F. Lopes-da-silva, T. Van-lierop, C. Schrijer, S. Van-leeuwen, and W. , Organization of thalamic and cortical alpha rhythms: Spectra and coherences, Electroencephalography and Clinical Neurophysiology, vol.35, issue.6, pp.627-666, 1973.
DOI : 10.1016/0013-4694(73)90216-2

F. Lopes-da-silva, J. Vos, J. Mooibroek, and A. Van-rotterdam, Relative contributions of intracortical and thalamo-cortical processes in the generation of alpha rhythms, revealed by partial coherence analysis, Electroencephalography and Clinical Neurophysiology, vol.50, issue.5-6, pp.5-6449, 1980.
DOI : 10.1016/0013-4694(80)90011-5

M. Steriade and M. Deschenes, The thalamus as a neuronal oscillator, Brain Research Reviews, vol.8, issue.1, pp.1-63, 1984.
DOI : 10.1016/0165-0173(84)90017-1

S. Hughes and V. Crunelli, Just a phase they're going through: The complex interaction of intrinsic high-threshold bursting and gap junctions in the generation of thalamic ?? and ?? rhythms, International Journal of Psychophysiology, vol.64, issue.1, pp.3-17, 2007.
DOI : 10.1016/j.ijpsycho.2006.08.004

S. Hughes and V. Crunelli, Thalamic mechanisms of EEG alpha rhythms and their pathological implications . The Neuroscientist, pp.357-72, 2005.

S. Haegens, V. Nácher, R. Luna, R. Romo, and O. Jensen, ??-Oscillations in the monkey sensorimotor network influence discrimination performance by rhythmical inhibition of neuronal spiking, Proceedings of the National Academy of Sciences, vol.108, issue.48, pp.19377-82, 2011.
DOI : 10.1073/pnas.1117190108

P. Ritter and A. Villringer, Simultaneous EEG???fMRI, Neuroscience & Biobehavioral Reviews, vol.30, issue.6, pp.823-861, 2006.
DOI : 10.1016/j.neubiorev.2006.06.008

R. Goldman, J. Stern, J. Engel, . Jr, and M. Cohen, Simultaneous EEG and fMRI of the alpha rhythm, NeuroReport, vol.13, issue.18, pp.2487-92, 2002.
DOI : 10.1097/00001756-200212200-00022

J. De-munck, S. Gonçalves, L. Huijboom, J. Kuijer, P. Pouwels et al., The hemodynamic response of the alpha rhythm: An EEG/fMRI study, NeuroImage, vol.35, issue.3, pp.1142-51, 2007.
DOI : 10.1016/j.neuroimage.2007.01.022

S. Gonçalves, J. De-munck, P. Pouwels, R. Schoonhoven, J. Kuijer et al., Correlating the alpha rhythm to BOLD using simultaneous EEG/fMRI: Inter-subject variability, NeuroImage, vol.30, issue.1, pp.203-216, 2006.
DOI : 10.1016/j.neuroimage.2005.09.062

M. Moosmann, P. Ritter, I. Krastel, A. Brink, S. Thees et al., Correlates of alpha rhythm in functional magnetic resonance imaging and near infrared spectroscopy, NeuroImage, vol.20, issue.1
DOI : 10.1016/S1053-8119(03)00344-6

H. Laufs, K. Krakow, P. Sterzer, E. Eger, A. Beyerle et al., Electroencephalographic signatures of attentional and cognitive default modes in spontaneous brain activity fluctuations at rest, Proceedings of the National Academy of Sciences, vol.100, issue.19, pp.11053-11061, 2003.
DOI : 10.1073/pnas.1831638100

R. Stefanescu and V. Jirsa, A Low Dimensional Description of Globally Coupled Heterogeneous Neural Networks of Excitatory and Inhibitory Neurons, PLoS Computational Biology, vol.92, issue.11, 2008.
DOI : 10.1371/journal.pcbi.1000219.s004

J. Hindmarsh and R. Rose, A Model of Neuronal Bursting Using Three Coupled First Order Differential Equations, Proceedings of the Royal Society B: Biological Sciences, vol.221, issue.1222, pp.87-102, 1222.
DOI : 10.1098/rspb.1984.0024

F. Freyer, J. Roberts, P. Ritter, and M. Breakspear, A Canonical Model of Multistability and Scale-Invariance in Biological Systems, PLoS Computational Biology, vol.8, issue.8, p.22912567, 2012.
DOI : 10.1371/journal.pcbi.1002634.s001

