Dynamic causal modeling of evoked responses in EEG and MEG
Open accessAbstract
Neuronally plausible, generative or forward models are essential for understanding how event-related fields (ERFs) and potentials (ERPs) are generated. In this paper, we present a new approach to modeling event-related responses measured with EEG or MEG. This approach uses a biologically informed model to make inferences about the underlying neuronal networks generating responses. The approach can be regarded as a neurobiologically constrained source reconstruction scheme, in which the parameters of the reconstruction have an explicit neuronal interpretation. Specifically, these parameters encode, among other things, the coupling among sources and how that coupling depends upon stimulus attributes or experimental context. The basic idea is to supplement conventional electromagnetic forward models, of how sources are expressed in measurement space, with a model of how source activity is generated by neuronal dynamics. A single inversion of this extended forward model enables inference about both the spatial deployment of sources and the underlying neuronal architecture generating them. Critically, this inference covers long-range connections among well-defined neuronal subpopulations. In a previous paper, we simulated ERPs using a hierarchical neural-mass model that embodied bottom-up, top-down and lateral connections among remote regions. In this paper, we describe a Bayesian procedure to estimate the parameters of this model using empirical data. We demonstrate this procedure by characterizing the role of changes in cortico-cortical coupling, in the genesis of ERPs. In the first experiment, ERPs recorded during the perception of faces and houses were modeled as distinct cortical sources in the ventral visual pathway. Category-selectivity, as indexed by the face-selective N170, could be explained by category-specific differences in forward connections from sensory to higher areas in the ventral stream. We were able to quantify and make inferences about these effects using conditional estimates of connectivity. This allowed us to identify where, in the processing stream, category-selectivity emerged. In the second experiment, we used an auditory oddball paradigm to show that the mismatch negativity can be explained by changes in connectivity. Specifically, using Bayesian model selection, we assessed changes in backward connections, above and beyond changes in forward connections. In accord with theoretical predictions, there was strong evidence for learning-related changes in both forward and backward coupling. These examples show that category- or context-specific coupling among cortical regions can be assessed explicitly, within a mechanistic, biologically motivated inference framework.
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DCM has also been formulated for M/EEG data, serving to explain a variety of data features such as event-related potentials, induced responses, or steady-state responses.
“DCM has also been formulated for M/EEG data, serving to explain a variety of data features such as event-related potentials (David et al., 2006), induced responses (Chen et al., 2008), or steady-state responses (Moran et al., 2009).”
From Allostatic Self-efficacy: A Metacognitive Theory of Dyshomeostasis-Induced Fatigue and Depression (2016) · cites this paper as David et al., 2006
DCMs have been implemented for a range of measurement techniques other than fMRI, including EEG, MEG, and LFPs, both in the time domain and frequency domain.
“Dynamic causal models (DCMs)1 have also been implemented for a range of measurement techniques other than fMRI, including electroencephalography (EEG), magnetoencephalography (MEG), and local field potentials (LFPs) obtained from invasive recordings in humans or animals, both in the time domain (Daunizeau et al., 2009b; David et al., 2006; Kiebel et al., 2006) and frequency domain (Chen et al., 2”
