Dynamic causal modelling for EEG and MEG
Open accessAbstract
Dynamic Causal Modelling (DCM) is an approach first introduced for the analysis of functional magnetic resonance imaging (fMRI) to quantify effective connectivity between brain areas. Recently, this framework has been extended and established in the magneto/encephalography (M/EEG) domain. DCM for M/EEG entails the inversion a full spatiotemporal model of evoked responses, over multiple conditions. This model rests on a biophysical and neurobiological generative model for electrophysiological data. A generative model is a prescription of how data are generated. The inversion of a DCM provides conditional densities on the model parameters and, indeed on the model itself. These densities enable one to answer key questions about the underlying system. A DCM comprises two parts; one part describes the dynamics within and among neuronal sources, and the second describes how source dynamics generate data in the sensors, using the lead-field. The parameters of this spatiotemporal model are estimated using a single (iterative) Bayesian procedure. In this paper, we will motivate and describe the current DCM framework. Two examples show how the approach can be applied to M/EEG experiments.
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Dynamic causal modeling, leveraging EEG's temporal precision, enables exploration of these mechanisms.
“Dynamic causal modeling (DCM), leveraging EEG’s temporal precision, enables exploration of these mechanisms21–23.”
From Deviations in effective connectivity explain different hallucination subtypes in Parkinson's disease psychosis (2026) · cites this paper as [21]
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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
EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis
Klimesch, W. (1999) · Brain Research Reviews · doi:10.1016/s0165-0173(98)00056-3 · Cited by 6,889 · 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-citationPreface: 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
Picton, T. W., Bentin, S., Berg, P., Donchin, E., Hillyard, S. A., Johnson, R., Miller, G. A., Ritter, W., Ruchkin, D. S., Rugg, M. D., et al. (2000) · Psychophysiology · doi:10.1111/1469-8986.3720127 · Cited by 2,157 · see citing works
Oscillatory gamma activity in humans and its role in object representation
Tallon‐Baudry, C. (1999) · Trends in Cognitive Sciences · doi:10.1016/s1364-6613(99)01299-1 · Cited by 2,111 · see citing works
Dynamic imaging of coherent sources: studying neural interactions in the human brain
Gross, J., Kujala, J., Hämäläinen, M., Timmermann, L., Schnitzler, A., & Salmelin, R. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.98.2.694 · Cited by 1,810 · see citing works
Baillet, S., Mosher, J. C., & Leahy, R. M. (2001) · IEEE Signal Processing Magazine · doi:10.1109/79.962275 · Cited by 1,691 · see citing works
(2003) · Cited by 1,680 · see citing works
Dynamic Brain Sources of Visual Evoked Responses
Makeig, S., Westerfield, M., Jung, T.-P., Enghoff, S., Townsend, J., Courchesne, E., & Sejnowski, T. J. (2002) · Science · doi:10.1126/science.1066168 · Cited by 1,630 · see citing works
Multivariate Statistical Modelling Based on Generalized Linear Models
Fahrmeir, L., & Tutz, G. (1994) · Springer series in statistics · doi:10.1007/978-1-4899-0010-4 · Cited by 1,413 · see citing works
Event-related potentials and recognition memory
Rugg, M. D., & Curran, T. (2007) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2007.04.004 · Cited by 1,283 · see citing works
Human gamma-frequency oscillations associated with attention and memory
Jensen, O. B., Kaiser, J., & Lachaux, J.-P. (2007) · Trends in Neurosciences · doi:10.1016/j.tins.2007.05.001 · Cited by 1,239 · see citing works
Jansen, B. H., & Rit, V. G. (1995) · Biological Cybernetics · doi:10.1007/bf00199471 · Cited by 1,159 · see citing works
The concept of auditory stimulus representation in cognitive neuroscience.
Näätänen, R., & Winkler, I. (1999) · Psychological Bulletin · doi:10.1037/0033-2909.125.6.826 · Cited by 1,069 · see citing works
Giard, M., Perrin, F., Pernier, J., & Bouchet, P. (1990) · Psychophysiology · doi:10.1111/j.1469-8986.1990.tb03184.x · Cited by 871 · 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
Visual speech speeds up the neural processing of auditory speech
van Wassenhove, V., Grant, K. W., & Poeppel, D. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0408949102 · Cited by 843 · see citing works
Auditory frequency discrimination and event-related potentials
Sams, M. E., Paavilainen, P., Alho, K., & Näätänen, R. (1985) · Electroencephalography and Clinical Neurophysiology/Evoked Potentials Section · doi:10.1016/0168-5597(85)90054-1 · Cited by 799 · see citing works
Amygdalar and Hippocampal Theta Rhythm Synchronization During Fear Memory Retrieval
Seidenbecher, T., Laxmi, T. R., Stork, O., & Pape, H.-C. (2003) · Science · doi:10.1126/science.1085818 · Cited by 728 · see citing works
A 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-citationTwo bilateral sources of the late AEP as identified by a spatio-temporal dipole model
Scherg, M., & CRAMON, D. V. (1985) · Electroencephalography and Clinical Neurophysiology/Evoked Potentials Section · doi:10.1016/0168-5597(85)90033-4 · Cited by 683 · see citing works
Attentive novelty detection in humans is governed by pre-attentive sensory memory
Tiitinen, H., May, P., Reinikainen, K., & Näätänen, R. (1994) · Nature · doi:10.1038/372090a0 · Cited by 637 · see citing works
Dynamic causal modeling of evoked responses in EEG and MEG
David, O., Kiebel, S. J., Harrison, L. M., Mattout, J., Kilner, J. M., & Friston, K. J. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2005.10.045 · Cited by 620 · see citing works
Self-citationMultiple sparse priors for the M/EEG inverse problem.
