A short history of causal modeling of fMRI data
Open accessAbstract
Twenty years ago, the discovery of the blood oxygen level dependent (BOLD) contrast and invention of functional magnetic resonance imaging (MRI) not only allowed for enhanced analyses of regional brain activity, but also laid the foundation for novel approaches to studying effective connectivity, which is essential for mechanistically interpretable accounts of neuronal systems. Dynamic causal modeling (DCM) and Granger causality (G-causality) modeling have since become the most frequently used techniques for inferring effective connectivity from fMRI data. In this paper, we provide a short historical overview of these approaches, describing milestones of their development from our subjective perspectives.
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During handwriting with a stylus, velocity, frequency, trajectory duration, and pressure of strokes were studied as indicators for cognitive workload.
“During handwriting with a stylus, the velocity [211,260], frequency [210], trajectory duration [209], and pressure of strokes [260] were studied as indicators for cognitive workload.”
From A Survey on Measuring Cognitive Workload in Human-Computer Interaction (2023) · cites this paper as [211]
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“knowledge, it is possible that it allows for inference on certain (neuronal) mechanisms, but not on others, due to conditional dependencies among parameters that are typical for biological systems (Gutenkunst et al., 2007; Stephan et al., 2007b).”
Ten simple rules for dynamic causal modeling
Stephan, K. E., Penny, W. D., Moran, R. J., den Ouden, H. E. M., Daunizeau, J., & Friston, K. J. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.11.015 · Cited by 803 · see citing works
Self-citationComparing families of dynamic causal models
Penny, W. D., Stephan, K. E., Daunizeau, J., Rosa, M. J., Friston, K. J., Schofield, T. M., & Leff, A. P. (2010) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000709 · Cited by 688 · see citing works
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Self-citationComparing dynamic causal models using AIC, BIC and free energy
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“imization (DEM; (Friston et al., 2008)) or Generalised Filtering (Friston et al.”
Friston, K., Stephan, K., Li, B., & Daunizeau, J. (2010) · Mathematical Problems in Engineering · doi:10.1155/2010/621670 · Cited by 171 · see citing works
Self-citationAn in vivo assay of synaptic function mediating human cognition
Moran, R. J., Symmonds, M., Stephan, K. E., Friston, K. J., & Dolan, R. J. (2011) · Current Biology · doi:10.1016/j.cub.2011.06.053 · Cited by 137 · see citing works
Self-citationBayesian estimation of synaptic physiology from the spectral responses of neural masses
Moran, R. J., Stephan, K. E., Kiebel, S. J., Rombach, N., O'Connor, W. T., Murphy, K. J., Reilly, R. B., & Friston, K. J. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.01.025 · Cited by 126 · see citing works
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Dynamic causal modeling: a generative model of slice timing in fMRI
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Moran, R. J., Jung, F., Kumagai, T., Endepols, H., Graf, R., Dolan, R. J., Friston, K. J., Stephan, K. E., & Tittgemeyer, M. (2011) · PLoS ONE · doi:10.1371/journal.pone.0022790 · Cited by 88 · see citing works
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van Diessen, E., Numan, T., van Dellen, E., van der Kooi, A. W., Boersma, M., Hofman, D., van Lutterveld, R., van Dijk, B. W., van Straaten, E. C. W., Hillebrand, A., et al. (2015) · Clinical Neurophysiology · doi:10.1016/j.clinph.2014.11.018 · Cited by 417 · see citing works
A Survey on Measuring Cognitive Workload in Human-Computer Interaction
Kosch, T., Karolus, J., Zagermann, J., Reiterer, H., Schmidt, A., & Woźniak, P. W. (2023) · ACM Computing Surveys · doi:10.1145/3582272 · Cited by 304 · see citing works
“…investigate the oxygen levels in the blood, or Functional Magnetic Resonance Imaging (fMRI) that measures the electro-magnetic responses of the brain, was introduced in the 70s [69] and 90s [229], respectively, to obtain more accurate brain imaging measurements at the cost of temporal resolution.”
Top-down regulation of default mode activity in spatial visual attention
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- Authors
- Stephan, K. E., & Roebroeck, A.
- Affiliations
- Wellcome Centre for Human Neuroimaging (GB)
- Maastricht University (NL)
- Corresponding author
- Stephan, Klaas Enno
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2012-08
- Volume
- 62
- Issue
- 2
- Pages
- 856-863
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2129932189
- Cited by
- 112
- References
- 15
- Citations by year
- 2026: 1 · 2025: 6 · 2024: 4 · 2023: 4 · 2022: 10 · 2021: 7 · 2020: 5 · 2019: 4 · 2018: 4 · 2017: 7 · 2016: 10 · 2015: 15 · 2014: 13 · 2013: 15 · 2012: 7
- FWCI
- 1.27
- Type
- journal article
- Language
- en
- Open access
- Licence
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Research Publications (Maastricht University) (publishedVersion, other-oa)
- Zurich Open Repository and Archive (University of Zurich) (acceptedVersion)
- Zurich Open Repository and Archive (University of Zurich) (submittedVersion)
- Research Publications (Maastricht University) (submittedVersion, other-oa)
- Zurich Open Repository and Archive (University of Zurich)
- Funders
- Wellcome Trust (091593)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- dynamic causal modeling, Granger causality, effective connectivity, functional MRI, BOLD contrast
- MeSH terms
- Brain, Brain Mapping, Humans, Magnetic Resonance Imaging, Models, Neurological, Models, Theoretical, History, 20th Century, History, 21st Century
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