G. Deco, V. Jirsa, A. Mcintosh, O. Sporns, and R. Kötter, Key role of coupling, delay, and noise in resting brain fluctuations, Proceedings of the National Academy of Sciences, vol.106, issue.25, pp.10302-10309, 2009.
DOI : 10.1073/pnas.0901831106

C. Honey, R. Kötter, M. Breakspear, and O. Sporns, Network structure of cerebral cortex shapes functional connectivity on multiple time scales, Proceedings of the National Academy of Sciences, vol.104, issue.24, pp.10240-10245, 2007.
DOI : 10.1073/pnas.0701519104

P. Robinson, C. Rennie, D. Rowe, O. Connor, S. Wright et al., Neurophysical Modeling of Brain Dynamics, Neuropsychopharmacology, vol.28, issue.S1, pp.74-83, 2003.
DOI : 10.1038/sj.npp.1300143

F. Freyer, J. Roberts, R. Becker, P. Robinson, P. Ritter et al., Biophysical Mechanisms of Multistability in Resting-State Cortical Rhythms, Journal of Neuroscience, vol.31, issue.17, pp.6353-61, 2011.
DOI : 10.1523/JNEUROSCI.6693-10.2011

F. Freyer, K. Aquino, P. Robinson, P. Ritter, and M. Breakspear, Bistability and Non-Gaussian Fluctuations in Spontaneous Cortical Activity, Journal of Neuroscience, vol.29, issue.26, pp.8512-8536, 2009.
DOI : 10.1523/JNEUROSCI.0754-09.2009

R. Sotero and N. Trujillo-barreto, Biophysical model for integrating neuronal activity, EEG, fMRI and metabolism, NeuroImage, vol.39, issue.1, pp.290-309, 2008.
DOI : 10.1016/j.neuroimage.2007.08.001

P. Ritter, M. Schirner, A. Mcintosh, and V. Jirsa, The virtual brain integrates computational modelling and multimodal neuroimaging. Brain Connect, pp.121-166, 2012.

A. Ghosh, Y. Rho, A. Mcintosh, R. Kötter, and V. Jirsa, Noise during Rest Enables the Exploration of the Brain's Dynamic Repertoire, PLoS Computational Biology, vol.2, issue.10, pp.1000196-1000202, 2008.
DOI : 10.1371/journal.pcbi.1000196.s011

Y. Rho, R. Mcintosh, and V. Jirsa, Synchrony of Two Brain Regions Predicts the Blood Oxygen Level Dependent Activity of a Third, Brain Connectivity, vol.1, issue.1, pp.73-80, 2011.
DOI : 10.1089/brain.2011.0009

D. Chawla, E. Lumer, and K. Friston, The Relationship Between Synchronization Among Neuronal Populations and Their Mean Activity Levels, Neural Computation, vol.66, issue.6, pp.1389-411, 1999.
DOI : 10.1038/373033a0

J. Kilner, J. Mattout, R. Henson, and K. Friston, Hemodynamic correlates of EEG: A heuristic, NeuroImage, vol.28, issue.1, pp.280-286, 2005.
DOI : 10.1016/j.neuroimage.2005.06.008

J. Riera, E. Aubert, K. Iwata, R. Kawashima, X. Wan et al., Fusing EEG and fMRI based on a bottom-up model: inferring activation and effective connectivity in neural masses, Philosophical Transactions of the Royal Society B: Biological Sciences, vol.21, issue.4, pp.1025-1066, 1457.
DOI : 10.1002/hbm.20000

M. Lauritzen, C. Mathiesen, K. Schaefer, and K. Thomsen, Neuronal inhibition and excitation, and the dichotomic control of brain hemodynamic and oxygen responses, NeuroImage, vol.62, issue.2, p.22261372, 2012.
DOI : 10.1016/j.neuroimage.2012.01.040

M. Havlicek, K. Friston, J. J. Brázdil, M. Calhoun, and V. , Dynamic modeling of neuronal responses in fMRI using cubature Kalman filtering, NeuroImage, vol.56, issue.4, pp.2109-2137, 2011.
DOI : 10.1016/j.neuroimage.2011.03.005

B. Feige, K. Scheffler, F. Esposito, D. Salle, F. Hennig et al., Cortical and Subcortical Correlates of Electroencephalographic Alpha Rhythm Modulation, Journal of Neurophysiology, vol.93, issue.5, pp.2864-72, 2005.
DOI : 10.1152/jn.00721.2004