Friston, K., Harrison, L., Daunizeau, J., Kiebel, S., Phillips, C., Trujillo-Barreto, N., Henson, R., Flandin, G., & Mattout, J. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2007.09.048 · Cited by 589 · see citing works
Self-citationSeparate Time Behaviors of the Temporal and Frontal Mismatch Negativity Sources
Rinne, T., Alho, K., Ilmoniemi, R. J., Virtanen, J. P., & Näätänen, R. (2000) · NeuroImage · doi:10.1006/nimg.2000.0591 · Cited by 514 · see citing works
Opitz, B., Rinne, T., Mecklinger, A., von Cramon, D. Y., & Schröger, E. (2002) · NeuroImage · doi:10.1006/nimg.2001.0970 · Cited by 513 · see citing works
Probabilistic Mapping and Volume Measurement of Human Primary Auditory Cortex
Rademacher, J., Morosan, P., Schormann, T., Schleicher, A., Werner, C. W., Freund, H., & Zilles, K. (2001) · NeuroImage · doi:10.1006/nimg.2000.0714 · Cited by 503 · see citing works
Abnormal oscillatory synchronisation in the motor system leads to impaired movement
Brown, P. (2007) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2007.12.001 · Cited by 476 · see citing works
Human posterior auditory cortex gates novel sounds to consciousness
Jääskeläinen, I. P., Ahveninen, J., Bonmassar, G., Dale, A. M., Ilmoniemi, R. J., Levänen, S., Lin, F., May, P., Melcher, J. R., Stufflebeam, S. M., et al. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0303760101 · Cited by 464 · see citing works
Breakspear, M. J., Roberts, J. A., Terry, J. R., Rodrigues, S., Mahant, N., & Robinson, P. A. (2005) · Cerebral Cortex · doi:10.1093/cercor/bhj072 · Cited by 463 · 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-citationGamma Oscillations in Human Primary Somatosensory Cortex Reflect Pain Perception
Groß, J., Schnitzler, A., Timmermann, L., & Ploner, M. (2007) · PLoS Biology · doi:10.1371/journal.pbio.0050133 · Cited by 416 · see citing works
Geyer, M. A., Wilkinson, L. S., Humby, T., & Robbins, T. W. (1993) · Biological Psychiatry · doi:10.1016/0006-3223(93)90180-l · Cited by 377 · see citing works
Winkler, I., Karmos, G., & Näätänen, R. (1996) · Brain Research · doi:10.1016/s0006-8993(96)01008-6 · Cited by 338 · see citing works
Prefrontal cortex involvement in preattentive auditory deviance detection:
Doeller, C. F., Opitz, B., Mecklinger, A., Krick, C. M., Reith, W., & Schröger, E. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00389-6 · Cited by 337 · see citing works
A Bayesian approach to introducing anatomo-functional priors in the EEG/MEG inverse problem
Baillet, S., & Garnero, L. (1997) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.568913 · Cited by 326 · see citing works
Inhibition of uptake unmasks rapid extracellular turnover of glutamate of nonvesicular origin
Jabaudon, D., Shimamoto, K., Yasuda‐Kamatani, Y., Scanziani, M., Gähwiler, B. H., & Gerber, U. R. (1999) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.96.15.8733 · Cited by 305 · see citing works
Modelling 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-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-citationOscillatory neuronal dynamics during language comprehension
BASTIAANSEN, M. C. M., & Peter Hagoort, A. (2006) · Progress in brain research · doi:10.1016/s0079-6123(06)59012-0 · Cited by 294 · see citing works
Hierarchical Bayesian estimation for MEG inverse problem
Sato, M.-A., Yoshioka, T., Kajihara, S., Toyama, K., Goda, N., Doya, K., & Kawato, M. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.06.037 · Cited by 276 · 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 neural mass model of spectral responses in electrophysiology
Moran, R., Kiebel, S. J., Stephan, K. E., Reilly, R. B., Jean Daunizeau, A., & Friston, K. J. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.05.032 · Cited by 214 · see citing works
Self-citationAn empirical Bayesian solution to the source reconstruction problem in EEG
Phillips, C. L. M., Mattout, J., Rugg, M. D., Maquet, P., & Friston, K. J. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2004.10.030 · Cited by 197 · see citing works
Self-citationBifurcation Analysis of Jansen's Neural Mass Model
Grimbert, F., & Faugeras, O. D. (2006) · Neural Computation · doi:10.1162/neco.2006.18.12.3052 · Cited by 196 · see citing works
Dynamic causal models of steady-state responses
Moran, R. J., Stephan, K. E., Seidenbecher, T., Pape, H.-C., Dolan, R. J., & Friston, K. J. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.09.048 · Cited by 195 · see citing works
Self-citationAttention capture by auditory significant stimuli: semantic analysis follows attention switching
Escera, C., Yago, E., Corral, M. J., Corbera, S., & Nuñez, M. I. (2003) · European Journal of Neuroscience · doi:10.1046/j.1460-9568.2003.02937.x · Cited by 193 · see citing works
Zhang, Z. (1995) · Physics in Medicine and Biology · doi:10.1088/0031-9155/40/3/001 · Cited by 192 · see citing works
MEG source localization under multiple constraints: An extended Bayesian framework
Mattout, J., Phillips, C. L. M., Penny, W. D., Rugg, M. D., & Friston, K. J. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.10.037 · Cited by 187 · see citing works
Self-citationPopulation dynamics: Variance and the sigmoid activation function
