International Journal of Biomedical Imaging
Volume 2008 (2008), Article ID 218519, 14 pages
doi:10.1155/2008/218519
Review Article
Contribution of Exploratory Methods to the Investigation of Extended Large-Scale Brain Networks in Functional MRI: Methodologies, Results, and Challenges
1U678, Inserm, Paris 75013, France
2Faculté de Médecine Pitié-Salpêtrière, Université Pierre et Marie Curie, Paris 75013, France
Received 31 August 2007; Accepted 7 December 2007
Academic Editor: Oury Monchi
Copyright © 2008 V. Perlbarg and G. Marrelec. This is an open access article distributed under the
Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Linked References
- W. Chen and S. Ogawa, “Principles of BOLD functional MRI,” in Functional MRI, C. Moonen and P. Bandettini, Eds., pp. 103–113, Springer, Berlin, Germany, 1999.
- S. A. Huettel, A. W. Song, and G. McCarthy, Functional Magnetic Resonance Imaging, Sinauer Associates, Sunderland, Mass, USA, 2004.
- K. J. Friston, A. P. Holmes, J.-B. Poline, et al., “Analysis of fMRI time-series revisited,” NeuroImage, vol. 2, no. 1, pp. 45–53, 1995. View at Publisher · View at Google Scholar · View at PubMed
- K. J. Friston, A. P. Holmes, K. J. Worsley, J.-P. Poline, C. D. Frith, and R. S. J. Frackowiak, “Statistical parametric maps in functional imaging: a general linear approach,” Human Brain Mapping, vol. 2, no. 4, pp. 189–210, 1994. View at Publisher · View at Google Scholar
- K. J. Friston, P. Jezzard, and R. Turner, “Analysis of functional MRI time-series,” Human Brain Mapping, vol. 1, no. 2, pp. 153–171, 1993. View at Publisher · View at Google Scholar
- N. Picard and P. L. Strick, “Imaging the premotor areas,” Current Opinion in Neurobiology, vol. 11, no. 6, pp. 663–672, 2001. View at Publisher · View at Google Scholar
- G. Tononi, O. Sporns, and G. M. Edelman, “A measure for brain complexity: relating functional segregation and integration in the nervous system,” Proceedings of the National Academy of Sciences of the United States of America, vol. 91, no. 11, pp. 5033–5037, 1994. View at Publisher · View at Google Scholar
- S. Zeki and S. Shipp, “The functional logic of cortical connections,” Nature, vol. 335, no. 6188, pp. 311–317, 1988. View at Publisher · View at Google Scholar · View at PubMed
- D. O. Hebb, The Organization of Behavior: A Neurophysiological Theory, John Wiley & Sons, New York, NY, USA, 1949.
- A. R. Luria, “The functional organization of the brain,” Scientific American, vol. 222, no. 3, pp. 66–78, 1970.
- F. Varela, J.-P. Lachaux, E. Rodriguez, and J. Martinerie, “The brainweb: phase synchronization and large-scale integration,” Nature Reviews Neuroscience, vol. 2, no. 4, pp. 229–239, 2001. View at Publisher · View at Google Scholar · View at PubMed
- B. Biswal, F. Z. Yetkin, V. M. Haughton, and J. S. Hyde, “Functional connectivity in the motor cortex of resting human brain using echo-planar MRI,” Magnetic Resonance in Medicine, vol. 34, no. 4, pp. 537–541, 1995. View at Publisher · View at Google Scholar
- B. B. Biswal, J. Van Kylen, and J. S. Hyde, “Simultaneous assessment of flow and BOLD signals in resting-state functional connectivity maps,” NMR in Biomedicine, vol. 10, no. 4-5, pp. 165–170, 1997. View at Publisher · View at Google Scholar
- D. A. Gusnard and M. E. Raichle, “Searching for a baseline: functional imaging and the resting human brain,” Nature Reviews Neuroscience, vol. 2, no. 10, pp. 685–694, 2001. View at Publisher · View at Google Scholar · View at PubMed
- M. E. Raichle and M. A. Mintun, “Brain work and brain imaging,” Annual Review of Neuroscience, vol. 29, pp. 449–476, 2006. View at Publisher · View at Google Scholar · View at PubMed
- R. G. Shulman, D. L. Rothman, K. L. Behar, and F. Hyder, “Energetic basis of brain activity: implications for neuroimaging,” Trends in Neurosciences, vol. 27, no. 8, pp. 489–495, 2004. View at Publisher · View at Google Scholar · View at PubMed
- S. L. Bressler and E. Tognoli, “Operational principles of neurocognitive networks,” International Journal of Psychophysiology, vol. 60, no. 2, pp. 139–148, 2006. View at Publisher · View at Google Scholar · View at PubMed
- M.-M. Mesulam, “From sensation to cognition,” Brain, vol. 121, no. 6, pp. 1013–1052, 1998. View at Publisher · View at Google Scholar
- G. Marrelec, J. Daunizeau, M. Pélégrini-Issac, J. Doyon, and H. Benali, “Conditional correlation as a measure of mediated interactivity in fMRI and MEG/EEG,” IEEE Transactions on Signal Processing, vol. 53, no. 9, pp. 3503–3516, 2005. View at Publisher · View at Google Scholar · View at MathSciNet
- W. Kahle, Atlas de Poche d'Anatomie. 3. Système nerveux et organes des sens, Flammarion, Paris, France, 3rd edition, 2002.
