Brain functional modeling, what do we measure with fMRI data?

Neuroscience Research

Volumn 64, Issue 1, 2009, Pages 12-19

  de Marco, G ^a   Devauchelle, B ^a   Berquin, P ^a  

^a AMIENS UNIVERSITY HOSPITAL   (France)

Author keywords

DCM; fMRI; Model; Network; SEM

Indexed keywords

NEUROTRANSMITTER;

ARTICLE; BRAIN DEVELOPMENT; BRAIN FUNCTION; BRAIN MAPPING; BRAIN REGION; CAUSAL MODELING; DYNAMIC CAUSAL MODELING; ELECTROENCEPHALOGRAM; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HYPOTHESIS; INDEPENDENT COMPONENT ANALYSIS; INFORMATION PROCESSING; INTERMETHOD COMPARISON; NERVE CELL NETWORK; NERVE CELL PLASTICITY; NEUROIMAGING; OXYGEN BLOOD LEVEL; PRIORITY JOURNAL; RESPONSE VARIABLE; SPATIAL ORIENTATION; STRUCTURAL EQUATION MODELING;

BRAIN; BRAIN MAPPING; CEREBROVASCULAR CIRCULATION; HUMANS; MAGNETIC RESONANCE IMAGING; MODELS, NEUROLOGICAL; NEURAL PATHWAYS; OXYGEN; TIME FACTORS;

EID: 64249094266     PISSN: 01680102     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neures.2009.01.015     Document Type: Article

References (117)

