A. M. Kelly and H. Garavan, Human functional neuroimaging of brain changes associated with practice, Cerebral Cortex, vol.15, issue.8, pp.1089-1102, 2005.

B. Horwitz, M. A. Tagamets, and A. R. Mcintosh, Neural modeling, functional brain imaging, and cognition, Trends in Cognitive Sciences, vol.3, issue.3, pp.91-98, 1999.

M. M. Mesulam, From sensation to cognition, Brain, vol.121, pp.1013-1052, 1998.

S. L. Bressler, Large-scale cortical networks and cognition, Brain Research Reviews, vol.20, issue.3, pp.288-304, 1995.

G. Tononi, G. M. Edelman, and O. Sporns, Complexity and coherence: Integrating information in the brain, Trends in Cognitive Sciences, vol.2, pp.474-484, 1998.

O. Sporns, Organization, development and function of complex brain networks, Trends in Cognitive Science, vol.8, issue.9, pp.418-425, 2004.

G. L. Gerstein and D. H. Perkel, Simultaneously recorded trains of action potentials: Analysis and functional interpretation, Science, vol.164, issue.881, pp.828-830, 1969.

K. Friston, Functional and effective connectivity in neuroimaging: A synthesis, Human Brain Mapping, vol.2, pp.56-78, 1994.

A. Mcintosh and F. Gonzalez-lima, Structural equation modeling and its application to network analysis in functional brain imaging, Human Brain Mapping, vol.2, pp.2-22, 1994.

A. Aersten and H. Preissl, Dynamics of activity and connectivity in physiological neuronal networks, NonLinear Dynamics and Neuronal Networks, pp.281-302, 1991.

C. Buchel and K. Friston, Assessing interactions among neuronal systems using functional neuroimaging, Neural Networks, vol.13, issue.8-9, pp.871-82, 2000.

R. Henson, Analysis of fMRI time series: Linear timeinvariant models, event-related fMRI, and optimal experimental design, Human Brain Function, pp.793-823, 2004.

K. E. Stephan, Biophysical models of fMRI responses, Current Opinion Neurobiology, vol.14, issue.5, pp.629-635, 2004.

R. Goebel, Investigating directed cortical interactions in time-resolved fMRI data using vector autoregressive modeling and Granger causality mapping, Magnetic Resonance Imaging, vol.21, issue.10, pp.1251-1261, 2003.

R. Baumgartner, Comparison of two exploratory data analysis methods for fMRI: Fuzzy clustering vs. principal component analysis, Magnetic Resonance Imaging, vol.18, issue.1, pp.89-94, 2000.

R. Baumgartner, Resampling as a cluster validation technique in fMRI, Journal of Magnetic Resonance Imaging, vol.11, issue.2, pp.228-231, 2000.

R. Baumgartner, C. Windischberger, and E. Moser, Quantification in functional magnetic resonance imaging: Fuzzy clustering vs. correlation analysis, Magnetic Resonance Imaging, vol.16, issue.2, pp.115-125, 1998.

D. Cordes, Hierarchical clustering to measure connectivity in fMRI resting-state data, Magnetic Resonance Imaging, vol.20, pp.305-317, 2002.

C. Goutte, On clustering fMRI time series, Neuroimage, vol.9, issue.3, pp.298-310, 1999.

K. J. Friston, Psychophysiological and modulatory interactions in neuroimaging, Neuroimage, vol.6, issue.3, pp.218-229, 1997.

S. Fall and G. De-marco, Assessment of brain interactivity in the motor cortex from the concept of functional connectivity and spectral analysis of fMRI data, Biological Cybernetics, vol.98, issue.2, pp.101-114, 2008.

F. T. Sun, L. M. Miller, and M. D'esposito, Measuring temporal dynamics of functional networks using phase spectrum of fMRI data, Neuroimage, vol.28, issue.1, pp.227-237, 2005.

K. Muller, On multivariate spectral analysis of fMRI time series, Neuroimage, vol.14, issue.2, pp.347-356, 2001.

K. J. Friston, Functional connectivity: The principal-component analysis of large (PET) data sets, Journal of Cerebral Blood Flow & Metabolism, vol.13, issue.1, pp.5-14, 1993.

A. H. Andersen, D. M. Gash, and M. J. Avison, Principal component analysis of the dynamic response measured by fMRI: A generalized linear systems framework, Magnetic Resonance Imaging, vol.17, issue.6, pp.795-815, 1999.

E. T. Bullmore, Functional magnetic resonance image analysis of a large-scale neurocognitive network, Neuroimage, vol.4, issue.1, pp.16-33, 1996.