- K. Brodmann, Vergleichende Lokalisationslehre der Großhirnrinde in ihren
Prinzipien dargestellt auf Grund des Zellenbaues, J. A. Barth, Leipzig, Germany, 1909.
- M. F. Bear, B. W. Connors, and M. A. Paradiso, Neuroscience: Exploring the Brain, Lippincott Williams & Wilkins, Baltimore, Md, USA, 2nd edition, 2001.
- R. A. Poldrack, “Can cognitive processes be inferred from neuroimaging data?,” Trends in Cognitive Sciences, vol. 10, no. 2, pp. 59–63, 2006. View at Publisher · View at Google Scholar · View at PubMed
- S. L. Bressler, “Large-scale cortical networks and cognition,” Brain Research Reviews, vol. 20, no. 3, pp. 288–304, 1995. View at Publisher · View at Google Scholar
- K. Friston, “Beyond phrenology: what can neuroimaging tell us about distributed circuitry?,” Annual Review of Neuroscience, vol. 25, pp. 221–250, 2002. View at Publisher · View at Google Scholar · View at PubMed
- D. J. Felleman and D. C. Van Essen, “Distributed hierarchical processing in the primate cerebral cortex,” Cerebral Cortex, vol. 1, no. 1, pp. 1–47, 1991. View at Publisher · View at Google Scholar
- R. Kötter and K. E. Stephan, “Network participation indices: characterizing component roles for information processing in neural networks,” Neural Networks, vol. 16, no. 9, pp. 1261–1275, 2003. View at Publisher · View at Google Scholar · View at PubMed
- J. W. Scannell, G. A. P. C. Burns, C. C. Hilgetag, M. A. O'Neil, and M. P. Young, “The connectional organization of the cortico-thalamic system of the cat,” Cerebral Cortex, vol. 9, no. 3, pp. 277–299, 1999. View at Publisher · View at Google Scholar
- O. Sporns, C. J. Honey, and R. Kötter, “Identification and classification of hubs in brain networks,” PLoS Biology, vol. 2, no. 10, p. e1049, 2007.
- M. P. Young, “Objective analysis of the topological organization of the primate cortical visual system,” Nature, vol. 358, no. 6382, pp. 152–155, 1992. View at Publisher · View at Google Scholar · View at PubMed
- E. Hoshi, L. Tremblay, J. Féger, P. L. Carras, and P. L. Strick, “The cerebellum communicates with the basal ganglia,” Nature Neuroscience, vol. 8, no. 11, pp. 1491–1493, 2005. View at Publisher · View at Google Scholar · View at PubMed
- H. Künzle, “An autoradiographic analysis of the efferent connections from premotor and adjacent
prefrontal regions (areas 6 and 9) in macaca fascicularis,” Brain, Behavior and Evolution, vol. 15, no. 3, pp. 185–234, 1978.