1. Aersten A., and Preissl H. Dynamics of activity and connectivity in physiological neuronal networks. In: Schuster H.G. (Ed). Non Linear Dynamics and Neuronal Networks (1991), VCH Publishers Inc., New York 281-302
2. Aguirre G.K., Zarahn E., and D'Esposito M. The variability of human, BOLD hemodynamic responses. Neuroimage 8 (1998) 360-369
3. Andersen A.H., Gash D.M., and Avison M.J. Principal component analysis of the dynamic response measured by fMRI: a generalized linear systems framework. Magn. Reson. Imaging 17 (1999) 795-815
4. Arthurs O.J., and Boniface S. How well do we understand the neural origins of the fMRI BOLD signal?. Trends Neurosci. 25 (2002) 27-31
5. Baumgartner R., Windischberger C., and Moser E. Quantification in functional magnetic resonance imaging: fuzzy clustering vs. correlation analysis. Magn. Reson. Imaging 16 (1998) 115-125
6. Beckmann C.F., and Smith S.M. Probabilistic independent component analysis for functional magnetic resonance imaging. IEEE Trans. Med. Imaging 23 (2004) 137-152
7. Birn R.M., Diamond J.B., Smith M.A., and Bandettini P.A. Separating respiratory-variation-related fluctuations from neuronal-activity-related fluctuations in fMRI. Neuroimage 31 (2006) 1536-1548
8. Biswal B., DeYoe A.E., and Hyde J.S. Reduction of physiological fluctuations in fMRI using digital filters. Magn. Reson. Med. 35 (1996) 107-113
9. Bollen K. With new incremental structural index for general equation models made. Sociol. Methods Res. 17 (1989) 303-316
10. Bollen K., and Long J. Testing Structural Equation Models (1993), Sage, Thousand Oaks, CA
11. Bressler S.L. Large-scale cortical networks and cognition. Brain Res. Brain Res. Rev. 20 (1995) 288-304
12. Buchel C., and Friston K. Assessing interactions among neuronal systems using functional neuroimaging. Neural Netw. 13 (2000) 871-882
13. Buchel C., and Friston K.J. Modulation of connectivity in visual pathways by attention: cortical interactions evaluated with structural equation modelling and fMRI. Cereb. Cortex 7 (1997) 768-778
14. Büchel C., and Friston K.J. Modulation of connectivity in visual pathways by attention: cortical interactions evaluated with structural equation modelling and fMRI. Cereb. Cortex 7 (1997) 768-778
15. Buckner R.L. The hemodynamic inverse problem: making inferences about neural activity from measured MRI signals. Proc. Natl. Acad. Sci. U.S.A. 100 (2003) 2177-2179
16. Bullmore E., Horwitz B., Honey G., Brammer M., Williams S., and Sharma T. How good is good enough in path analysis of fMRI data?. Neuroimage 11 (2000) 289-301
17. Buxton R.B., Wong E.C., and Frank L.R. Dynamics of blood flow and oxygenation changes during brain activation: the balloon model. Magn. Reson. Med. 39 (1998) 855-864
18. Calhoun V.D., Adali T., Giuliani N.R., Pekar J.J., Kiehl K.A., and Pearlson G.D. Method for multimodal analysis of independent source differences in schizophrenia: combining gray matter structural and auditory oddball functional data. Hum. Brain Mapp. 27 (2006) 47-62
19. Calhoun V.D., Adali T., Pearlson G.D., and Pekar J.J. Spatial and temporal independent component analysis of functional MRI data containing a pair of task-related waveforms. Hum. Brain Mapp. 13 (2001) 43-53
20. Casado M., Isope P., and Ascher P. Involvement of presynaptic N-methyl-d-aspartate receptors in cerebellar long-term depression. Neuron 33 (2002) 123-130
21. Charlton R.A., Landau S., Schiavone F., Barrick T.R., Clark C.A., Markus H.S., and Morris R.G. A structural equation modeling investigation of age-related variance in executive function and DTI measured white matter damage. Neurobiol. Aging (2007)
22. Correa N., Adali T., and Calhoun V.D. Performance of blind source separation algorithms for fMRI analysis using a group ICA method. Magn. Reson. Imaging 25 (2007) 684-694
23. Craggs J.G., Price D.D., Verne G.N., Perlstein W.M., and Robinson M.M. Functional brain interactions that serve cognitive-affective processing during pain and placebo analgesia. Neuroimage 38 (2007) 720-729
24. Damasio A. Descartes' Error: Emotion, Reason, and the Human Brain (1994), Grosset/Putnam Books
25. Darwin C. The Descent of Man, and Selection in Relation to Sex vol. 2 (1871), John Murray, Londres