P. R. Karunanayaka, Age-related connectivity changes in fMRI data from children listening to stories, Neuroimage, vol.34, issue.1, pp.349-360, 2007.

N. Correa, T. Adali, and V. D. Calhoun, Performance of blind source separation algorithms for fMRI analysis using a group ICA method, Magnetic Resonance Imaging, vol.25, issue.5, pp.684-694, 2007.

V. D. Calhoun, Latency (in) sensitive ICA. Group independent component analysis of fMRI data in the temporal frequency domain, Neuroimage, vol.20, issue.3, pp.1661-1669, 2003.

M. J. Jafri, A method for functional network connectivity among spatially independent resting-state components in schizophrenia, Neuroimage, vol.39, issue.4, pp.1666-1681, 2008.

A. Hyvärinen, Fast and robust fixed-point algorithms for independent component analysis, IEEE Transactions on Neural Networks, vol.10, pp.626-634, 1999.

F. Esposito, Spatial independent component analysis of functional MRI time-series: To what extent do results depend on the algorithm used?, Human Brain Mapping, vol.16, issue.3, pp.146-157, 2002.

C. F. Beckmann and S. M. Smith, Probabilistic independent component analysis for functional magnetic resonance imaging, IEEE Transactions on Medical Imaging, vol.23, issue.2, pp.137-152, 2004.

M. J. Mckeown and T. J. Sejnowski, Independent component analysis of fMRI data: Examining the assumptions, Human Brain Mapping, vol.6, issue.5-6, pp.368-372, 1998.

M. J. Mckeown, Analysis of fMRI data by blind separation into independent spatial components, Human Brain Mapping, vol.6, issue.3, pp.160-188, 1998.

D. Hu, Unified SPM-ICA for fMRI analysis, Neuroimage, vol.25, issue.3, pp.746-755, 2005.

B. Hong, G. D. Pearlson, and V. D. Calhoun, Source density-driven independent component analysis approach for fMRI data, Human Brain Mapping, vol.25, issue.3, pp.297-307, 2005.

M. J. Mckeown, Detection of consistently task-related activations in fMRI data with hybrid independent component analysis, Neuroimage, vol.11, issue.1, pp.24-35, 2000.

F. T. Sun, L. M. Miller, and M. D'esposito, Measuring interregional functional connectivity using coherence and partial coherence analyses of fMRI data, Neuroimage, vol.21, issue.2, pp.647-458, 2004.

L. J. Marchini and B. D. Ripley, A new statistical approach to detecting significant activation in funtional MRI, Neuroimage, vol.12, pp.366-380, 2000.

C. Andrew and G. Pfurtscheller, Event-related coherence as a tool for studying dynamic interaction of brain regions, Electroencephalography and Clinical Neurophysiology, vol.98, issue.2, pp.144-148, 1996.

J. Classen, Integrative visuomotor behavior is associated with interregionally coherent oscillations in the human brain, Journal of Neurophysiology, vol.79, issue.3, pp.1567-1573, 1998.

F. G. Andres, Functional coupling of human cortical sensorimotor areas during bimanual skill acquisition, Brain, vol.122, pp.855-870, 1999.

P. Rappelsberger and H. Petsche, Probability mapping: Power and coherence analyses of cognitive processes, Brain Topography, vol.1, issue.1, pp.46-54, 1988.

T. Locatelli, EEG coherence in Alzheimer's disease, Electroencephalography and Clinical Neurophysiology, vol.106, issue.3, pp.229-237, 1998.

K. and L. Roc'h-;-besthorn, EEG coherence in Alzheimer disease, Electroencephalography and Clinical Neurophysiology, vol.91, issue.3, pp.232-233, 1994.

C. Besthorn, EEG coherence in Alzheimer disease, Electroencephalography and Clinical Neurophysiology, vol.90, issue.3, pp.242-245, 1994.

N. K. Logothetis, Neurophysiological investigation of the basis of the fMRI signal, Nature, vol.412, issue.6843, pp.150-157, 1636.

A. R. Mcintosh and F. Gonzalez-lima, Structural equation modeling and its application to network analysis in functional brain imaging, Human Brain Mapping, vol.2, pp.2-22, 1994.

M. Glabus, Interindividual differences in functional interactions among prefrontal, parietal and parahippocampal regions during working memory, Cerebral Cortex, vol.13, pp.1352-1361, 2003.

M. S. Goncalves and D. A. Hall, Connectivity analysis with structural equation modelling: An example of the effects of voxel selection, Neuroimage, vol.20, issue.3, pp.1455-1467, 2003.