Marreiros, A. C., Jean Daunizeau, A., Kiebel, S. J., & Friston, K. J. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.04.239 · Cited by 173 · see citing works
Self-citationRealistically Coupled Neural Mass Models Can Generate EEG Rhythms
Sotero, R. C., Trujillo‐Barreto, N. J., Iturria‐Medina, Y., Carbonell, F., & Jiménez, J. C. (2007) · Neural Computation · doi:10.1162/neco.2007.19.2.478 · Cited by 161 · see citing works
Symmetrical event-related EEG/fMRI information fusion in a variational Bayesian framework
Jean Daunizeau, A., Grova, C., Marrelec, G., Mattout, J., Jbabdi, S., Pélégrini‐Issac, M., Lina, J., & Benali, H. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.01.044 · Cited by 160 · see citing works
Population Activity in the Human Dorsal Pathway Predicts the Accuracy of Visual Motion Detection
Donner, T. H., Siegel, M., Oostenveld, R., Fries, P., Bauer, M., & Engel, A. K. (2007) · Journal of Neurophysiology · doi:10.1152/jn.01141.2006 · Cited by 152 · see citing works
Maeß, B., Jacobsen, T., Schröger, E., & Friederici, A. D. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.05.040 · Cited by 145 · see citing works
Dynamic sensory updating in the auditory system
Sussman, E. S., & Winkler, I. (2001) · Cognitive Brain Research · doi:10.1016/s0926-6410(01)00067-2 · Cited by 145 · see citing works
Jemel, B., Achenbach, C., Müller, B. W., Röpcke, B., & Oades, R. D. (2002) · Brain Topography · doi:10.1023/a:1019944805499 · Cited by 140 · see citing works
Dynamic causal modelling of induced responses
Chen, C. C., Kiebel, S. J., & Friston, K. J. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.03.026 · Cited by 136 · see citing works
Self-citationBiophysical model for integrating neuronal activity, EEG, fMRI and metabolism
Sotero, R. C., & Trujillo‐Barreto, N. J. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.08.001 · Cited by 136 · see citing works
Dynamic causal modelling of evoked responses: The role of intrinsic connections
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
Self-citationNeuromagnetic localization of rhythmic activity in the human brain: a comparison of three methods
Liljeström, M., Kujala, J., Jensen, O. B., & Salmelin, R. H. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2004.11.034 · Cited by 127 · see citing works
Bayesian 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
Self-citationVariational Bayesian inversion of the equivalent current dipole model in EEG/MEG
Kiebel, S. J., Jean Daunizeau, A., Phillips, C. L. M., & Friston, K. J. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.09.005 · Cited by 105 · see citing works
Self-citationBayesian estimation of evoked and induced responses
Friston, K. J., Henson, R. N., Phillips, C. L. M., & Mattout, J. (2006) · Human Brain Mapping · doi:10.1002/hbm.20214 · Cited by 98 · see citing works
Self-citationPopulation dynamics under the Laplace assumption
Marreiros, A. C., Kiebel, S. J., Jean Daunizeau, A., Harrison, L. M., & Friston, K. J. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.10.008 · Cited by 85 · see citing works
Self-citationStatistical parametric mapping for event-related potentials (II): a hierarchical temporal model
Kiebel, S. J., & Friston, K. J. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.02.013 · Cited by 84 · see citing works
Self-citationNummenmaa, A. R., Auranen, T., Hämäläinen, M., Jääskeläinen, I. P., Lampinen, J., Sams, M. E., & Vehtari, A. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2006.05.001 · Cited by 73 · see citing works
Jean Daunizeau, A., Mattout, J., Clonda, D., Goulard, B., Benali, H., & Lina, J.-M. (2006) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2005.869791 · Cited by 73 · see citing works
Spatiotemporal Bayesian inference dipole analysis for MEG neuroimaging data
Jun, S. C., George, J., Paré-Blagoev, J., Plis, S., Ranken, D. M., Schmidt, D. M., & Wood, C. C. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.06.003 · Cited by 72 · see citing works
A probabilistic algorithm integrating source localization and noise suppression for MEG and EEG data
Zumer, J. M., Attias, H. T., Sekihara, K., & Nagarajan, S. S. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.04.054 · Cited by 71 · see citing works
Problems and paradigms in ERP research
Gaillard, A. W. K. (1988) · Biological Psychology · doi:10.1016/0301-0511(88)90015-4 · Cited by 60 · see citing works
Zumer, J. M., Attias, H. T., Sekihara, K., & Nagarajan, S. S. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.02.006 · Cited by 53 · see citing works
A mesostate-space model for EEG and MEG
Jean Daunizeau, A., & Friston, K. J. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.06.034 · Cited by 44 · see citing works
Self-citationRodrigues, S., Terry, J. R., & Breakspear, M. J. (2006) · Physics Letters A · doi:10.1016/j.physleta.2006.03.003 · Cited by 39 · see citing works
Poline, J., Strother, S. C., Dehaene‐Lambertz, G., Egan, G. F., & Lancaster, J. L. (2006) · Human Brain Mapping · doi:10.1002/hbm.20268 · Cited by 37 · see citing works
Automatic relevance determination based hierarchical Bayesian MEG inversion in practice