From Ten simple rules for dynamic causal modeling (2010) · cites this paper as David et al., 2006
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Cites
Press, W. H., Teukolsky, S. A., Vetterling, W. T., & Flannery, B. P. (1994) · Cited by 15,411 · see citing works
Distributed hierarchical processing in the primate cerebral cortex
Felleman, D. J., & Van Essen, D. C. (1991) · Cerebral Cortex · doi:10.1093/cercor/1.1.1 · Cited by 7,783 · see citing works
Numerical Solution of Stochastic Differential Equations
Kloeden, P. E., & Platen, E. (1992) · Springer eBooks · doi:10.1007/978-3-662-12616-5 · Cited by 5,131 · see citing works
Numerical solution of stochastic differential equations
Kloeden, P. E. 1., & Platen, E. (2016) · doi:10.5194/gmd-2016-45-rc1 · Cited by 5,119 · see citing works
Friston, K. J., Harrison, L., & Penny, W. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00202-7 · Cited by 4,583 · see citing works
Self-citationDistributed and overlapping representations of faces and objects in ventral temporal cortex
Haxby, J. V., Gobbini, M. I., Furey, M. L., Ishai, A., Schouten, J. L., & Pietrini, P. (2001) · Science · doi:10.1126/science.1063736 · Cited by 3,940 · see citing works
Dynamic predictions: Oscillations and synchrony in top–down processing
Engel, A. K., Fries, P., & Singer, W. (2001) · Nature Reviews Neuroscience · doi:10.1038/35094565 · Cited by 3,454 · see citing works
Preface: Cerebral Cortex Has Come of Age
Goldman, P. S., & RAKIC, P. T. (1991) · Cerebral Cortex · doi:10.1093/cercor/1.1.1-a · Cited by 3,412 · see citing works
A cortical representation of the local visual environment
Epstein, R. A., & Kanwisher, N. (1998) · Nature · doi:10.1038/33402 · Cited by 2,960 · see citing works
Effects of Attention and Emotion on Face Processing in the Human Brain
Vuilleumier, P., Armony, J. L., Driver, J., & Dolan, R. J. (2001) · Neuron · doi:10.1016/s0896-6273(01)00328-2 · Cited by 1,664 · see citing works
Human neural systems for face recognition and social communication
Haxby, J. V., Hoffman, E. A., & Gobbini, M. I. (2002) · Biological Psychiatry · doi:10.1016/s0006-3223(01)01330-0 · Cited by 1,287 · see citing works
Normal and pathological oscillatory communication in the brain
Schnitzler, A., & Groß, J. (2005) · Nature reviews. Neuroscience · doi:10.1038/nrn1650 · Cited by 1,229 · see citing works
Jansen, B. H., & Rit, V. G. (1995) · Biological Cybernetics · doi:10.1007/bf00199471 · Cited by 1,159 · see citing works
Dual streams of auditory afferents target multiple domains in the primate prefrontal cortex
Romanski, L. M., Tian, B., Fritz, J. B., Mishkin, M., Goldman, P. S., & Rauschecker, J. P. (1999) · Nature Neuroscience · doi:10.1038/16056 · Cited by 1,136 · see citing works
Brovelli, A., Ding, M., Ledberg, A., Chen, Y., Nakamura, R., & Bressler, S. L. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0308538101 · Cited by 1,065 · see citing works
Processing of low-probability sounds by cortical neurons
Ulanovsky, N., Las, L., & Nelken, I. (2003) · Nature Neuroscience · doi:10.1038/nn1032 · Cited by 1,049 · see citing works
Mapping directed influence over the brain using Granger causality and fMRI
Roebroeck, A. F., Formisano, E., & Goebel, R. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2004.11.017 · Cited by 1,024 · see citing works
Subdivisions of auditory cortex and processing streams in primates
Kaas, J. H., & Hackett, T. A. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.97.22.11793 · Cited by 999 · see citing works
Distributed representation of objects in the human ventral visual pathway
Ishai, A., Ungerleider, L. G., Martin, A. D., Schouten, J. L., & Haxby, J. V. (1999) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.96.16.9379 · Cited by 885 · see citing works
Allison, T. (1999) · Cerebral Cortex · doi:10.1093/cercor/9.5.415 · Cited by 882 · see citing works
Comparing dynamic causal models.