A. Mcintosh, Network analysis of cortical visual pathways mapped with PET, Journal of Neuroscience, vol.14, pp.655-666, 1994.

C. Büchel and K. Friston, Assessing interactions among neuronal systems using functional neuroimaging, Neural Networks, vol.13, issue.8-9, pp.871-882, 2000.

T. Taniwaki, Age-related alterations of the functional interactions within the basal ganglia and cerebellar motor loops in vivo, Neuroimage, vol.36, issue.4, pp.1263-1276, 2007.

J. G. Craggs, Functional brain interactions that serve cognitive-affective processing during pain and placebo analgesia, Neuroimage, vol.38, issue.4, pp.720-729, 2007.

L. Harrison, D. Penny, and K. Friston, Multivariate autoregressive modeling of fMRI time series, Neuroimage, vol.19, issue.4, pp.1477-1491, 2003.

J. Kim, Unified structural equation modeling approach for the analysis of multisubject, multivariate functional MRI data, Human Brain Mapping, vol.28, issue.2, pp.85-93, 2007.

W. D. Penny, Comparing dynamic causal models, Neuroimage, vol.22, issue.3, pp.1157-1172, 2004.

W. D. Penny, Modelling functional integration: A comparison of structural equation and dynamic causal models, Neuroimage, vol.23, pp.264-274, 2004.

K. J. Friston, L. Harrison, and W. Penny, Dynamic causal modeling, Neuroimage, vol.19, issue.4, pp.1273-1302, 2003.
URL : https://hal.archives-ouvertes.fr/inserm-00388967

O. David and K. J. Friston, A neural mass model for MEG/EEG: Coupling and neuronal dynamics, Neuroimage, vol.20, issue.3, pp.1743-1755, 2003.

O. David, D. Cosmelli, and K. J. Friston, Evaluation of different measures of functional connectivity using a neural mass model, Neuroimage, vol.21, issue.2, pp.659-673, 2004.

B. Horwitz, Relating fMRI and PET signals to neural activity by means of large-scale neural models, Neuroinformatics, vol.2, issue.2, pp.251-266, 2004.

F. T. Husain, Relating neuronal dynamics for auditory object processing to neuroimaging activity: A computational modeling and an fMRI study, Neuroimage, vol.21, issue.4, pp.1701-1720, 2004.

M. A. Tagamets and B. Horwitz, Integrating electrophysiological and anatomical experimental data to create a large-scale model that simulates a delayed match-to-sample human brain imaging study, Cerebral Cortex, vol.8, issue.4, pp.310-320, 1998.

J. Loehlin, Latent variable models: An introduction to factor, path, and structural analysis, Lawrence Erlbaum, 1998.

K. G. Jöreskog and D. Sörbom, LISREL 8.5 user's reference guide, Scientific Software International, 2000.

K. Bollen, With new incremental structural index for general equation models made, Sociological Methods and Research, vol.17, pp.303-316, 1989.

K. Bollen and J. Long, Testing structural equation models, Sage, 1993.

A. Mcintosh, Understanding neural interactions in learning and memory using function neuroimaging, Annals of the New York Academy of Sciences, vol.855, pp.556-571, 1998.

A. Mcintosh and F. Gonzales-lima, Structural modeling of functional neural pathways mapped with 2-deoxyglucose; effects of acoustic startle habituation on the auditory system 7, Brain Research, vol.547, pp.295-302, 1991.

A. Mcintosh and F. Gonzales-lima, Network interactions among limbic cortices, basal forebrain, and cerebellum differentiate a tone conditioned as a Pavlovian excitor or inhibitor: Fluorodeoxyglucose mapping and covariance structural modeling, Journal of Neurophysiology, vol.72, pp.1717-1733, 1994.

C. Büchel, J. Coull, and K. Friston, The predictive value of changes in effective connectivity for human learning, Science, vol.283, pp.1538-1541, 1999.

C. Büchel and K. J. Friston, Modulation of connectivity in visual pathways by attention: Cortical interactions evaluated with structural equation modelling and fMRI, Cerebral Cortex, vol.7, issue.8, pp.768-778, 1997.

E. Bullmore, How good is good enough in path analysis of fMRI data, Neuroimage, vol.11, issue.4, pp.289-301, 2000.

P. Fletcher, Learning-related neuronal responses in prefrontal cortex studied with functional neuroimaging, Cerebral Cortex, vol.9, pp.168-178, 1999.

S. Grafton, Network analysis of motor system connectivity in Parkinson's disease: Modulation of thalamocortical interactions after pallidotomy, Human Brain Mapping, vol.2, pp.45-55, 1994.