Nummenmaa, A. R., Auranen, T., Hämäläinen, M., Jääskeläinen, I. P., Sams, M. E., Vehtari, A., & Lampinen, J. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.04.021 · Cited by 32 · see citing works
Repetition suppression of induced gamma band responses is eliminated by task switching
Gruber, T., Giabbiconi, C., Trujillo‐Barreto, N. J., & Müller, M. M. (2006) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2006.05130.x · Cited by 31 · see citing works
Dynamical causal modelling for M/EEG: Spatial and temporal symmetry constraints
Fastenrath, M., Friston, K. J., & Kiebel, S. J. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.07.041 · Cited by 31 · see citing works
Self-citationRobust Bayesian general linear models
Penny, W. D., Kilner, J. M., & Blankenburg, F. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.01.058 · Cited by 25 · see citing works
Improving source detection and separation in a spatiotemporal Bayesian inference dipole analysis
Jun, S. C., George, J., Plis, S., Ranken, D. M., Schmidt, D. M., & Wood, C. C. (2006) · Physics in Medicine and Biology · doi:10.1088/0031-9155/51/10/004 · Cited by 23 · see citing works
Dipole modelling of MEG rhythms in time and frequency domains
Salmelin, R. H., & H�m�l�inen, M. S. (1995) · Brain Topography · doi:10.1007/bf01202384 · Cited by 21 · see citing works
Bayesian inverse analysis of neuromagnetic data using cortically constrained multiple dipoles
Auranen, T., Nummenmaa, A. R., Hämäläinen, M., Jääskeläinen, I. P., Lampinen, J., Vehtari, A., & Sams, M. E. (2007) · Human Brain Mapping · doi:10.1002/hbm.20334 · Cited by 19 · see citing works
The coupled dipole model: an integrated model for multiple MEG/EEG data sets
Bijma, F., de Munck, J. C., Böcker, K. B. E., Huizenga, H. M., & Heethaar, R. M. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.06.038 · Cited by 7 · see citing works
Hypoglutamatergia in the rat medial prefrontal cortex in two models of schizophrenia
Brady, A. T., Souza, I. F. J. D., O'Keeffe, Kenny, C. M., McCabe, O., Moran, M. P., Duffy, A., Mulvany, S. K., & O'Connor, W. T. (2005) · Acta Neurobiologiae Experimentalis · Cited by 3 · see citing works
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Schoffelen, J., & Groß, J. (2009) · Human Brain Mapping · doi:10.1002/hbm.20745 · Cited by 854 · see citing works
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Heilbron, M., & Chait, M. (2018) · Neuroscience · doi:10.1016/j.neuroscience.2017.07.061 · Cited by 428 · see citing works
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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-citationLindner, M., Vicente, R., Priesemann, V., & Wibral, M. (2011) · BMC Neuroscience · doi:10.1186/1471-2202-12-119 · Cited by 231 · see citing works
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Larson‐Prior, L. J., Oostenveld, R., Penna, S. D., Michalareas, G., Prior, F., Abbas Babajani-feremi, A., Schoffelen, J., Marzetti, L., de Pasquale, F., Pompeo, F., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.056 · Cited by 216 · see citing works
Gotts, S. J., Chow, C. C., & Martin, A. (2012) · Cognitive Neuroscience · doi:10.1080/17588928.2012.670617 · Cited by 213 · see citing works
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Self-citationRealistically Coupled Neural Mass Models Can Generate EEG Rhythms
Sotero, R. C., Trujillo‐Barreto, N. J., Iturria‐Medina, Y., Carbonell, F., & Jiménez, J. C. (2007) · Neural Computation · doi:10.1162/neco.2007.19.2.478 · Cited by 161 · see citing works
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Vaudano, A. E., Laufs, H., Kiebel, S. J., Carmichael, D. W., Hamandi, K., Guye, M., Thornton, R., Rodionov, R., Friston, K. J., Duncan, J. S., et al. (2009) · PLoS ONE · doi:10.1371/journal.pone.0006475 · Cited by 146 · 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-citationA Simulation Framework for Benchmarking EEG-Based Brain Connectivity Estimation Methodologies
Haufe, S., & Ewald, A. (2016) · Brain Topography · doi:10.1007/s10548-016-0498-y · Cited by 131 · see citing works
Neymotin, S. A., Daniels, D. S., Caldwell, B., McDougal, R. A., Carnevale, N. T., Jas, M., Moore, C. I., Hines, M. L., Hämäläinen, M., & Jones, S. R. (2020) · eLife · doi:10.7554/elife.51214 · Cited by 109 · see citing works
The generation of rhythms within a cortical region: Analysis of a neural mass model
Ursino, M., Cona, F., & Zavaglia, M. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.12.084 · Cited by 117 · see citing works
Functional networks of the brain: from connectivity restoration to dynamic integration
Hramov, A. E., Frolov, N. S., Maksimenko, V. A., Kurkin, S., Kazantsev, V., & Pisarchik, A. N. (2020) · Physics-Uspekhi · doi:10.3367/ufne.2020.06.038807 · Cited by 96 · see citing works
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Zarghami, T. S., & Friston, K. J. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116453 · Cited by 90 · see citing works
Self-citationAndrä, C., Mathias, B., Schwager, A., Macedonia, M., & von Kriegstein, K. (2020) · Educational Psychology Review · doi:10.1007/s10648-020-09527-z · Cited by 94 · see citing works
Rosch, R. E., Hunter, P. R., Baldeweg, T., Friston, K. J., & Meyer, M. P. (2018) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006375 · Cited by 74 · see citing works