26. David O., Cosmelli D., and Friston K.J. Evaluation of different measures of functional connectivity using a neural mass model. Neuroimage 21 (2004) 659-673
27. de Marco G., de Bonis M., Vrignaud P., Henry-Feugeas M.C., and Peretti I. Changes in effective connectivity during incidental and intentional perception of fearful faces. Neuroimage 30 (2006) 1030-1037
28. de Marco G., Vrignaud P., Destrieux C., de Marco D., Testelin S., Devauchelle B., and Berquin P. Principle of structural equation modeling for exploring functional interactivity within a putative network of interconnected brain areas. Magn. Reson. Imaging 27 (2009) 1-12
29. Duyn J.H., Moonen C.T., van Yperen G.H., de Boer R.W., and Luyten P.R. Inflow versus deoxyhemoglobin effects in BOLD functional MRI using gradient echoes at 1.5 T. NMR Biomed. 7 (1994) 83-88
30. Edelman, G. M., 1992. Bright air, Brilliant Fire: On the matter of Mind Editions O Jacob, 368 pp.
31. Esposito F., Formisano E., Seifritz E., Goebel R., Morrone R., Tedeschi G., and Di Salle F. Spatial independent component analysis of functional MRI time-series: to what extent do results depend on the algorithm used?. Hum. Brain Mapp. 16 (2002) 146-157
32. Fall S., and de Marco G. Assessment of brain interactivity in the motor cortex from the concept of functional connectivity and spectral analysis of fMRI data. Biol. Cybern. 98 (2008) 101-114
33. Fields R.D., and Burnstock G. Purinergic signalling in neuron-glia interactions. Nat. Rev. Neurosci. 7 (2006) 423-436
34. Fletcher P., Büchel C., Josephs O., Friston K., and Dolan R. Learning-related neuronal responses in prefrontal cortex studied with functional neuroimaging. Cereb. Cortex 9 (1999) 168-178
35. Frahm J., Merboldt K.D., Hanicke W., Kleinschmidt A., and Boecker H. Brain or vein-oxygenation or flow? On signal physiology in functional MRI of human brain activation. NMR Biomed. 7 (1994) 45-53
36. Friston K. Functional and effective connectivity in neuroimaging: a synthesis. Hum. Brain Mapp. 2 (1994) 56-78
37. Friston K.J., Buechel C., Fink G.R., Morris J., Rolls E., and Dolan R.J. Psychophysiological and modulatory interactions in neuroimaging. Neuroimage 6 (1997) 218-229
38. Friston K.J., Frith C.D., and Frackowiak R.S.J. Time-dependent changes in effective connectivity measured with PET. Hum. Brain Mapp. 1 (1993) 69-79
39. Friston K.J., Frith C.D., Liddle P.F., and Frackowiak R.S. Functional connectivity: the principal-component analysis of large (PET) data sets. J. Cereb. Blood Flow Metab. 13 (1993) 5-14
40. Friston K.J., Mechelli A., Turner R., and Price C.J. Nonlinear responses in fMRI: the Balloon model, Volterra kernels, and other hemodynamics. Neuroimage 12 4 (2000) 466-477
41. Friston K.J., Harrison L., and Penny W. Dynamic causal modelling. Neuroimage 19 (2003) 1273-1302
42. Fu C.H., McIntosh A.R., Kim J., Chau W., Bullmore E.T., Williams S.C., Honey G.D., and McGuire P.K. Modulation of effective connectivity by cognitive demand in phonological verbal fluency. Neuroimage 30 (2006) 266-271
43. Gerstein G.L., and Perkel D.H. Simultaneously recorded trains of action potentials: analysis and functional interpretation. Science 164 (1969) 828-830
44. Goebel R., Roebroeck A., Kim D.S., and Formisano E. Investigating directed cortical interactions in time-resolved fMRI data using vector autoregressive modeling and Granger causality mapping. Magn. Reson. Imaging 21 (2003) 1251-1261
45. Goncalves M.S., and Hall D.A. Connectivity analysis with structural equation modelling: an example of the effects of voxel selection. Neuroimage 20 3 (2003) 1455-1467
46. Gonzalez-Lima F., and McIntosh A. Analysis of neural network interactions related to associative learning using structural equation modeling. Math. Comput. Simulat. 40 (1995) 115-140
47. Gonzalez-Lima F., and McIntosh A.R. Analysis of neural interactions related to associative learning using structural equation modeling. Math. Comput. Simulat. 40 (1995) 115-140
48. Goutte C., Toft P., Rostrup E., Nielsen F., and Hansen L.K. On clustering fMRI time series. Neuroimage 9 (1999) 298-310