- G. R. Leichnetz, “Afferent and efferent connections of the dorsolateral precentral gyrus
(area 4, hand/arm region) in the macaque monkey, with comparisons to area 8,” Journal of Comparative Neurology, vol. 254, no. 4, pp. 460–492, 1986. View at Publisher · View at Google Scholar · View at PubMed
- T. J. Buschman and E. K. Miller, “Top-down versus bottom-up control of attention in the prefrontal and posterior parietal cortices,” Science, vol. 315, no. 5820, pp. 1860–1864, 2007. View at Publisher · View at Google Scholar · View at PubMed
- G. Buzsáki and A. Draguhn, “Neuronal olscillations in cortical networks,” Science, vol. 304, no. 5679, pp. 1926–1929, 2004. View at Publisher · View at Google Scholar · View at PubMed
- R. T. Knight, “Neural networks debunk phrenology,” Science, vol. 316, no. 5831, pp. 1578–1579, 2007. View at Publisher · View at Google Scholar · View at PubMed
- Y. B. Saalmann, I. N. Pigarev, and T. R. Vidyasagar, “Neural mechanisms of visual attention: how top-down feedback highlights relevant locations,” Science, vol. 316, no. 5831, pp. 1612–1615, 2007. View at Publisher · View at Google Scholar · View at PubMed
- T. Womelsdorf, J.-M. Schoffelen, R. Oostenveld, et al., “Modulation of neuronal interactions through neuronal synchronization,” Science, vol. 316, no. 5831, pp. 1609–1612, 2007. View at Publisher · View at Google Scholar · View at PubMed
- E. Başar, C. Başar-Eroğlu, S. Karakaş, and M. Schürmann, “Gamma, alpha, delta, and theta oscillations govern cognitive processes,” International Journal of Psychophysiology, vol. 39, no. 2--3, pp. 241–248, 2000. View at Publisher · View at Google Scholar
- M. E. Raichle, “Modern phrenology: maps of human cortical function,” Annals of the New York Academy of Sciences, vol. 882, pp. 107–118, 1999. View at Publisher · View at Google Scholar
- D. Cordes, V. M. Haughton, K. Arfanakis, et al., “Mapping functionally related regions of brain with functional connectivity MR imaging,” American Journal of Neuroradiology, vol. 21, no. 9, pp. 1636–1644, 2000.
- M. D. Fox, M. Corbetta, A. Z. Snyder, J. L. Vincent, and M. E. Raichle, “Spontaneous neuronal activity distinguishes human dorsal and ventral attention systems,” Proceedings of the National Academy of Sciences of the United States of America, vol. 103, no. 26, pp. 10046–10051, 2006. View at Publisher · View at Google Scholar · View at PubMed
- M. Hampson, B. S. Peterson, P. Skudlarski, J. C. Gatenby, and J. C. Gore, “Detection of functional connectivity using temporal correlations in MR images,” Human Brain Mapping, vol. 15, no. 4, pp. 247–262, 2002. View at Publisher · View at Google Scholar · View at PubMed
- M. J. Lowe, B. J. Mock, and J. A. Sorenson, “Functional connectivity in single and multislice echoplanar imaging using resting-state fluctuations,” NeuroImage, vol. 7, no. 2, pp. 119–132, 1998. View at Publisher · View at Google Scholar · View at PubMed
- M. Quigley, D. Cordes, G. Wendt, et al., “Effect of focal and nonfocal cerebral lesions on functional connectivity studied with MR imaging,” American Journal of Neuroradiology, vol. 22, no. 2, pp. 294–300, 2001.