Self-citationDynamic causal modelling of precision and synaptic gain in visual perception — an EEG study
Brown, H. R., & Friston, K. J. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.06.044 · Cited by 79 · see citing works
Self-citationAn EEG-based machine learning method to screen alcohol use disorder
Mumtaz, W., Vuong, P. L., Xia, L., Malik, A. S., & Rashid, R. B. A. (2016) · Cognitive Neurodynamics · doi:10.1007/s11571-016-9416-y · Cited by 78 · see citing works
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He, F., & Yang, Y. (2020) · Neuroscience · doi:10.1016/j.neuroscience.2020.12.001 · Cited by 76 · see citing works
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Roiser, J. P., Wigton, R. L., Kilner, J. M., Méndez, M. A., Hon, N., Friston, K. J., & Joyce, E. M. (2013) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2013.00176 · Cited by 75 · see citing works
Self-citationSumner, R. L., McMillan, R. L., Spriggs, M. J., Campbell, D. A., Malpas, G. A., Maxwell, E., Deng, C., Hay, J., Ponton, R., Kirk, I. J., et al. (2019) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2019.07.002 · Cited by 69 · see citing works
Bielczyk, N., Uithol, S., van Mourik, T., Anderson, P., Glennon, J. C., & Buitelaar, J. K. (2018) · Network Neuroscience · doi:10.1162/netn_a_00062 · Cited by 70 · see citing works
Keser, Z., Buchl, S. C., Seven, N. A., Markota, M., Clark, H. M., Jones, D. T., Lanzino, G. S., Brown, R. D., Worrell, G. A., & Lundstrom, B. N. (2022) · Frontiers in Neurology · doi:10.3389/fneur.2022.827866 · Cited by 66 · see citing works
An EEG-based functional connectivity measure for automatic detection of alcohol use disorder
Mumtaz, W., Saad, M. N. B. M., Kamel, N., Ali, S. S. A., & Malik, A. S. (2017) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2017.11.002 · Cited by 65 · see citing works
Reorganisation of brain networks in frontotemporal dementia and progressive supranuclear palsy
Hughes, L. E., Ghosh, B. C. P., & Rowe, J. B. (2013) · NeuroImage: Clinical · doi:10.1016/j.nicl.2013.03.009 · Cited by 60 · see citing works
Nguyen, V. T., Breakspear, M. J., & Cunnington, R. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.06.083 · Cited by 61 · see citing works
Ageing changes effective connectivity of motor networks during bimanual finger coordination
Loehrer, P. A., Nettersheim, F. S., Jung, F., Weber, I., Huber, C. A., Dembek, T. A., Pelzer, E. A., Fink, G. R., Tittgemeyer, M., & Timmermann, L. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.09.014 · Cited by 58 · see citing works
Good scientific practice in EEG and MEG research: Progress and perspectives
Niso, G., Krol, L. R., Combrisson, E., Dubarry, A., Elliott, M., Clément, F., Héjja‐Brichard, Y., Herbst, S. K., Jerbi, K., Ković, V., et al. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119056 · Cited by 64 · see citing works
Predicting Motor Imagery Performance From Resting-State EEG Using Dynamic Causal Modeling
Lee, M., Yoon, J.-G., & Lee, S.-W. (2020) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2020.00321 · Cited by 55 · see citing works
Best Practices in Data Analysis and Sharing in Neuroimaging using MEEGPreprint
Pernet, C. R., Garrido, M. I., Gramfort, A., Maurits, N. M., Michel, C. M., Pang, E. W., Salmelin, R. H., Schoffelen, J., Valdes-Sosa, P. A., & Puce, A. (2018) · doi:10.31219/osf.io/a8dhx · Cited by 56 · see citing works
Self-citationA dynamic causal model study of neuronal population dynamics
Marreiros, A. C., Kiebel, S. J., & Friston, K. J. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.01.098 · Cited by 53 · see citing works
Self-citationModeling time-varying brain networks with a self-tuning optimized Kalman filter
Pascucci, D., Rubega, M., & Plomp, G. (2020) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1007566 · Cited by 50 · see citing works
Computational Models in Electroencephalography
Glomb, K., Cabral, J., Cattani, A., Mazzoni, A., Raj, A., & Franceschiello, B. (2021) · Brain Topography · doi:10.1007/s10548-021-00828-2 · Cited by 57 · see citing works
Novelli, L., Friston, K. J., & Razi, A. (2023) · Network Neuroscience · doi:10.1162/netn_a_00348 · Cited by 54 · see citing works
Self-citationNeural Field Models: A mathematical overview and unifying framework
Cook, B. J., Peterson, A. D. H., Woldman, W., & Terry, J. R. (2022) · Mathematical Neuroscience and Applications · doi:10.46298/mna.7284 · Cited by 48 · see citing works
Scharmüller, W., Leutgeb, V., Schäfer, A., Köchel, A., & Schienle, A. (2011) · Brain Research · doi:10.1016/j.brainres.2011.04.018 · Cited by 50 · see citing works
Networks involved in seizure initiation
Vaudano, A. E., Carmichael, D. W., Salek‐Haddadi, A., Rampp, S., Stefan, H., Lemieux, L., & Koepp, M. J. (2012) · Neurology · doi:10.1212/wnl.0b013e31825fdf3a · Cited by 50 · see citing works
Chan, J. S., Wibral, M., Stawowsky, C., Brandl, M., Helbling, S., Naumer, M. J., Kaiser, J., & Wollstadt, P. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.631599 · Cited by 49 · see citing works
GABAergic cortical network physiology in frontotemporal lobar degeneration