Penny, W. D., Stephan, K. E., Mechelli, A., & Friston, K. J. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.03.026 · Cited by 848 · see citing works
Self-citationEEG and MEG: forward solutions for inverse methods
Mosher, J. C., Leahy, R. M., & Lewis, P. S. (1999) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.748978 · Cited by 845 · see citing works
Büchel, C. (1997) · Cerebral Cortex · doi:10.1093/cercor/7.8.768 · Cited by 794 · see citing works
Model of brain rhythmic activity
Lopes, F. H. D. S., Hoeks, A. P. G., Smits, H., & Zetterberg, L. H. (1974) · Kybernetik · doi:10.1007/bf00270757 · Cited by 734 · see citing works
Learning and inference in the brain
Friston, K. (2003) · Neural Networks · doi:10.1016/j.neunet.2003.06.005 · Cited by 724 · see citing works
Self-citationA neural mass model for MEG/EEG:
Olivier David, A., & Friston, K. J. (2003) · NeuroImage · doi:10.1016/j.neuroimage.2003.07.015 · Cited by 705 · see citing works
Self-citationEpileptic fast activity can be explained by a model of impaired GABAergic dendritic inhibition
Wendling, F., Bartoloméi, F., Bellanger, J.-J., & Chauvel, P. (2002) · European Journal of Neuroscience · doi:10.1046/j.1460-9568.2002.01985.x · Cited by 638 · see citing works
The Functional Neuroanatomy of Target Detection: An fMRI Study of Visual and Auditory Oddball Tasks
Linden, D. E. J. (1999) · Cerebral Cortex · doi:10.1093/cercor/9.8.815 · Cited by 512 · see citing works
An Area within Human Ventral Cortex Sensitive to “Building” Stimuli
Aguirre, G. K., Zarahn, E., & D’Esposito, M. (1998) · Neuron · doi:10.1016/s0896-6273(00)80546-2 · Cited by 477 · see citing works
Multivariate autoregressive modeling of fMRI time series
Harrison, L. M., Penny, W. D., & Friston, K. J. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00160-5 · Cited by 378 · see citing works
Self-citationPrediction of electroencephalographic spectra from neurophysiology
Robinson, P. A., RENNIE, C. J., Wright, J. J., Bahramali, H., Gordon, E., & ROWE, D. L. (2001) · Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics · doi:10.1103/physreve.63.021903 · Cited by 366 · see citing works
Mangin, J.-F., Frouin, V., Isabelle Bloch, A., R�gis, J., & L�pez-Krahe, J. (1995) · Journal of Mathematical Imaging and Vision · doi:10.1007/bf01250286 · Cited by 354 · see citing works
Constraints on cortical and thalamic projections: the no-strong-loops hypothesis
Crick, F., & Koch, C. (1998) · Nature · doi:10.1038/34584 · Cited by 353 · cited 1× · see citing works
“The cortex has a hierarchical organization (Crick and Koch, 1998; Felleman and Van Essen, 1991), comprising forward, backward and lateral processes that can be understood from an anatomical and cognitive perspective (Engel et al.”
Bayesian Estimation of Dynamical Systems: An Application to fMRI
Friston, K. J. (2002) · NeuroImage · doi:10.1006/nimg.2001.1044 · Cited by 310 · see citing works
Self-citationModelling event-related responses in the brain
Olivier David, A., Harrison, L. M., & Friston, K. J. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2004.12.030 · Cited by 299 · see citing works
Self-citationGenerators of the brainstem auditory evoked potential in cat III: identified cell populations
Melcher, J. R., & Kiang, N. Y. S. (1996) · Hearing Research · doi:10.1016/0378-5955(95)00200-6 · Cited by 290 · see citing works
A spatially continuous mean field theory of electrocortical activity
Liley, D. T. J., Cadusch, P. J., & Dafilis, M. P. (2002) · Network Computation in Neural Systems · doi:10.1080/net.13.1.67.113 · Cited by 261 · see citing works
Dynamics of the human alpha rhythm: evidence for non-linearity?