49. Handwerker D.A., Ollinger J.M., and D'Esposito M. Variation of BOLD hemodynamic responses across subjects and brain regions and their effects on statistical analyses. Neuroimage 21 (2004) 1639-1651
50. Harel N., Lee S.P., Nagaoka T., Kim D.S., and Kim S.G. Origin of negative blood oxygenation level-dependent fMRI signals. J. Cereb. Blood Flow Metab. 22 (2002) 908-917
51. Harrison L., Penny W.D., and Friston K. Multivariate autoregressive modeling of fMRI time series. Neuroimage 19 (2003) 1477-1491
52. Harrison R.V., Harel N., Panesar J., and Mount R.J. Blood capillary distribution correlates with hemodynamic-based functional imaging in cerebral cortex. Cereb. Cortex 12 (2002) 225-233
53. Henson R. Analysis of fMRI time series: linear time-invariant models, event-related fMRI, and optimal experimental design. In: Frackowiack R., et al. (Ed). Human Brain Function. 2nd ed. (2004), Elsevier, San Diego 793-823
54. Hollander M. Nonparametric statistical methods. Wiley Series in Probability and Statistics: Applied Probability and Statistic. 2nd ed. (1999), Wiley, New York
55. Hong B., Pearlson G.D., and Calhoun V.D. Source density-driven independent component analysis approach for fMRI data. Hum. Brain Mapp. 25 (2005) 297-307
56. Horwitz B. The elusive concept of brain connectivity. Neuroimage 19 (2003) 466-470
57. Horwitz B. Relating fMRI and PET signals to neural activity by means of large-scale neural models. Neuroinformatics 2 (2004) 251-266
58. Horwitz B., Tagamets M.A., and McIntosh A.R. Neural modeling, functional brain imaging, and cognition. Trends Cogn. Sci. 3 (1999) 91-98
59. Horwitz B., Warner B., Fitzer J., Tagamets M.A., Husain F.T., and Long T.W. Investigating the neural basis for functional and effective connectivity. Application to fMRI. Philos. Trans. R. Soc. Lond. B: Biol. Sci. 360 (2005) 1093-1108
60. Hu D., Yan L., Liu Y., Zhou Z., Friston K.J., Tan C., and Wu D. Unified SPM-ICA for fMRI analysis. Neuroimage 25 (2005) 746-755
61. Huettel S.A., and McCarthy G. Evidence for a refractory period in the hemodynamic response to visual stimuli as measured by MRI. Neuroimage 11 (2000) 547-553
62. Huettel S.A., and McCarthy G. Regional differences in the refractory period of the hemodynamic response: an event-related fMRI study. Neuroimage 14 (2001) 967-976
63. Hyvärinen A. Fast and robust fixed-point algorithms for independent component analysis. IEEE Trans. Neural Network 10 (1999) 626-634
64. Iidaka T., Omori M., Murata T., Kosaka H., Yonekura Y., Okada T., and Sadato N. Neural interaction of the amygdala with the prefrontal and temporal cortices in the processing of facial expressions as revealed by fMRI. J. Cogn. Neurosci. 13 (2001) 1035-1047
65. Jacquard A. Transmission between generations: the search for genetic models. Ann. Genet. 25 (1982) 197-200
66. Jafri M.J., Pearlson G.D., Stevens M., and Calhoun V.D. A method for functional network connectivity among spatially independent resting-state components in schizophrenia. Neuroimage 39 (2008) 1666-1681
67. Jöreskog K.G., and Sörbom D. LISREL 8. 5 User's Reference Guide (2000), Scientific Software International, Chicago
68. Kansaku K., Kitazawa S., and Kawano K. Sequential hemodynamic activation of motor areas and the draining veins during finger movements revealed by cross-correlation between signals from fMRI. Neuroreport 9 (1998) 1969-1974
69. Karunanayaka P.R., Holland S.K., Schmithorst V.J., Solodkin A., Chen E.E., Szaflarski J.P., and Plante E. Age-related connectivity changes in fMRI data from children listening to stories. Neuroimage 34 (2007) 349-360
70. Kim J., Zhu W., Chang L., Bentler P.M., and Ernst T. Unified structural equation modeling approach for the analysis of multisubject, multivariate functional MRI data. Hum. Brain Mapp. 28 (2007) 85-93
71. Kim S.G., Richter W., and Ugurbil K. Limitations of temporal resolution in functional MRI. Magn. Reson. Med. 37 (1997) 631-636
72. Kondo H., Morishita M., Osaka N., Osaka M., Fukuyama H., and Shibasaki H. Functional roles of the cingulo-frontal network in performance on working memory. Neuroimage 21 (2004) 2-14
73. Krause J.B., Taylor J.G., Schmidt D., Hautzel H., Mottaghy F.M., and Muller-Gartner H.W. Imaging and neural modelling in episodic and working memory processes. Neural Netw. 13 (2000) 847-859