Adams, N. E., Hughes, L. E., Rouse, M. A., Phillips, H. N., Shaw, A. D., Murley, A. G., Cope, T. E., Bevan-Jones, W. R., Passamonti, L., Street, D., et al. (2021) · Brain · doi:10.1093/brain/awab097 · Cited by 47 · see citing works
Self-citationTeki, S., Barnes, G. R., Penny, W. D., Iverson, P., Woodhead, Z., Griffiths, T. D., & Leff, A. P. (2013) · Brain · doi:10.1093/brain/awt087 · Cited by 48 · see citing works
Sanders, R. D., Banks, M. I., Darracq, M., Moran, R., SLEIGH, J. W., Gosseries, O., Bonhomme, V. L., Brichant, J. F., Rosanova, M., Raz, A., et al. (2018) · British Journal of Anaesthesia · doi:10.1016/j.bja.2018.07.006 · Cited by 43 · see citing works
Self-citationWright, S. K., Rosch, R. E., Wilson, M. A., Upadhya, M. A., Dhangar, D., Clarke-Bland, C., Wahid, T. T., Barman, S., Goebels, N., Kreye, J., et al. (2021) · Communications Biology · doi:10.1038/s42003-021-02635-8 · Cited by 44 · see citing works
Klamer, S., Rona, S., Elshahabi, A., Lerche, H., Braun, C., Honegger, J. B., Erb, M., & Focke, N. K. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.03.027 · Cited by 43 · see citing works
Empirical Bayes for Group (DCM) Studies: A Reproducibility Study
Vladimir Litvak, A., Garrido, M. I., Zeidman, P., & Friston, K. J. (2015) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2015.00670 · Cited by 43 · see citing works
Self-citationWang, P., & Knösche, T. R. (2013) · PLoS ONE · doi:10.1371/journal.pone.0077876 · Cited by 42 · see citing works
The use of magnetoencephalography in the study of psychopharmacology (pharmaco-MEG)
Muthukumaraswamy, S. D. (2014) · Journal of Psychopharmacology · doi:10.1177/0269881114536790 · Cited by 40 · see citing works
Brain Functional Correlates of Resting Hypnosis and Hypnotizability: A Review
Pascalis, V. D. (2024) · Brain Sciences · doi:10.3390/brainsci14020115 · Cited by 44 · see citing works
A review of EEG and MEG for brainnetome research
Zhang, X., Lei, X., Wu, T., & Jiang, T. (2013) · Cognitive Neurodynamics · doi:10.1007/s11571-013-9274-9 · Cited by 39 · see citing works
Sonkusare, S., Ding, Q., Zhao, Y., Liu, W., Yang, R., Mandali, A., Manssuer, L. R., Zhang, C., Cao, C., Sun, B., et al. (2022) · Molecular Psychiatry · doi:10.1038/s41380-022-01883-2 · Cited by 33 · see citing works
GABA-ergic Dynamics in Human Frontotemporal Networks Confirmed by Pharmaco-Magnetoencephalography
Adams, N., Hughes, L. E., Phillips, H. N., Shaw, A. D., Murley, A. G., Nesbitt, D. J., Cope, T., Bevan-Jones, W. R., Passamonti, L., & Rowe, J. B. (2020) · Journal of Neuroscience · doi:10.1523/jneurosci.1689-19.2019 · Cited by 34 · see citing works
Assessing levels of consciousness with symbolic analysis
Lee, U., Blain‐Moraes, S., & Mashour, G. A. (2014) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2014.0117 · Cited by 32 · see citing works
Ihalainen, R., Gosseries, O., de Steen, F. V., Raimondo, F., Panda, R., Bonhomme, V. L., Marinazzo, D., Bowman, H., Laureys, S., & Chennu, S. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.117841 · Cited by 31 · see citing works
Shaw, A. D., Hughes, L. E., Moran, R., Coyle-Gilchrist, I., Rittman, T., & Rowe, J. B. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhz024 · Cited by 30 · see citing works
Self-citationBourel‐Ponchel, E., Mahmoudzadeh, M., Adebimpe, A., & Wallois, F. (2019) · Frontiers in Neurology · doi:10.3389/fneur.2019.00809 · Cited by 31 · see citing works
Repetition priming and repetition suppression: Multiple mechanisms in need of testing
Gotts, S. J., Chow, C. C., & Martin, A. D. (2012) · Cognitive Neuroscience · doi:10.1080/17588928.2012.697054 · Cited by 30 · see citing works
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Albarracin, M., Constant, A., Friston, K. J., & Ramstead, M. J. D. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.585493 · Cited by 28 · see citing works
Self-citationCope, T. E., Hughes, L. E., Phillips, H. N., Adams, N. E., Jafarian, A., Nesbitt, D., Assem, M., Woolgar, A., Duncan, J., & Rowe, J. B. (2022) · Journal of Neuroscience · doi:10.1523/jneurosci.1622-21.2022 · Cited by 31 · see citing works
Modeling the effect of sleep regulation on a neural mass model
Costa, M. S., Jan Born, A., Claussen, J. C., & Martinetz, T. (2016) · Journal of Computational Neuroscience · doi:10.1007/s10827-016-0602-z · Cited by 28 · see citing works
Computational Science – ICCS 2020
Krzhizhanovskaya, V. V., Závodszky, G., Lees, M., Dongarra, J. J., Sloot, P. M. A., Brissos, S., Teixeira, J., Krzhizhanovskaya, V. V., Závodszky, G., Lees, M., et al. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-50436-6 · Cited by 28 · see citing works
Global dynamics of neural mass models
Cooray, G., Rosch, R. E., & Friston, K. J. (2023) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010915 · Cited by 27 · see citing works
Self-citationShaw, A. D., Muthukumaraswamy, S. D., Saxena, N., Sumner, R. L., Adams, N., Moran, R., & Singh, K. D. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117189 · Cited by 26 · see citing works
Self-citationGrove, T. B., Lasagna, C., Martínez-Cancino, R., Pamidighantam, P., Deldin, P., & Tso, I. (2020) · Biological Psychiatry: Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2020.08.013 · Cited by 25 · see citing works
Is predictive coding falsifiable?
