neuroscience to investigate aspects of functional specialization and functional integration in the human brain. Functional integration can be characterized in two ways, functional connectivity and effective connectivity. While functional connectivity describes statistical dependencies between data, effective connectivity rests on a mechanistic model of the causal effects that generated the data. This review addresses the conceptual and methodological basis of established techniques for characterizing effective connectivity using functional magnetic resonance imaging (fMRI) data. In particular, we focus on dynamic causal modeling (DCM) of fMRI data and emphasize the importance of model selection procedures and nonlinear mechanisms for context-dependent changes in connection strengths. Copyright © 2010 John Wiley & Sons, Ltd. For further resources related to this article, please visit the WIREs website.
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Impaired structural connectivity suggests that inefficient information transfer between distal brain regions is a core pathophysiological feature of ADHD.
“This impaired structural connectivity suggests that inefficient information transfer between distal brain regions is a core pathophysiological feature”
From ADHD in Adulthood: Clinical Presentation, Comorbidities, and Treatment Perspectives (2025) · cites this paper as [76]
The Introduction describes functional and effective connectivity, and the Conclusions discuss using dynamic causal modeling to investigate disease mechanisms, with schizophrenia as an example. Searches for ADHD, impaired structural connectivity, and inefficient transfer between distal regions found no passage linking those ideas to ADHD in our copy; no page numbers were supplied. (LLM, conf=0.76)
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- Authors
- Stephan, K. E., & Friston, K. J.
- Affiliations
- Wellcome Centre for Human Neuroimaging (GB)
- Corresponding author
- Stephan, Klaas Enno
- Venue
- WIREs Cognitive Science
- Publisher
- Wiley
- Published
- 2010-04-02
- Volume
- 1
- Issue
- 3
- Pages
- 446-459
- ISSN
- 1939-5078 (ISSN-L)
- 1939-5086
- PMC
- PMC3013343
- OpenAlex
- W2733346734
- Cited by
- 202
- References
- 75
- Citations by year
- 2026: 9 · 2025: 17 · 2024: 15 · 2023: 11 · 2022: 25 · 2021: 14 · 2020: 14 · 2019: 12 · 2018: 8 · 2017: 14 · 2016: 11 · 2015: 11 · 2014: 7 · 2013: 11 · 2012: 11
- FWCI
- 6.59
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Wiley Interdisciplinary Reviews Cognitive Science (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Zurich Open Repository and Archive (University of Zurich) (submittedVersion, other-oa)
- Funders
- Wellcome Trust (056750, 088130)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- effective connectivity, functional connectivity, dynamic causal modeling, functional MRI, model selection, nonlinear mechanisms, causal inference, brain network dynamics
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