G. Honey, Effects of verbal working memory load on corticocortical connectivity modeled by path analysis of functional magnetic resonance imaging data, Neuroimage, vol.17, pp.573-582, 2002.

J. Jennings, A. Mcintosh, and S. Kapur, Mapping neural interactivity onto regional activity: An analysis of semantic processing and response mode interactions, Neuroimage, vol.7, pp.244-254, 1998.

M. Hollander, Nonparametric statistical methods, Wiley Series in Probability and Statistics: Applied Probability and Statistic, 1999.

R. Kline, Principles and practice of structural equation modeling (methodology in the social sciences), 2004.

B. Byrne, Structural equation modeling with Amos: BASIC concepts, applications, and programming, 2001.

G. Marrelec, Using partial correlation to enhance structural equation modeling of functional MRI data, Magnetic Resonance Imaging, vol.25, issue.8, pp.1181-1189, 2007.
URL : https://hal.archives-ouvertes.fr/inserm-00140817

G. Marrelec, Large-scale neural model validation of partial correlation analysis for effective connectivity investigation in functional MRI, Human Brain Mapping, 2008.

B. P. Rogers, Assessing functional connectivity in the human brain by fMRI, Magnetic Resonance Imaging, vol.25, issue.10, pp.1347-1357, 2007.

B. P. Rogers, Comment on 'Assessing functional connectivity in the human brain by fMRI, Magnetic Resonance Imaging, vol.26, issue.1, p.146, 2008.

M. V. Au-duong, Modulation of effective connectivity inside the working memory network in patients at the earliest stage of multiple sclerosis, Neuroimage, vol.24, issue.2, pp.533-538, 2005.

M. F. Glabus, Interindividual differences in functional interactions among prefrontal, parietal and parahippocampal regions during working memory, Cerebral Cortex, vol.13, issue.12, pp.1352-1361, 2003.

R. G. Schlosser, G. Wagner, and H. Sauer, Assessing the working memory network: Studies with functional magnetic resonance imaging and structural equation modeling, Neuroscience, vol.139, issue.1, pp.91-103, 2006.

R. Schlosser, Altered effective connectivity during working memory performance in schizophrenia: A study with fMRI and structural equation modeling, Neuroimage, vol.19, issue.3, pp.751-763, 2003.

H. Kondo, Functional roles of the cingulo-frontal network in performance on working memory, Neuroimage, vol.21, issue.1, pp.2-14, 2004.

J. B. Krause, Imaging and neural modeling in episodic and working memory processes, Neural Networks, vol.13, issue.8-9, pp.847-859, 2000.

R. A. Charlton, A structural equation modeling investigation of age-related variance in executive function and DTI measured white matter damage, Neurobiology of Aging, 2007.

J. Rowe, Attention to action: Specific modulation of corticocortical interactions in humans, Neuroimage, vol.17, issue.2, pp.988-998, 2002.

F. M. Mottaghy, Systems level modeling of a neuronal network subserving intrinsic alertness, Neuroimage, vol.29, issue.1, pp.225-233, 2006.

K. I. Erickson, A structural equation modeling analysis of attentional control: An event-related fMRI study, Cognitive Brain Research, vol.22, issue.3, pp.349-357, 2005.

M. N. Rajah, A. R. Mcintosh, and C. L. Grady, Frontotemporal interactions in face encoding and recognition, Cognitive Brain Research, vol.8, issue.3, pp.259-269, 1999.

G. De-marco, Changes in effective connectivity during incidental and intentional perception of fearful faces, Neuroimage, vol.30, issue.3, pp.1030-1037, 2006.

J. L. Stein, A validated network of effective amygdala connectivity, Neuroimage, vol.36, issue.3, pp.736-745, 2007.

B. P. Rogers, J. D. Carew, and M. E. Meyerand, Hemispheric asymmetry in supplementary motor area connectivity during unilateral finger movements, Neuroimage, vol.22, issue.2, pp.855-859, 2004.

S. T. Grafton, Network analysis of motor system connectivity in Parkinson's disease: Modulation of thalamocortical interactions after pallidotomy, Human Brain Mapping, vol.2, pp.45-55, 1994.

I. Toni, Changes of cortico-striatal effective connectivity during visuomotor learning, Cerebral Cortex, vol.12, issue.10, pp.1040-1047, 2002.

T. Taniwaki, Functional network of the basal ganglia and cerebellar motor loops in vivo: Different activation patterns between self-initiated and externally triggered movements, Neuroimage, vol.31, issue.2, pp.745-753, 2006.