Stam, C. J., Pijn, J. P. M., Suffczyński, P., & Lopes, F. H. D. S. (1999) · Clinical Neurophysiology · doi:10.1016/s1388-2457(99)00099-1 · Cited by 258 · see citing works
Estimation of multiscale neurophysiologic parameters by electroencephalographic means
Robinson, P. A., RENNIE, C. J., ROWE, D. L., & O’Connor, S. C. (2004) · Human Brain Mapping · doi:10.1002/hbm.20032 · Cited by 244 · see citing works
Unified neurophysical model of EEG spectra and evoked potentials
RENNIE, C. J., Robinson, P. A., & Wright, J. J. (2002) · Biological Cybernetics · doi:10.1007/s00422-002-0310-9 · Cited by 238 · see citing works
Dynamic causal modelling of evoked responses in EEG/MEG with lead field parameterization
Kiebel, S. J., David, O., & Friston, K. J. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2005.12.055 · Cited by 233 · see citing works
Self-citationDynamic causal modelling of evoked potentials: A reproducibility study
Garrido, M. I., Kilner, J. M., Kiebel, S. J., Stephan, K. E., & Friston, K. J. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.03.014 · Cited by 233 · see citing works
Self-citationA state-space model of the hemodynamic approach: nonlinear filtering of BOLD signals
Riera, J. J., Watanabe, J., Iwata, K., Miura, N., Aubert, E., Ozaki, T., & Kawashima, R. (2003) · NeuroImage · doi:10.1016/j.neuroimage.2003.09.052 · Cited by 186 · see citing works
A critical analysis of linear inverse solutions to the neuroelectromagnetic inverse problem
de Peralta-Menendez, R. G., & Andino, S. L. G. (1998) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.664200 · Cited by 175 · see citing works
Debener, S., Kranczioch, C., Herrmann, C. S., & Engel, A. K. (2002) · International Journal of Psychophysiology · doi:10.1016/s0167-8760(02)00072-7 · Cited by 135 · see citing works
Smith, P. H., & Populin, L. C. (2001) · The Journal of Comparative Neurology · doi:10.1002/cne.1084 · Cited by 128 · see citing works
Dau, T. (2003) · The Journal of the Acoustical Society of America · doi:10.1121/1.1534833 · Cited by 115 · see citing works
McIntosh, A. R., & Gonzalez-Lima, F. (1994) · Journal of Neurophysiology · doi:10.1152/jn.1994.72.4.1717 · Cited by 114 · see citing works
Olivier David, A., Garnero, L., Cosmelli, D. J., & Varela, F. J. (2002) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2002.802013 · Cited by 81 · see citing works
Locking-Based Frequency Measurement and Synchronization of Chaotic Oscillators with Complex Dynamics
Rosenblum, M., PIKOVSKY, A. S., Kurths, J., Osipov, G. V., Kiss, I. Z., & Hudson, J. L. (2002) · Physical Review Letters · doi:10.1103/physrevlett.89.264102 · Cited by 67 · see citing works
Jirsa, V. (2004) · International Journal of Bifurcation and Chaos · doi:10.1142/s0218127404009375 · Cited by 17 · see citing works
Transmission of stimulus-locked responses in two oscillators with bistable coupling
Tass, P. A. (2004) · Biological Cybernetics · doi:10.1007/s00422-004-0512-4 · Cited by 12 · see citing works
Flagged first, then by citations
1 of the 53 references couldn’t be matched to a known paper.
Cited by
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A theory of cortical responses.
Friston, K. (2005) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2005.1622 · Cited by 4,578 · see citing works
Self-citationFunctional and Effective Connectivity: A Review
Friston, K. J. (2011) · Brain Connectivity · doi:10.1089/brain.2011.0008 · Cited by 3,415 · see citing works
Self-citationCanonical 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 · see citing works
Self-citationThe mismatch negativity: a review of underlying mechanisms
Garrido, M. I., Kilner, J. M., Stephan, K. E., & Friston, K. J. (2009) · Clinical Neurophysiology · doi:10.1016/j.clinph.2008.11.029 · Cited by 1,441 · see citing works
Self-citationDysconnection in schizophrenia: from abnormal synaptic plasticity to failures of self-monitoring
Stephan, K. E., Friston, K. J., & Frith, C. D. (2009) · Schizophrenia Bulletin · doi:10.1093/schbul/sbn176 · Cited by 1,134 · see citing works