M. Difrancesco, S. Holland, and J. Szaflarski, Simultaneous EEG/Functional Magnetic Resonance Imaging at 4 Tesla: Correlates of Brain Activity to Spontaneous Alpha Rhythm During Relaxation, Journal of Clinical Neurophysiology, vol.25, issue.5, pp.255-64, 2008.
DOI : 10.1097/WNP.0b013e3181879d56

H. Laufs, A. Kleinschmidt, A. Beyerle, E. Eger, A. Salek-haddadi et al., EEG-correlated fMRI of human alpha activity, NeuroImage, vol.19, issue.4, pp.1463-76, 2003.
DOI : 10.1016/S1053-8119(03)00286-6

K. Lindgren, C. Larson, S. Schaefer, H. Abercrombie, R. Ward et al., Thalamic metabolic rate predicts EEG alpha power in healthy control subjects but not in depressed patients, Biological Psychiatry, vol.45, issue.8, pp.943-52, 1999.
DOI : 10.1016/S0006-3223(98)00350-3

C. Larson, R. Davidson, H. Abercrombie, R. Ward, S. Schaefer et al., Relations between PET-derived measures of thalamic glucose metabolism and EEG alpha power, Psychophysiology, vol.35, issue.2, pp.162-171, 1998.
DOI : 10.1111/1469-8986.3520162

P. Danos, S. Guich, L. Abel, and M. Buchsbaum, EEG Alpha Rhythm and Glucose Metabolic Rate in the Thalamus in Schizophrenia, Neuropsychobiology, vol.43, issue.4, pp.265-72, 2001.
DOI : 10.1159/000054901

R. Becker, M. Reinacher, F. Freyer, A. Villringer, and P. Ritter, How Ongoing Neuronal Oscillations Account for Evoked fMRI Variability, Journal of Neuroscience, vol.31, issue.30, pp.11016-11043, 2011.
DOI : 10.1523/JNEUROSCI.0210-11.2011

A. Arieli, S. Sterkin, A. Grinvald, and A. Aertsen, Dynamics of Ongoing Activity: Explanation of the Large Variability in Evoked Cortical Responses, Science, vol.273, issue.5283, pp.1868-70, 1996.
DOI : 10.1126/science.273.5283.1868

A. Arieli, D. Shoham, R. Hildesheim, and A. Grinvald, Coherent spatiotemporal patterns of ongoing activity revealed by real-time optical imaging coupled with single-unit recording in the cat visual cortex, J Neurophysiol, vol.73, issue.5, pp.2072-93, 1995.

R. Azouz and C. Gray, Cellular mechanisms contributing to response variability of cortical neurons in vivo, J Neurosci Mar, vol.15, issue.196, pp.2209-2232, 1999.

P. Nunez and R. Silberstein, On the relationship of synaptic activity to macroscopic measurements: does co-registration of EEG with fMRI make sense?, Brain Topography, vol.13, issue.2, pp.79-96, 2000.
DOI : 10.1023/A:1026683200895

E. Lumer, Neural dynamics in a model of the thalamocortical system. I. Layers, loops and the emergence of fast synchronous rhythms. Cerebral Cortex, pp.207-234, 1997.

E. Lumer, G. Edelman, and G. Tononi, Neural dynamics in a model of the thalamocortical system. II. The role of neural synchrony tested through perturbations of spike timing. Cereb Cortex, pp.228-264, 1997.

M. Dhamala, V. Jirsa, and M. Ding, Enhancement of Neural Synchrony by Time Delay, Physical Review Letters, vol.92, issue.7, pp.74104-14995856, 2004.
DOI : 10.1103/PhysRevLett.92.074104

O. Jensen and A. Mazaheri, Shaping Functional Architecture by Oscillatory Alpha Activity: Gating by Inhibition, Frontiers in Human Neuroscience, vol.4, p.21119777, 2010.
DOI : 10.3389/fnhum.2010.00186

A. Engel, P. Fries, and W. Singer, Dynamic predictions: Oscillations and synchrony in top???down processing, Nature Reviews Neuroscience, vol.51, issue.10, pp.704-720, 2001.
DOI : 10.1038/35094565

M. Reinacher, R. Becker, A. Villringer, and P. Ritter, Oscillatory brain states interact with late cognitive components of the somatosensory evoked potential, Journal of Neuroscience Methods, vol.183, issue.1, pp.49-56, 2009.
DOI : 10.1016/j.jneumeth.2009.06.036