- J. L. Vincent, A. Z. Snyder, M. D. Fox, et al., “Coherent spontaneous activity identifies a hippocampal-parietal memory network,” Journal of Neurophysiology, vol. 96, no. 6, pp. 3517–3531, 2006. View at Publisher · View at Google Scholar · View at PubMed
- J. Xiong, L. M. Parsons, J.-H. Gao, and P. T. Fox, “Interregional connectivity to primary motor cortex revealed using MRI resting state images,” Human Brain Mapping, vol. 8, no. 2--3, pp. 151–156, 1999. View at Publisher · View at Google Scholar
- 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, no. 2, pp. 647–658, 2004. View at Publisher · View at Google Scholar · View at PubMed
- 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, no. 1, pp. 227–237, 2005. View at Publisher · View at Google Scholar · View at PubMed
- M. S. Gonçalves and D. A. Hall, “Connectivity analysis with structural equation modelling: an example of the effects of voxel selection,” NeuroImage, vol. 20, no. 3, pp. 1455–1467, 2003. View at Publisher · View at Google Scholar
- J. L. Vincent, G. H. Patel, M. D. Fox, et al., “Intrinsic functional architecture in the anaesthetized monkey brain,” Nature, vol. 447, no. 7140, pp. 83–86, 2007. View at Publisher · View at Google Scholar · View at PubMed
- Y. M. Wang and J. Xia, “Functional interactivity in fMRI using multiple seeds' correlation analyses—novel methods and comparisons,” in Proceedings of the 20th International Conference on Information Processing in Medical Imaging (IPMI '07), N. Karssemeijer and B. P. F. Lelieveldt, Eds., vol. 4584 of Lecture Notes in Computer, pp. 147–159, Springer, Kerkrade, The Netherlands, July 2007.
- 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, no. 6, pp. 795–815, 1999. View at Publisher · View at Google Scholar
- R. Baumgartner, L. Ryner, W. Richter, R. Summers, M. Jarmasz, and R. Somorjai, “Comparison of two exploratory data analysis methods for fMRI: fuzzy clustering vs. principal component analysis,” Magnetic Resonance Imaging, vol. 18, no. 1, pp. 89–94, 2000. View at Publisher · View at Google Scholar
- E. T. Bullmore, S. Rabe-Hesketh, R. G. Morris, et al., “Functional magnetic resonance image analysis of a large-scale neurocognitive network,” NeuroImage, vol. 4, no. 1, pp. 16–33, 1996. View at Publisher · View at Google Scholar · View at PubMed
- R. Baumgartner, C. Windischberger, and E. Moser, “Quantification in functional magnetic resonance imaging: fuzzy clustering vs. correlation analysis,” Magnetic Resonance Imaging, vol. 16, no. 2, pp. 115–125, 1998. View at Publisher · View at Google Scholar
- R. Baumgartner, R. Somorjai, R. Summers, and W. Richter, “Assessment of cluster homogeneity in fMRI data using Kendall's coefficient of concordance,” Magnetic Resonance Imaging, vol. 17, no. 10, pp. 1525–1532, 1999. View at Publisher · View at Google Scholar
- R. Baumgartner, R. Somorjai, R. Summers, W. Richter, and L. Ryner, “Correlator beware: correlation has limited selectivity for fMRI data analysis,” NeuroImage, vol. 12, no. 2, pp. 240–243, 2000. View at Publisher · View at Google Scholar · View at PubMed
- P. Filzmoser, R. Baumgartner, and E. Moser, “A hierarchical clustering method for analyzing functional MR images,” Magnetic Resonance Imaging, vol. 17, no. 6, pp. 817–826, 1999. View at Publisher · View at Google Scholar
- C. Goutte, P. Toft, E. Rostrup, F. Å. Nielsen, and L. K. Hansen, “On clustering fMRI time series,” NeuroImage, vol. 9, no. 3, pp. 298–310, 1999. View at Publisher · View at Google Scholar
- S. J. Peltier, T. A. Polk, and D. C. Noll, “Detecting low-frequency functional connectivity in fMRI using a self-organizing map (SOM) algorithm,” Human Brain Mapping, vol. 20, no. 4, pp. 220–226, 2003. View at Publisher · View at Google Scholar · View at PubMed
- K.-H. Chuang, M.-J. Chiu, C.-C. Lin, and J.-H. Chen, “Model-free functional MRI analysis using Kohonen clustering neural network and fuzzy C-means,” IEEE Transactions on Medical Imaging, vol. 18, no. 12, pp. 1117–1128, 1999. View at Publisher · View at Google Scholar
- D. Cordes, V. Haughton, J. D. Carew, K. Arfanakis, and K. Maravilla, “Hierarchical clustering to measure connectivity in fMRI resting-state data,” Magnetic Resonance Imaging, vol. 20, no. 4, pp. 305–317, 2002. View at Publisher · View at Google Scholar
- J. R. Foucher, P. Vidailhet, S. Chanraud, et al., “Functional integration in schizophrenia: too little or too much? Preliminary results on fMRI data,” NeuroImage, vol. 26, no. 2, pp. 374–388, 2005. View at Publisher · View at Google Scholar · View at PubMed
- G. Tononi, A. R. McIntosh, D. P. Russell, and G. M. Edelman, “Functional clustering: identifying strongly interactive brain regions in neuroimaging data,” NeuroImage, vol. 7, no. 2, pp. 133–149, 1998. View at Publisher · View at Google Scholar · View at PubMed
- M. J. McKeown, S. Makeig, G. G. Brown, et al., “Analysis of fMRI data by blind separation into independent spatial components,” Human Brain Mapping, vol. 6, no. 3, pp. 160–188, 1998. View at Publisher · View at Google Scholar
- K. J. Friston and C. Büchel, “Functional connectivity: eigenimages and multivariate analysis,” in Human Brain Function, pp. 999–1018, Elsevier, San Diego, Calif, USA, 2004.