Self-citationThe dynamic brain: from spiking neurons to neural masses and cortical fields
Deco, G., Jirsa, V. K., Robinson, P. A., Breakspear, M., & Friston, K. (2008) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000092 · Cited by 1,084 · see citing works
Self-citationSynaptic plasticity and dysconnection in schizophrenia
Stephan, K. E., Baldeweg, T., & Friston, K. J. (2006) · Biological Psychiatry · doi:10.1016/j.biopsych.2005.10.005 · Cited by 841 · see citing works
Self-citationVariational free energy and the Laplace approximation
Friston, K., Mattout, J., Trujillo-Barreto, N., Ashburner, J., & Penny, W. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2006.08.035 · Cited by 880 · see citing works
Self-citationTen 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-citationAnalysing connectivity with Granger causality and dynamic causal modelling
Friston, K., Moran, R., & Seth, A. K. (2013) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2012.11.010 · Cited by 684 · see citing works
Self-citationEEG and MEG Data Analysis in SPM8
Vladimir Litvak, A., Mattout, J., Kiebel, S. J., Phillips, C. L. M., Henson, R. N., Kilner, J. M., Barnes, G. R., Oostenveld, R., Jean Daunizeau, A., Flandin, G., et al. (2011) · Computational Intelligence and Neuroscience · doi:10.1155/2011/852961 · Cited by 586 · see citing works
Self-citationPreserved Feedforward But Impaired Top-Down Processes in the Vegetative State
Boly, M., Garrido, M. I., Gosseries, O., Bruno, M., Boveroux, P., Caroline Schnakers, A., Massimini, M., Vladimir Litvak, A., Laureys, S., & Friston, K. J. (2011) · Science · doi:10.1126/science.1202043 · Cited by 499 · see citing works
Self-citationPerceptions as Hypotheses: Saccades as Experiments
Friston, K., Adams, R. A., Perrinet, L., & Breakspear, M. (2012) · Frontiers in Psychology · doi:10.3389/fpsyg.2012.00151 · Cited by 462 · see citing works
Self-citationAllostatic Self-efficacy: A Metacognitive Theory of Dyshomeostasis-Induced Fatigue and Depression
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
The functional anatomy of the MMN: a DCM study of the roving paradigm
Garrido, M. I., Friston, K. J., Kiebel, S. J., Stephan, K. E., Baldeweg, T., & Kilner, J. M. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.05.018 · Cited by 458 · see citing works
Self-citationComparing hemodynamic models with DCM
Stephan, K. E., Weiskopf, N., Drysdale, P. M., Robinson, P. A., & Friston, K. J. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.07.040 · Cited by 441 · see citing works
Self-citationCausal Modelling and Brain Connectivity in Functional Magnetic Resonance Imaging
Friston, K. J. (2009) · PLoS Biology · doi:10.1371/journal.pbio.1000033 · Cited by 444 · see citing works
Self-citationNonlinear dynamic causal models for fMRI
Stephan, K. E., Kasper, L., Harrison, L. M., Daunizeau, J., den Ouden, H. E. M., Breakspear, M., & Friston, K. J. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.04.262 · Cited by 416 · see citing works
Self-citationMEG: An Introduction to Methods
(2010) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195307238.001.0001 · Cited by 411 · see citing works
VBA: A Probabilistic Treatment of Nonlinear Models for Neurobiological and Behavioural Data
Daunizeau, J., Adam, V., & Rigoux, L. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003441 · Cited by 385 · see citing works
Dynamic causal modelling: A critical review of the biophysical and statistical foundations
Daunizeau, J., David, O., & Stephan, K. E. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2009.11.062 · Cited by 331 · see citing works
Mechanisms of evoked and induced responses in MEG/EEG
Olivier David, A., Kilner, J. M., & Friston, K. J. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.02.034 · Cited by 339 · see citing works
Self-citationA Dual Role for Prediction Error in Associative Learning