Bowman, H., Collins, D., Nayak, A. K., & Cruse, D. (2023) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2023.105404 · Cited by 24 · see citing works
UKF-based closed loop iterative learning control of epileptiform wave in a neural mass model
Shan, B., Wang, J., Deng, B., Wei, X., Yu, H., & Li, H. (2014) · Cognitive Neurodynamics · doi:10.1007/s11571-014-9306-0 · Cited by 26 · see citing works
Dzafic, I., Larsen, K. M., Darke, H., Pertile, H., Carter, O., Sundram, S., & Garrido, M. I. (2021) · Schizophrenia Bulletin · doi:10.1093/schbul/sbaa188 · Cited by 24 · see citing works
Self-citationPereira, I., Frässle, S., Heinzle, J., Schöbi, D., Tri, C., Gruber, M., & Stephan, K. E. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118662 · Cited by 22 · see citing works
Preterm neonates distinguish rhythm violation through a hierarchy of cortical processing
Edalati, M., Mahmoudzadeh, M., Ghostine, G., Kongolo, G., Safaie, J., Wallois, F., & Moghimi, S. (2022) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2022.101168 · Cited by 25 · see citing works
On the synchrony of steady state visual evoked potentials and oscillatory burst events
Vialatte, F., Dauwels, J., Maurice, M., Yamaguchi, Y., & Cichocki, A. S. (2009) · Cognitive Neurodynamics · doi:10.1007/s11571-009-9082-4 · Cited by 23 · see citing works
Whyte, C. J., Hohwy, J., & Smith, R. (2022) · Current Research in Neurobiology · doi:10.1016/j.crneur.2022.100036 · Cited by 24 · see citing works
Dynamic Causal Modeling for fMRI With Wilson-Cowan-Based Neuronal Equations
Sadeghi, S., Mier, D. U., Gerchen, M. F., Schmidt, S. N. L., & Haß, J. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.593867 · Cited by 21 · see citing works
Cope, T., Hughes, L. E., Phillips, H. N., Adams, N., Jafarian, A., Nesbitt, D. J., Assem, M., Woolgar, A., Duncan, J., & Rowe, J. B. (2022) · Apollo (University of Cambridge) · doi:10.17863/cam.83553 · Cited by 23 · see citing works
Spedden, M. E., Beck, M. M., Christensen, M. S., Dietz, M. J., Karabanov, A. N., Geertsen, S. S., Nielsen, J. B., & Lundbye‐Jensen, J. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116982 · Cited by 21 · see citing works
Huang, J., Choo, S., Pugh, Z. H., & Nam, C. S. (2021) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720820987443 · Cited by 21 · see citing works
Ouyang, G., & Zhou, C. (2020) · Cognitive Neurodynamics · doi:10.1007/s11571-020-09631-4 · Cited by 20 · see citing works
Modeling and MEG evidence of early consonance processing in auditory cortex
Tabas, A., Andermann, M., Schuberth, V., Riedel, H., Balaguer‐Ballester, E., & Rupp, A. (2019) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006820 · Cited by 20 · see citing works
Tabas, A., & von Kriegstein, K. (2021) · Frontiers in Neural Circuits · doi:10.3389/fncir.2021.644743 · Cited by 20 · see citing works
Brain Network Analysis: A Review on Multivariate Analytical Methods
Bahrami, M., Laurienti, P. J., Shappell, H. M., & Simpson, S. L. (2022) · Brain Connectivity · doi:10.1089/brain.2022.0007 · Cited by 20 · see citing works
Harnessing electroencephalography connectomes for cognitive and clinical neuroscience
Zhang, Y., & Chen, Z. S. (2025) · Nature Biomedical Engineering · doi:10.1038/s41551-025-01442-4 · Cited by 17 · see citing works
Zhao, Y., Boley, M., Pelentritou, A., Karoly, P. J., Freestone, D. R., Liu, Y., Muthukumaraswamy, S. D., William, W., Liley, D. T. J., & Kuhlmann, L. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119592 · Cited by 16 · see citing works
Brain dynamics of mental workload in a multitasking context: Evidence from dynamic causal modeling
Huang, J., Pugh, Z. H., Kim, S., & Nam, C. S. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2023.108043 · Cited by 18 · see citing works
Extracranial Estimation of Neural Mass Model Parameters Using the Unscented Kalman Filter
Escuain-Poole, L., García‐Ojalvo, J., & Pons, A. J. (2018) · Frontiers in Applied Mathematics and Statistics · doi:10.3389/fams.2018.00046 · Cited by 17 · see citing works
Esménio, S., Soares, J. M., Oliveira‐Silva, P., Gonçalves, Ó. F., Friston, K. J., & Coutinho, J. F. P. (2020) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2020.00151 · Cited by 17 · see citing works
Self-citationCasey, C. P., Tanabe, S., Farahbakhsh, Z. Z., Parker, M., Bo, A. Y., White, M., Ballweg, T., Mcintosh, A., Filbey, W., Banks, M. I., et al. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119657 · Cited by 18 · see citing works