- C. Ecker, E. Reynaud, S. C. Williams, and M. J. Brammer, “Detecting functional nodes in large-scale cortical networks with functional magnetic resonance imaging:
a principal component analysis of the human visual system,” Human Brain Mapping, vol. 28, no. 9, pp. 817–834, 2007. View at Publisher · View at Google Scholar · View at PubMed
- V. D. Calhoun, T. Adali, J. J. Pekar, and G. D. Pearlson, “Latency (in)sensitive ICA: group independent component analysis of fMRI data in the temporal frequency domain,” NeuroImage, vol. 20, no. 3, pp. 1661–1669, 2003. View at Publisher · View at Google Scholar
- S. Achard, R. Salvador, B. Whitcher, J. Suckling, and E. Bullmore, “A resilient, low-frequency, small-world human brain functional network with highly connected association cortical hubs,” Journal of Neuroscience, vol. 26, no. 1, pp. 63–72, 2006. View at Publisher · View at Google Scholar · View at PubMed
- R. Salvador, J. Suckling, M. R. Coleman, J. D. Pickard, D. Menon, and E. Bullmore, “Neurophysiological architecture of functional magnetic resonance images of human brain,” Cerebral Cortex, vol. 15, no. 9, pp. 1332–2342, 2005. View at Publisher · View at Google Scholar · View at PubMed
- R. Salvador, J. Suckling, C. Schwarzbauer, and E. Bullmore, “Undirected graphs of frequency-dependent functional connectivity in whole brain networks,” Philosophical Transactions of the Royal Society of London Series B, vol. 360, no. 1457, pp. 937–946, 2005. View at Publisher · View at Google Scholar · View at PubMed
- V. D. Calhoun, T. Adali, V. B. McGinty, J. J. Pekar, T. D. Watson, and G. D. Pearlson, “fMRI activation in a visual-perception task:
network of areas detected using the general linear model and independent components analysis,” NeuroImage, vol. 14, no. 5, pp. 1080–1088, 2001. View at Publisher · View at Google Scholar · View at PubMed
- V. D. Calhoun, T. Adali, G. D. Pearlson, and J. J. Pekar, “A method for making group inferences from functional MRI data using independent component analysis,” Human Brain Mapping, vol. 14, no. 3, pp. 140–151, 2001. View at Publisher · View at Google Scholar · View at PubMed
- V. G. van de Ven, E. Formisano, D. Prvulovic, C. H. Roeder, and D. E. J. Linden, “Functional connectivity as revealed by spatial independent component analysis of fMRI measurements during rest,” Human Brain Mapping, vol. 22, no. 3, pp. 165–178, 2004. View at Publisher · View at Google Scholar · View at PubMed
- C. F. Beckmann, M. DeLuca, J. T. Devlin, and S. M. Smith, “Investigations into resting-state connectivity using independent component analysis,” Philosophical Transactions of the Royal Society of London Series B, vol. 360, no. 1457, pp. 1001–1013, 2005. View at Publisher · View at Google Scholar · View at PubMed
- J. S. Damoiseaux, S. A. R. B. Rombouts, F. Barkhof, et al., “Consistent resting-state networks across healthy subjects,” Proceedings of the National Academy of Sciences of the United States of America, vol. 103, no. 37, pp. 13848–13853, 2006. View at Publisher · View at Google Scholar · View at PubMed
- M. De Luca, C. F. Beckmann, N. De Stefano, P. M. Matthews, and S. M. Smith, “fMRI resting state networks define distinct modes of long-distance interactions in the human brain,” NeuroImage, vol. 29, no. 4, pp. 1359–1367, 2006. View at Publisher · View at Google Scholar · View at PubMed