74. Kruger G., and Glover G.H. Physiological noise in oxygenation-sensitive magnetic resonance imaging. Magn. Reson. Med. 46 (2001) 631-637
75. Lai S., Hopkins A.L., Haacke E.M., Li D., Wasserman B.A., Buckley P., Friedman L., Meltzer H., Hedera P., and Friedland R. Identification of vascular structures as a major source of signal contrast in high resolution 2D and 3D functional activation imaging of the motor cortex at 1.5 T: preliminary results. Magn. Reson. Med. 30 (1993) 387-392
76. Lee A.T., Glover G.H., and Meyer C.H. Discrimination of large venous vessels in time-course spiral blood-oxygen-level-dependent magnetic-resonance functional neuroimaging. Magn. Reson. Med. 33 (1995) 745-754
77. Lee P.R., Cohen J.E., Becker K.G., and Fields R.D. Gene expression in the conversion of early phase to late-phase long-term potentiation. Ann. N.Y. Acad. Sci. 1048 (2005) 259-271
78. Leopold D.A., Murayama Y., and Logothetis N.K. Very slow activity fluctuations in monkey visual cortex: implications for functional brain imaging. Cereb. Cortex 13 (2003) 422-433
79. Liao C.H., Worsley K.J., Poline J.B., Aston J.A., Duncan G.H., and Evans A.C. Estimating the delay of the fMRI response. Neuroimage 16 (2002) 593-606
80. Loehlin J. Latent Variable Models: An Introduction to Factor, Path, and Structural Analysis. 4th ed. (1998), Lawrence Erlbaum, Mahwah, NJ
81. Logothetis N.K., Pauls J., Augath M., Trinath T., and Oeltermann A. Neurophysiological investigation of the basis of the fMRI signal. Nature 412 (2001) 150-157
82. Marrelec G., Bellec P., Krainik A., Duffau H., Pelegrini-Issac M., Lehericy S., Benali H., and Doyon J. Regions, systems, and the brain: hierarchical measures of functional integration in fMRI. Med. Image Anal. (2008)
83. Mathiesen C., Caesar K., Akgoren N., and Lauritzen M. Modification of activity-dependent increases of cerebral blood flow by excitatory synaptic activity and spikes in rat cerebellar cortex. J. Physiol. 512 Pt 2 (1998) 555-566
84. McIntosh A., and Gonzalez-Lima F. Structural equation modeling and its application to network analysis in functional brain imaging. Hum. Brain Mapp. 2 (1994) 2-22
85. McKeown M.J. Detection of consistently task-related activations in fMRI data with hybrid independent component analysis. Neuroimage 11 (2000) 24-35
86. McKeown M.J., Makeig S., Brown G.G., Jung T.P., Kindermann S.S., Bell A.J., and Sejnowski T.J. Analysis of fMRI data by blind separation into independent spatial components. Hum. Brain Mapp. 6 (1998) 160-188
87. McKeown M.J., and Sejnowski T.J. Independent component analysis of fMRI data: examining the assumptions. Hum. Brain Mapp. 6 (1998) 368-372
88. Mechelli A., Penny W.D., Price C.J., Gitelman D.R., and Friston K.J. Effective connectivity and intersubject variability: using a multisubject network to test differences and commonalities. Neuroimage 17 3 (2002) 1459-1469
89. Mesulam M.M. From sensation to cognition. Brain 121 Pt 6 (1998) 1013-1052
90. Mottaghy F.M., Willmes K., Horwitz B., Muller H.W., Krause B.J., and Sturm W. Systems level modeling of a neuronal network subserving intrinsic alertness. Neuroimage 29 (2006) 225-233
91. Nederbragt H. Hierarchical organization of biological systems and the structure of adaptation in evolution and tumorigenesis. J. Theor. Biol. 184 (1997) 149-156
92. Nelson P.G., Yu C., Fields R.D., and Neale E.A. Synaptic connections in vitro: modulation of number and efficacy by electrical activity. Science 244 (1989) 585-587
93. Ngai A.C., Jolley M.A., D'Ambrosio R., Meno J.R., and Winn H.R. Frequency-dependent changes in cerebral blood flow and evoked potentials during somatosensory stimulation in the rat. Brain Res. 837 (1999) 221-228
94. Nomura M., Iidaka T., Kakehi K., Tsukiura T., Hasegawa T., Maeda Y., and Matsue Y. Frontal lobe networks for effective processing of ambiguously expressed emotions in humans. Neurosci. Lett. 348 (2003) 113-116
95. Obata T., Liu T.T., Miller K.L., Luh W.M., Wong E.C., Frank L.R., and Buxton R.B. Discrepancies between BOLD and flow dynamics in primary and supplementary motor areas: application of the balloon model to the interpretation of BOLD transients. Neuroimage 21 (2004) 144-153