den Ouden, H. E. M., Friston, K. J., Daw, N. D., McIntosh, A. R., & Stephan, K. E. (2009) · Cerebral Cortex · doi:10.1093/cercor/bhn161 · Cited by 306 · see citing works
Self-citationBabiloni, C., Barry, R. J., Başar, E., Blinowska, K. J., Cichocki, A. S., Drinkenburg, W. H. I. M., Klimesch, W., Knight, R. T., Lopes, F. H. D. S., Nunez, P. L., et al. (2019) · Clinical Neurophysiology · doi:10.1016/j.clinph.2019.06.234 · Cited by 322 · see citing works
Free Energy, Precision and Learning: The Role of Cholinergic Neuromodulation
Moran, R. J., Campo, P., Symmonds, M., Stephan, K. E., Dolan, R. J., & Friston, K. J. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.4255-12.2013 · Cited by 312 · see citing works
Self-citationEvoked brain responses are generated by feedback loops
Garrido, M. I., Kilner, J. M., Kiebel, S. J., & Friston, K. J. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0706274105 · Cited by 296 · see citing works
Self-citationComputational approaches to psychiatry
Stephan, K. E., & Mathys, C. (2014) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2013.12.007 · Cited by 260 · see citing works
Dynamic causal modelling revisited
Friston, K. J., Preller, K. H., Mathys, C., Cagnan, H., Heinzle, J., Razi, A., & Zeidman, P. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2017.02.045 · Cited by 271 · see citing works
Self-citationQuinn, C. J., Coleman, T. P., Kiyavash, N., & Hatsopoulos, N. G. (2010) · Journal of Computational Neuroscience · doi:10.1007/s10827-010-0247-2 · Cited by 274 · see citing works
Impaired pitch perception and memory in congenital amusia: the deficit starts in the auditory cortex
Albouy, P., Mattout, J., Bouet, R., Maby, E., Sanchez, G., Aguera, P., Daligault, S., Delpuech, C., Bertrand, O., Caclin, A., et al. (2013) · Brain · doi:10.1093/brain/awt082 · Cited by 269 · see citing works
Self-citationTMS combined with EEG: Recommendations and open issues for data collection and analysis
Hernandez-Pavon, J. C., Veniero, D., Bergmann, T. O., Belardinelli, P., Bortoletto, M., Casarotto, S., Casula, E. P., Farzan, F., Fecchio, M., Julkunen, P., et al. (2023) · Brain Stimulation · doi:10.1016/j.brs.2023.02.009 · Cited by 238 · see citing works
Multivariate Statistical Analyses for Neuroimaging Data
McIntosh, A. R., & Mišić, B. (2012) · Annual Review of Psychology · doi:10.1146/annurev-psych-113011-143804 · Cited by 253 · see citing works
Neural masses and fields in dynamic causal modeling
Moran, R., Pinotsis, D. A., & Friston, K. (2013) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2013.00057 · Cited by 255 · see citing works
Self-citationA Bayesian framework for global tractography
Jbabdi, S., Woolrich, M. W., Andersson, J., & Behrens, T. E. J. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.04.039 · Cited by 251 · see citing works
Brain functional and effective connectivity based on electroencephalography recordings: A review
Cao, J. H., Zhao, Y., Shan, X., Wei, H., Guo, Y., Chen, L., Erkoyuncu, J. A., & Sarrigiannis, P. G. (2021) · Human Brain Mapping · doi:10.1002/hbm.25683 · Cited by 244 · see citing works
Dynamic causal modelling of evoked responses in EEG/MEG with lead field parameterization
Kiebel, S. J., David, O., & Friston, K. J. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2005.12.055 · Cited by 233 · see citing works
Self-citationMuthukumaraswamy, S. D., Shaw, A. D., Jackson, L. E., Hall, J., Moran, R., & Saxena, N. K. (2015) · Journal of Neuroscience · doi:10.1523/jneurosci.0903-15.2015 · Cited by 230 · see citing works
Dynamic causal modelling of evoked potentials: A reproducibility study
Garrido, M. I., Kilner, J. M., Kiebel, S. J., Stephan, K. E., & Friston, K. J. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.03.014 · Cited by 233 · see citing works
Self-citationStatistical testing in electrophysiological studies
Maris, E. (2011) · Psychophysiology · doi:10.1111/j.1469-8986.2011.01320.x · Cited by 233 · see citing works
Waking and dreaming consciousness: neurobiological and functional considerations.
