A DCM for resting state fMRI
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This technical note introduces a dynamic causal model (DCM) for resting state fMRI time series based upon observed functional connectivity--as measured by the cross spectra among different brain regions. This DCM is based upon a deterministic model that generates predicted crossed spectra from a biophysically plausible model of coupled neuronal fluctuations in a distributed neuronal network or graph. Effectively, the resulting scheme finds the best effective connectivity among hidden neuronal states that explains the observed functional connectivity among haemodynamic responses. This is because the cross spectra contain all the information about (second order) statistical dependencies among regional dynamics. In this note, we focus on describing the model, its relationship to existing measures of directed and undirected functional connectivity and establishing its face validity using simulations. In subsequent papers, we will evaluate its construct validity in relation to stochastic DCM and its predictive validity in Parkinson's and Huntington's disease.
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Extensions of DCM to the frequency domain allow for inference on connectivity from measurements during unconstrained cognition (resting state).
“Similarly, extensions to the frequency domain allow for inference on connectivity from measurements during unconstrained cognition (also known as “resting state”) (Friston et al., 2014a).”
From Allostatic Self-efficacy: A Metacognitive Theory of Dyshomeostasis-Induced Fatigue and Depression (2016) · cites this paper as Friston et al., 2014a
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Cites
Functional connectivity in the motor cortex of resting human brain using echo‐planar mri
Biswal, B., Zerrin Yetkin, F., Haughton, V. M., & Hyde, J. S. (1995) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910340409 · Cited by 9,812 · see citing works
Self-citationTracking whole-brain connectivity dynamics in the resting state
Allen, E. A., Damaraju, E., Plis, S. M., Erhardt, E. B., Eichele, T., & Calhoun, V. D. (2014) · Cerebral Cortex · doi:10.1093/cercor/bhs352 · Cited by 2,992 · see citing works
Canonical Microcircuits for Predictive Coding
Bastos, A. M., Usrey, W. M., Adams, R. A., Mangun, G. R., Fries, P., & Friston, K. J. (2012) · Neuron · doi:10.1016/j.neuron.2012.10.038 · Cited by 2,421 · cited 1× · see citing works
“Theoretically, this is consistent with predictive coding, where top-down predictions suppress prediction errors in lower levels of a hierarchy (Bastos et al., 2012).”
ResultSelf-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-citationForward and backward connections in the brain: a DCM study of functional asymmetries
Chen, C. C., Henson, R. N., Stephan, K. E., Kilner, J. M., & Friston, K. J. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.12.041 · Cited by 109 · see citing works
Flagged first, then by citations
Research works printed but not linked: 29
- Angelucci A. Bressloff P.C. Contribution of feedforward, lateral and feedback connections to the classical receptive field center and extra-classical receptive field surround of primate V1 neurons Prog. Brain Res. 154 2006 93 120 17010705
- Angelucci A. Bullier J. Reaching beyond the classical receptive field of V1 neurons: horizontal or feedback axons? J. Physiol. Paris 97 2003 141 154 14766139
- Beal M.J. Variational Algorithms for Approximate Bayesian Inference 2003 University College London (PhD. Thesis)
- Biswal B.B. Van Kylen J. Hyde J.S. Simultaneous assessment of flow and BOLD signals in resting-state functional connectivity maps NMR Biomed. 165–70 4–5 1997 10 9430343
- Breakspear M. Dynamic connectivity in neural systems: theoretical and empirical considerations Neuroinformatics 2 2 2004 205 226 15319517
- Breakspear M. Stam C.J. Dynamics of a neural system with a multiscale architecture Philos. Trans. R. Soc. Lond. B Biol. Sci. 360 1457 2005 1051 1074 16087448 PMC1854927
- Brown E. Moehlis J. Holmes P. On the phase reduction and response dynamics of neural oscillator populations Neural Comput. 16 2004 673 715 15025826
- Bullmore E. Sporns O. Complex brain networks: graph theoretical analysis of structural and functional systems Nat. Rev. Neurosci. 10 3 2009 186 198 19190637
- Bullmore E. Long C. Suckling J. Fadili J. Calvert G. Zelaya F. Carpenter T.A. Brammer M. Colored noise and computational inference in neurophysiological (fMRI) time series analysis: resampling methods in time and wavelet domains Hum. Brain Mapp. 12 2 2001 61 78 11169871 PMC6871881
- Buxton R.B. Wong E.C. Frank L.R. Dynamics of blood flow and oxygenation changes during brain activation: the Balloon model Magn. Res. Med. 39 1998 855 864 9621908
- Carr J. Applications of Centre Manifold Theory 1981 Springer-Verlag Berlin
- Damoiseaux J.S. Greicius M.D. Greater than the sum of its parts: a review of studies combining structural connectivity and resting-state functional connectivity Brain Struct. Funct. 213 6 2009 525 533 19565262
- Di X. Biswal B.B. Identifying the default mode network structure using dynamic causal modeling on resting-state functional magnetic resonance imaging Neuroimage 86 2014 53 59 23927904 PMC3947265
- Friston K.J. Harrison L. Penny W. Dynamic causal modelling Neuroimage 19 2003 1273 1302 12948688