96. Penny W.D., Stephan K.E., Mechelli A., and Friston K.J. Comparing dynamic causal models. Neuroimage 22 (2004) 1157-1172
97. Quaglino V., Bourdin B., Czternasty G., Vrignaud P., Fall S., Meyer M.E., Berquin P., Devauchelle B., and de Marco G. Differences in effective connectivity between dyslexic children and normal readers during a pseudoword reading task: an fMRI study. Neurophysiol. Clin. 38 (2008) 73-82
98. Querne L., Berquin P., Vernier-Hauvette M.P., Fall S., Deltour L., Meyer M.E., and de Marco G. Dysfunction of the attentional brain network in children with developmental coordination disorder: a fMRI study. Brain Res. 1244 (2008) 89-102
99. Raichle M.E. Behind the scenes of functional brain imaging: a historical and physiological perspective. Proc. Natl. Acad. Sci. U.S.A. 95 (1998) 765-772
100. Saad Z.S., DeYoe E.A., and Ropella K.M. Estimation of FMRI response delays. Neuroimage 18 (2003) 494-504
101. Saad Z.S., Ropella K.M., Cox R.W., and DeYoe E.A. Analysis and use of FMRI response delays. Hum. Brain Mapp. 13 (2001) 74-93
102. Schlosser R.G., Wagner G., and Sauer H. Assessing the working memory network: studies with functional magnetic resonance imaging and structural equation modeling. Neuroscience 139 (2006) 91-103
103. Sheth S.A., Nemoto M., Guiou M., Walker M., Pouratian N., and Toga A.W. Linear and nonlinear relationships between neuronal activity, oxygen metabolism, and hemodynamic responses. Neuron 42 (2004) 347-355
104. Shmuel A., Augath M., Oeltermann A., and Logothetis N.K. Negative functional MRI response correlates with decreases in neuronal activity in monkey visual area V1. Nat. Neurosci. 9 (2006) 569-577
105. Shmueli K., van Gelderen P., de Zwart J.A., Horovitz S.G., Fukunaga M., Jansma J.M., and Duyn J.H. Low-frequency fluctuations in the cardiac rate as a source of variance in the resting-state fMRI BOLD signal. Neuroimage 38 (2007) 306-320
106. Sporns O., Chialvo D.R., Kaiser M., and Hilgetag C.C. Organization, development and function of complex brain networks. Trends Cogn. Sci. 8 (2004) 418-425
107. Stein J.L., Wiedholz L.M., Bassett D.S., Weinberger D.R., Zink C.F., Mattay V.S., and Meyer-Lindenberg A. A validated network of effective amygdala connectivity. Neuroimage 36 (2007) 736-745
108. Stephan K.E., Harrison L.M., Penny W.D., and Friston K.J. Biophysical models of fMRI responses. Curr. Opin. Neurobiol. 14 (2004) 629-635
109. Stevens M.C., Kiehl K.A., Pearlson G.D., and Calhoun V.D. Functional neural networks underlying response inhibition in adolescents and adults. Behav. Brain Res. 181 (2007) 12-22
110. Taniwaki T., Okayama A., Yoshiura T., Togao O., Nakamura Y., Yamasaki T., Ogata K., Shigeto H., Ohyagi Y., Kira J., and Tobimatsu S. Age-related alterations of the functional interactions within the basal ganglia and cerebellar motor loops in vivo. Neuroimage 36 (2007) 1263-1276
111. Tononi G., Edelman G.M., and Sporns O. Complexity and coherence: integrating information in the brain. Trends Cogn. Sci.. 2 (1998) 474-484
112. Triantafyllou C., Hoge R.D., Krueger G., Wiggins C.J., Potthast A., Wiggins G.C., and Wald L.L. Comparison of physiological noise at 1.5 T, 3 T and 7 T and optimization of fMRI acquisition parameters. Neuroimage 26 (2005) 243-250
113. Varela F., Lachaux J.P., Rodriguez E., and Martinerie J. The brainweb: phase synchronization and large-scale integration. Nat. Rev. Neurosci. 2 (2001) 229-239
114. Waldvogel D., van Gelderen P., Muellbacher W., Ziemann U., Immisch I., and Hallett M. The relative metabolic demand of inhibition and excitation. Nature 406 (2000) 995-998
115. Windischberger C., Langenberger H., Sycha T., Tschernko E.M., Fuchsjager-Mayerl G., Schmetterer L., and Moser E. On the origin of respiratory artifacts in BOLD-EPI of the human brain. Magn. Reson. Imaging 20 (2002) 575-582
116. Wise R.G., Ide K., Poulin M.J., and Tracey I. Resting fluctuations in arterial carbon dioxide induce significant low frequency variations in BOLD signal. Neuroimage 21 (2004) 1652-1664
117. Zhuang J., LaConte S., Peltier S., Zhang K., and Hu X. Connectivity exploration with structural equation modeling: an fMRI study of bimanual motor coordination. Neuroimage 25 (2005) 462-470