Hobson, J. A., & Friston, K. J. (2012) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2012.05.003 · Cited by 287 · see citing works
Self-citationRepetition suppression and plasticity in the human brain
Garrido, M. I., Kilner, J. M., Kiebel, S. J., Stephan, K. E., Baldeweg, T., & Friston, K. J. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.06.034 · Cited by 223 · see citing works
Self-citationDynamic causal models of neural system dynamics: current state and future extensions
Stephan, K. E., Harrison, L. M., Kiebel, S. J., Olivier David, A., Penny, W. D., & Friston, K. J. (2007) · Journal of Biosciences · doi:10.1007/s12038-007-0012-5 · Cited by 222 · see citing works
Self-citationA neural mass model of spectral responses in electrophysiology
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Kiebel, S. J., Garrido, M. I., Moran, R. J., & Friston, K. J. (2008) · Cognitive Neurodynamics · doi:10.1007/s11571-008-9038-0 · Cited by 211 · see citing works
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Self-citationWibral, M., Rahm, B., Rieder, M., Lindner, M., Vicente, R., & Kaiser, J. (2010) · Progress in Biophysics and Molecular Biology · doi:10.1016/j.pbiomolbio.2010.11.006 · Cited by 187 · see citing works
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Jones, S. R., Pritchett, D. L., Stufflebeam, S. M., Hämäläinen, M., & Moore, C. I. (2007) · The Journal of Neuroscience · doi:10.1523/jneurosci.0482-07.2007 · Cited by 160 · see citing works
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Stephan, K. E., Schlagenhauf, F., Huys, Q. J. M., Raman, S., Aponte, E. A., Brodersen, K. H., Rigoux, L., Moran, R., Jean Daunizeau, A., Dolan, R. J., et al. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.06.038 · Cited by 166 · see citing works
Self-citationMcCormick, C., Ciaramelli, E., Luca, F. D., & Maguire, E. A. (2017) · Neuroscience · doi:10.1016/j.neuroscience.2017.07.066 · Cited by 159 · see citing works
TAPAS: An Open-Source Software Package for Translational Neuromodeling and Computational Psychiatry
Frässle, S., Aponte, E. A., Bollmann, S., Brodersen, K. H., Do, C. T., Harrison, O. K., Harrison, S. J., Heinzle, J., Iglesias, S., Kasper, L., et al. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.680811 · Cited by 169 · see citing works
Methods for analysis of brain connectivity: An IFCN-sponsored review
Rossini, P. M., Iorio, R. D., Bentivoglio, M., Bertini, G., Ferreri, F., Gerloff, C. P., Ilmoniemi, R. J., Miraglia, F., Nitsche, M. A., Pestilli, F., et al. (2019) · Clinical Neurophysiology · doi:10.1016/j.clinph.2019.06.006 · Cited by 165 · see citing works
Bastos, A. M., Litvak, V., Moran, R., Bosman, C. A., Fries, P., & Friston, K. J. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.12.081 · Cited by 152 · see citing works
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Rudrauf, D., Olivier David, A., Lachaux, J.-P., Kovach, C. K., Martinerie, J. M., Renault, B., & Damásio, A. R. (2008) · Journal of Neuroscience · doi:10.1523/jneurosci.3476-07.2008 · Cited by 145 · see citing works
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Sotero, R. C., & Trujillo‐Barreto, N. J. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.08.001 · Cited by 137 · see citing works
(2019) · Handbook of clinical neurology · doi:10.1016/b978-0-444-64032-1.00006-0 · Cited by 134 · see citing works
Friston, K. J., Bastos, A. M., Oswal, A., van Wijk, B. C. M., Richter, C. G., & Vladimir Litvak, A. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.06.062 · Cited by 133 · see citing works
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Friston, K. J., & Dolan, R. J. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.12.068 · Cited by 131 · see citing works
Self-citationHashemi, M., Vattikonda, A. N., Ší́p, V., Guye, M., Bartoloméi, F., Woodman, M., & Jirsa, V. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116839 · Cited by 131 · see citing works
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Kimura, M. (2011) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2011.11.010 · Cited by 130 · see citing works
Lu, Q., Li, H., Luo, G., Wang, Y., Tang, H., Han, L., & Yao, Z. (2012) · Neuroscience Letters · doi:10.1016/j.neulet.2012.06.058 · Cited by 129 · see citing works
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McFadyen, J., Mermillod, M., Mattingley, J. B., Halász, V., & Garrido, M. I. (2017) · Journal of Neuroscience · doi:10.1523/jneurosci.3525-16.2017 · Cited by 130 · see citing works
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Federmeier, K. D. (2021) · Psychophysiology · doi:10.1111/psyp.13940 · Cited by 129 · see citing works
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Kiebel, S. J., Garrido, M. I., & Friston, K. J. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.02.046 · Cited by 127 · see citing works