Mappings between a macroscopic neural-mass model and a reduced conductance-based model
Rodrigues, S., Chizhov, A. V., Marten, F., & Terry, J. R. (2010) · Biological Cybernetics · doi:10.1007/s00422-010-0372-z · Cited by 18 · see citing works
Raj, A., Verma, P., & Nagarajan, S. S. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.959557 · Cited by 16 · see citing works
Multi-channel neural mass modelling and analyzing
Cui, D. Y., Xiaoli Li, A., Ji, X., & Liu, L. (2011) · Science China Information Sciences · doi:10.1007/s11432-011-4216-9 · Cited by 15 · see citing works
Identifying neural drivers of benign childhood epilepsy with centrotemporal spikes
Adebimpe, A., Bourel‐Ponchel, E., & Wallois, F. (2017) · NeuroImage Clinical · doi:10.1016/j.nicl.2017.11.024 · Cited by 16 · see citing works
Prediction of Speech Sounds Is Facilitated by a Functional Fronto-Temporal Network
Oestreich, L., Whitford, T. J., & Garrido, M. I. (2018) · Frontiers in Neural Circuits · doi:10.3389/fncir.2018.00043 · Cited by 17 · see citing works
Self-citationOn self-feedback connectivity in neural mass models applied to event-related potentials
Youssofzadeh, V., Prasad, G., & Wong‐Lin, K. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.12.067 · Cited by 14 · see citing works
Oestreich, L., Randeniya, R., & Garrido, M. I. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.04.008 · Cited by 15 · see citing works
Self-citationA marginalised Markov Chain Monte Carlo approach for model based analysis of EEG data
Hettiarachchi, I. T., Mohamed, S. M. K., & Nahavandi, S. (2012) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2012.6235866 · Cited by 13 · see citing works
Perceptual learning to discriminate the intensity and spatial location of nociceptive stimuli
Mancini, F., Dolgevica, K., Steckelmacher, J., Haggard, P., Friston, K. J., & Iannetti, G. D. (2016) · Scientific Reports · doi:10.1038/srep39104 · Cited by 12 · see citing works
Self-citationBayesian inference of a spectral graph model for brain oscillations
Jin, H., Verma, P., Jiang, F., Nagarajan, S. S., & Raj, A. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120278 · Cited by 12 · see citing works
Reliability of energy landscape analysis of resting‐state functional MRI data
Khanra, P., Nakuci, J., Muldoon, S. F., Watanabe, T., & Masuda, N. (2024) · European Journal of Neuroscience · doi:10.1111/ejn.16390 · Cited by 13 · see citing works
Ihalainen, R., Annen, J., Gosseries, O., Cardone, P., Panda, R., Martial, C., Thibaut, A., Laureys, S., & Chennu, S. (2024) · PLoS ONE · doi:10.1371/journal.pone.0298110 · Cited by 12 · see citing works
In search of specificity: Functional MRI in the study of emotional experience
Schienle, A. (2009) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2008.12.016 · Cited by 12 · see citing works
Evaluation of brain connectivity: The role of magnetoencephalography
Burgess, R. C. (2011) · Epilepsia · doi:10.1111/j.1528-1167.2011.03148.x · Cited by 12 · see citing works
- Authors
- Kiebel, S. J., Garrido, M. I., Moran, R. J., & Friston, K. J.
- Affiliations
- Wellcome Centre for Human Neuroimaging (GB)
- Corresponding author
- Kiebel, Stefan J.
- Venue
- Cognitive Neurodynamics
- Published
- 2008-04-23
- Volume
- 2
- Issue
- 2
- Pages
- 121-136
- ISSN
- 1871-4080 (ISSN-L)
- 1871-4099
- PMC
- PMC2427062
- OpenAlex
- W2124995442
- Cited by
- 211
- References
- 86
- Citations by year
- 2026: 13 · 2025: 14 · 2024: 12 · 2023: 18 · 2022: 24 · 2021: 17 · 2020: 23 · 2019: 12 · 2018: 11 · 2017: 9 · 2016: 6 · 2015: 8 · 2014: 4 · 2013: 13 · 2012: 7
- FWCI
- 3.28
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc
- Locations
- Cognitive Neurodynamics (publishedVersion, cc-by-nc)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Minerva Access (University of Melbourne) (submittedVersion, cc-by-nc)
- UCL Discovery (University College London) (submittedVersion)
- Max Planck Digital Library (submittedVersion, other-oa)
- Max Planck Digital Library (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion, other-oa)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Explore Bristol Research (submittedVersion)
- Bristol Research (University of Bristol) (submittedVersion)
- Funders
- Wellcome Trust (088130)
- Irish Research Council
- Fundação para a Ciência e a Tecnologia
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Keywords
- dynamic causal modeling, M/EEG, effective connectivity, generative models, Bayesian parameter estimation, evoked potentials, lead field
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