- Friston K. Mattout J. Trujillo-Barreto N. Ashburner J. Penny W. Variational free energy and the Laplace approximation Neuroimage 34 1 2007 220 234 17055746
- Friston K.J. Li B. Daunizeau J. Stephan K. Network discovery with DCM Neuroimage 56 3 2011 1202 1221 21182971 PMC3094760
- Friston K.J. Bastos A. Litvak V. Stephan E.K. Fries P. Moran R.J. DCM for complex-valued data: cross-spectra, coherence and phase-delays Neuroimage 59 1 2012 439 455 21820062 PMC3200431
- Friston K. Moran R. Seth A.K. Analysing connectivity with Granger causality and dynamic causal modelling Curr. Opin. Neurobiol. 23 2 2013 172 178 23265964 PMC3925802
- Goebel R. Roebroeck A. Kim D.S. Formisano E. Investigating directed cortical interactions in time-resolved fMRI data using vector autoregressive modeling and Granger causality mapping Magn. Reson. Imaging 21 10 2003 1251 1261 14725933
- Haken H. Synergetics: an introduction Non-equilibrium Phase Transition and Self-selforganisation in Physics, Chemistry and Biology 3rd edn 1983 Springer Verlag Berlin
- Harrison L.M. Penny W. Friston K.J. Multivariate autoregressive modeling of fMRI time series Neuroimage 19 2003 1477 1491 12948704
- Kloeden P.E. Platen E. Numerical Solution to Stochastic Differential Equations 1999 Springer New York
- Li B. Daunizeau J. Stephan E.K. Penny W.D.H. Friston K. Generalised filtering and stochastic DCM for fMRI Neuroimage 58 2 2011 442 457 21310247
- Marreiros A.C. Kiebel S.J. Friston K.J. Dynamic causal modelling for fMRI: a two-state model Neuroimage 39 1 2008 269 278 17936017
- Robinson P.A. Rennie C.J. Rowe D.L. O'Connor S.C. Estimation of multiscale neurophysiologic parameters by electroencephalographic means Hum Brain Mapp 23 1 2004 53 72 15281141 PMC6871818
- Seghier M.L. Friston K.J. Network discovery with large DCMs Neuroimage 68 2013 181 191 23246991 PMC3566585
- Shin C.W. Kim S. Self-organized criticality and scale-free properties in emergent functional neural networks Phys. Rev. E Stat. Nonlinear Soft Matter Phys. 74 2006 45101 (no. 4 Pt 2) 17155118
- Stam C.J. de Bruin E.A. Scale-free dynamics of global functional connectivity in the human brain Hum. Brain Mapp. 22 2 2004 97 109 15108297 PMC6871799
- Stephan K.E. Weiskopf N. Drysdale P.M. Robinson P.A. Friston K.J. Comparing hemodynamic models with DCM Neuroimage 38 2007 387 401 17884583 PMC2636182
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Fornito, A., Zalesky, A., & Breakspear, M. (2015) · Nature Reviews Neuroscience · doi:10.1038/nrn3901 · Cited by 1,734 · see citing works
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Stephan, K. E., Manjaly, Z. M., Mathys, C. D., Weber, L. A. E., Paliwal, S., Gard, T., Tittgemeyer, M., Fleming, S. M., Haker, H., Seth, A. K., et al. (2016) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2016.00550 · Cited by 437 · see citing works
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Self-citationOn nodes and modes in resting state fMRI
Friston, K. J., Kahan, J., Razi, A., Stephan, K. E., & Sporns, O. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.05.056 · Cited by 85 · see citing works
Self-citationRay, D., Bezmaternykh, D., Mel’nikov, M., Friston, K. J., & Das, M. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2105730118 · Cited by 73 · see citing works
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Admon, R., & Pizzagalli, D. A. (2015) · Nature Communications · doi:10.1038/ncomms10065 · Cited by 57 · see citing works
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Fridgeirsson, E. A., Figee, M., Luigjes, J., van den Munckhof, P., Schuurman, P. R., van Wingen, G., & Denys, D. (2020) · Brain · doi:10.1093/brain/awaa100 · Cited by 51 · see citing works
Jamieson, A. J., Harrison, B. J., Razi, A., & Davey, C. G. (2022) · Neuropsychopharmacology · doi:10.1038/s41386-021-01214-z · Cited by 41 · see citing works
Self-citationThomas, G. E. C., Zeidman, P., Sultana, T., Zarkali, A., Razi, A., & Weil, R. S. (2022) · Brain Communications · doi:10.1093/braincomms/fcac329 · Cited by 38 · see citing works
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- Authors
- Friston, K. J., Kahan, J., Biswal, B., & Razi, A.
- Affiliations
- Wellcome Centre for Human Neuroimaging (GB)
- National Hospital for Neurology and Neurosurgery (GB)
- NED University of Engineering and Technology (PK)
- Corresponding author
- Friston, Karl J.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2014-07
- Volume
- 94
- Pages
- 396-407
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC4073651
- OpenAlex
- W2015822010
- Cited by
- 553
- References
- 5
- Citations by year
- 2026: 29 · 2025: 62 · 2024: 61 · 2023: 63 · 2022: 55 · 2021: 63 · 2020: 42 · 2019: 40 · 2018: 40 · 2017: 36 · 2016: 28 · 2015: 27 · 2014: 6
- FWCI
- 11.15
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- NeuroImage (publishedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- Wellcome Trust
- 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
- dynamic causal modeling, resting-state fMRI, functional connectivity, cross-spectral analysis, effective connectivity, directed functional connectivity, hemodynamic response, Parkinson's disease, Huntington's disease
- MeSH terms
- Algorithms, Attention, Brain Mapping, Computer Simulation, Data Interpretation, Statistical, Humans, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Motion Perception, Rest, Sensitivity and Specificity, Visual Cortex, Reproducibility of Results, Models, Statistical
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