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Lohmann, G., Erfurth, K., Müller, K., & Turner, R. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.09.025 · Cited by 125 · see citing works
Chennu, S., Noreika, V., Gueorguiev, D., Shtyrov, Y., Bekinschtein, T. A., & Henson, R. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.1125-16.2016 · Cited by 107 · see citing works
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Leff, A. P., Schofield, T. M., Stephan, K. E., Crinion, J. T., Friston, K. J., & Price, C. J. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.2903-08.2008 · Cited by 123 · see citing works
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Dima, D., Dietrich, D. E., Dillo, W., & Emrich, H. M. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.12.086 · Cited by 122 · see citing works
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Spiegler, A., Knösche, T. R., Schwab, K., Haueisen, J., & Atay, F. M. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002298 · Cited by 113 · see citing works
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Henson, R. N., Flandin, G., Friston, K. J., & Mattout, J. (2010) · Human Brain Mapping · doi:10.1002/hbm.20956 · Cited by 117 · see citing works
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Auksztulewicz, R., Spitzer, B., & Blankenburg, F. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.3974-11.2012 · Cited by 112 · see citing works
Current perspectives and methods in studying neural mechanisms of multisensory interactions
Klemen, J., & Chambers, C. (2011) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2011.04.015 · Cited by 112 · see citing works
Subcortical amygdala pathways enable rapid face processing
Garvert, M. M., Friston, K. J., Dolan, R. J., & Garrido, M. I. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.07.047 · Cited by 111 · see citing works
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Frässle, S., Lomakina, E. I., Kasper, L., Manjaly, Z. M., Leff, A. P., Pruessmann, K. P., Buhmann, J. M., & Stephan, K. E. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.05.058 · Cited by 104 · see citing works
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Schmidt, A., Diaconescu, A. O., Kometer, M., Friston, K. J., Stephan, K. E., & Vollenweider, F. X. (2013) · Cerebral Cortex · doi:10.1093/cercor/bhs238 · Cited by 109 · see citing works
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Cho, J., Vorwerk, J., Wolters, C. H., & Knösche, T. R. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.01.043 · Cited by 110 · see citing works
Functional Evidence for a Dual Route to Amygdala
Garrido, M. I., Barnes, G. R., Sahani, M., & Dolan, R. J. (2011) · Current Biology · doi:10.1016/j.cub.2011.11.056 · Cited by 110 · see citing works
Attenuated human auditory middle latency response and evoked 40‐Hz response to self‐initiated sounds
Baess, P., Widmann, A., Roye, A., Schröger, E., & Jacobsen, T. (2009) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2009.06683.x · Cited by 110 · see citing works
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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
- Authors
- David, O., Kiebel, S. J., Harrison, L. M., Mattout, J., Kilner, J. M., & Friston, K. J.
- Affiliations
- UCL Queen Square Institute of Neurology (GB)
- Corresponding author
- Kiebel, Stefan J.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2006-05
- Volume
- 30
- Issue
- 4
- Pages
- 1255-1272
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2053773581
- Cited by
- 620
- References
- 53
- Citations by year
- 2026: 15 · 2025: 25 · 2024: 17 · 2023: 18 · 2022: 28 · 2021: 28 · 2020: 28 · 2019: 55 · 2018: 31 · 2017: 38 · 2016: 32 · 2015: 53 · 2014: 33 · 2013: 30 · 2012: 41
- FWCI
- 12.94
- Type
- journal article
- Language
- en
- Open access
- green
- inserm.hal.science
- Licence
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- HAL (submittedVersion, other-oa)
- UCL Discovery (University College London) (submittedVersion)
- Max Planck Digital Library (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Funders
- Wellcome Trust
- Centre National de la Recherche Scientifique
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- dynamic causal modeling, event-related potentials, event-related fields, corticocortical connections, source localization, Bayesian model selection, N170, face perception, ventral stream, mismatch negativity, auditory oddball paradigm
- MeSH terms
- Auditory Pathways, Bayes Theorem, Brain Mapping, Cerebral Cortex, Electroencephalography, Evoked Potentials, Humans, Nerve Net, Synaptic Transmission, Neurons, Pattern Recognition, Visual, Pitch Perception, Visual Pathways, Magnetoencephalography, Neural Networks, Computer, Nonlinear Dynamics
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