F. Freyer, R. Becker, H. Dinse, and P. Ritter, State-Dependent Perceptual Learning, Journal of Neuroscience, vol.33, issue.7, pp.2900-2907, 2013.
DOI : 10.1523/JNEUROSCI.4039-12.2013

F. Freyer, M. Reinacher, G. Nolte, H. Dinse, and P. Ritter, Repetitive tactile stimulation changes resting-state functional connectivity???implications for treatment of sensorimotor decline, Frontiers in Human Neuroscience, vol.6, p.22654748, 2012.
DOI : 10.3389/fnhum.2012.00144

R. Becker, M. Pefkou, C. Michel, and A. Hervais-adelman, Left temporal alpha-band activity reflects single word intelligibility, Frontiers in Systems Neuroscience. Frontiers, vol.7, 2013.

P. Ritter, J. Born, M. Brecht, H. Dinse, U. Heinemann et al., State-dependencies of learning across brain scales, Frontiers in Computational Neuroscience, vol.8, 2015.
DOI : 10.1038/nn1369

W. Klimesch, EEG-alpha rhythms and memory processes, International Journal of Psychophysiology, vol.26, issue.1-3, pp.319-359, 1997.
DOI : 10.1016/S0167-8760(97)00773-3

N. Busch, J. Dubois, and R. Vanrullen, The Phase of Ongoing EEG Oscillations Predicts Visual Perception, Journal of Neuroscience, vol.29, issue.24, pp.7869-76, 2009.
DOI : 10.1523/JNEUROSCI.0113-09.2009

URL : https://hal.archives-ouvertes.fr/hal-00402080

O. Jensen, M. Bonnefond, and R. Vanrullen, An oscillatory mechanism for prioritizing salient unattended stimuli . Trends in Cognitive Sciences, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00685973

P. Ritter, M. Moosmann, and A. Villringer, Rolandic alpha and beta EEG rhythms' strengths are inversely related to fMRI-BOLD signal in primary somatosensory and motor cortex, Human Brain Mapping, vol.47, issue.4, pp.1168-87, 2009.
DOI : 10.1002/hbm.20585

D. Roy, R. Sigala, M. Breakspear, A. Mcintosh, V. Jirsa et al., Using the Virtual Brain to Reveal the Role of Oscillations and Plasticity in Shaping Brain's Dynamical Landscape, Brain Connectivity, vol.4, issue.10
DOI : 10.1089/brain.2014.0252

S. Leon, P. Knock, S. Woodman, M. Domide, L. Mersmann et al., The Virtual Brain: a simulator of primate brain network dynamics

C. Assisi, V. Jirsa, and J. Kelso, Synchrony and Clustering in Heterogeneous Networks with Global Coupling and Parameter Dispersion, Physical Review Letters, vol.94, issue.1, pp.18106-15698140, 2005.
DOI : 10.1103/PhysRevLett.94.018106

R. Stefanescu and V. Jirsa, Reduced representations of heterogeneous mixed neural networks with synaptic coupling, Physical Review E, vol.83, issue.2, p.26204, 2011.
DOI : 10.1103/PhysRevE.83.026204

C. Landisman, M. Long, M. Beierlein, M. Deans, D. Paul et al., Electrical synapses in the thalamic reticular nucleus, Journal of Neuroscience Feb, vol.1, issue.223, pp.1002-1011, 2002.

R. Manella, INTEGRATION OF STOCHASTIC DIFFERENTIAL EQUATIONS ON A COMPUTER, International Journal of Modern Physics C, vol.13, issue.09, pp.1177-94, 2002.
DOI : 10.1142/S0129183102004042

N. Logothetis, J. Pauls, M. Augath, T. Trinath, and A. Oeltermann, Neurophysiological investigation of the basis of the fMRI signal, Nature Jul, vol.12, issue.4126843, pp.150-157, 2001.

S. Burns, D. Xing, and R. Shapley, Comparisons of the Dynamics of Local Field Potential and Multiunit Activity Signals in Macaque Visual Cortex, Journal of Neuroscience, vol.30, issue.41, pp.13739-13788, 2010.
DOI : 10.1523/JNEUROSCI.0743-10.2010

F. Lopes-da-silva, S. Van-leeuwen, and W. , The cortical source of the alpha rhythm, Neuroscience Letters, vol.6, issue.2-3, pp.237-278, 1977.
DOI : 10.1016/0304-3940(77)90024-6

P. Sanz-leon, S. Knock, A. Spiegler, and V. Jirsa, Mathematical framework for large-scale brain network modelling in The Virtual Brain, Neuroimage, 2015.