J. Zhuang, Connectivity exploration with structural equation modeling: An fMRI study of bimanual motor coordination, Neuroimage, vol.25, issue.2, pp.462-470, 2004.

A. R. Laird, Modeling motor connectivity using TMS/PET and structural equation modeling, 2008.

V. Quaglino, Differences in effective connectivity between dyslexic children and normal readers during a pseudoword reading task: An fMRI study, Clinical Neurophysiology, vol.38, issue.2, pp.73-82, 2008.
URL : https://hal.archives-ouvertes.fr/hal-02310864

C. H. Fu, Modulation of effective connectivity by cognitive demand in phonological verbal fluency, Neuroimage, vol.30, issue.1, pp.266-271, 2006.

B. Horwitz, K. J. Friston, and J. G. Taylor, Neural modeling and functional brain imaging: An overview, Neural Networks, vol.13, issue.8-9, pp.829-846, 2000.

L. Lee, L. Harrison, and A. Mechelli, A report of the functional connectivity, pp.457-465, 2003.

A. Mcintosh, Towards a network theory of cognition, Neural Networks, vol.13, pp.861-876, 2001.

B. Horwitz, The elusive concept of brain connectivity, Neuroimage, vol.19, issue.2, pp.466-470, 2003.

F. Gonzalez-lima and A. Mcintosh, Analysis of neural network interactions related to associative learning using structural equation modeling, Mathematics and Computers in Simulation, vol.40, pp.115-140, 1995.

A. Roebroeck, E. Formisano, and R. Goebel, Mapping directed influence over the brain using Granger causality and fMRI, Neuroimage, vol.25, issue.1, pp.230-242, 2005.

I. Korhonen, Linear multivariate models for physiological signal analysis: Theory, Computer Methods Programs in Biomedicine, vol.51, issue.1-2, pp.85-94, 1996.

I. Korhonen, R. Takalo, and V. Turjanmaa, Multivariate autoregressive model with immediate transfer paths for assessment of interactions between cardiopulmonary variability signals, Medical & Biology Engineering & Computer, vol.34, issue.3, pp.199-206, 1996.

K. E. Stephan, Dynamic causal models of neural system dynamics: Current state and future extensions, Journal of Bioscience, vol.32, issue.1, pp.129-144, 2007.
URL : https://hal.archives-ouvertes.fr/inserm-00381759

R. B. Buxton, E. C. Wong, and L. R. Frank, Dynamics of blood flow and oxygenation changes during brain activation: The balloon model, Magnetic Resonance in Medicine, vol.39, issue.6, pp.855-864, 1998.

K. J. Friston, Nonlinear responses in fMRI: The Balloon model, Volterra kernels, and other hemodynamics, Neuroimage, vol.12, issue.4, pp.466-477, 2000.

P. J. Basser and D. K. Jones, Diffusion-tensor MRI: Theory, experimental design and data analysis-a technical review, NMR Biomedicine, vol.15, issue.7-8, pp.456-467, 2002.

P. J. Basser, J. Mattiello, and D. Lebihan, Estimation of the effective self-diffusion tensor from the NMR spin echo, Journal of Magnetic Resonance B, vol.103, issue.3, pp.247-254, 1994.
URL : https://hal.archives-ouvertes.fr/hal-00349722

D. J. Werring, The structural and functional mechanisms of motor recovery: Complementary use of diffusion tensor and functional magnetic resonance imaging in a traumatic injury of the internal capsule, Neurosurgery & Psychiatry, vol.65, pp.863-869, 1998.

D. J. Werring, A direct demonstration of both structure and function in the visual system: Combining diffusion tensor imaging with functional magnetic resonance imaging, Neuroimage, vol.9, pp.352-361, 1999.

U. C. Wieshmann, Combined functional magnetic resonance imaging and diffusion tensor imaging demonstrate widespread modified organization in malformation of cortical development, Journal of Neurology, Neurosurgery & Psychiatry, vol.70, pp.521-523, 2001.

P. J. Olesen, Combined analysis of DTI and fMRI data reveals a joint maturation of white and grey matter in a fronto-parietal network, Cognitive Brain Research, vol.18, issue.1, pp.48-57, 2003.

F. Gonzalez-lima and A. R. Mcintosh, Analysis of neural interactions related to associative learning using structural equation modeling, Mathematics and Computers in Simulation, vol.40, pp.115-140, 1995.

A. Mechelli, Effective connectivity and intersubject variability: Using a multisubject network to test differences and commonalities, Neuroimage, vol.17, issue.3, pp.1459-1469, 2002.