- F. Esposito, T. Scarabino, A. Hyvarinen, et al., “Independent component analysis of fMRI group studies by self-organizing clustering,” NeuroImage, vol. 25, no. 1, pp. 193–205, 2005. View at Publisher · View at Google Scholar · View at PubMed
- P. Bellec, V. Perlbarg, S. Jbabdi, et al., “Identification of large-scale networks in the brain using fMRI,” NeuroImage, vol. 29, no. 4, pp. 1231–1243, 2006. View at Publisher · View at Google Scholar · View at PubMed
- N. Tzourio-Mazoyer, B. Landeau, D. Papathanassiou, et al., “Automated anatomical labeling of activations in SPM using a macroscopic anatomical
parcellation of the MNI MRI single-subject brain,” NeuroImage, vol. 15, no. 1, pp. 273–289, 2002. View at Publisher · View at Google Scholar · View at PubMed
- Y. Lu, T. Jiang, and Y. Zang, “Region growing method for the analysis of functional MRI data,” NeuroImage, vol. 20, no. 1, pp. 455–465, 2003. View at Publisher · View at Google Scholar
- P. Fransson, “Spontaneous low-frequency BOLD signal fluctuations:
an fMRI investigation of the resting-state default mode of brain function hypothesis,” Human Brain Mapping, vol. 26, no. 1, pp. 15–29, 2005. View at Publisher · View at Google Scholar · View at PubMed
- P. Fransson, “How default is the default mode of brain function? Further evidence from intrinsic BOLD signal fluctuations,” Neuropsychologia, vol. 44, no. 14, pp. 2836–2845, 2006. View at Publisher · View at Google Scholar · View at PubMed
- M. D. Greicius, B. Krasnow, A. L. Reiss, and V. Menon, “Functional connectivity in the resting brain: a network analysis of the default mode hypothesis,” Proceedings of the National Academy of Sciences of the United States of America, vol. 100, no. 1, pp. 253–258, 2003. View at Publisher · View at Google Scholar · View at PubMed
- M. D. Greicius and V. Menon, “Default-mode activity during a passive sensory task: uncoupled from deactivation but impacting activation,” Journal of Cognitive Neuroscience, vol. 16, no. 9, pp. 1484–1492, 2004. View at Publisher · View at Google Scholar · View at PubMed
- M. D. Fox, A. Z. Snyder, J. L. Vincent, M. Corbetta, D. C. Van Essen, and M. E. Raichle, “The human brain is intrinsically organized into dynamic, anticorrelated functional networks,” Proceedings of the National Academy of Sciences of the United States of America, vol. 102, no. 27, pp. 9673–9678, 2005. View at Publisher · View at Google Scholar · View at PubMed
- T. Stein, C. Moritz, M. Quigley, D. Cordes, V. Haughton, and E. Meyerand, “Functional connectivity in the thalamus and hippocampus studied with functional MR imaging,” American Journal of Neuroradiology, vol. 21, no. 8, pp. 1397–1401, 2000.
- M. F. Mason, M. I. Norton, J. D. Van Horn, D. M. Wegner, S. T. Grafton, and C. N. Macrae, “Wandering minds: the default network and stimulus-independent thought,” Science, vol. 315, no. 5810, pp. 393–395, 2007. View at Publisher · View at Google Scholar · View at PubMed
- M. E. Raichle, “Neuroscience: the brain's dark energy,” Science, vol. 314, no. 5803, pp. 1249–1250, 2006.
- M. E. Raichle, A. M. MacLeod, A. Z. Snyder, W. J. Powers, D. A. Gusnard, and G. L. Shulman, “A default mode of brain function,” Proceedings of the National Academy of Sciences of the United States of America, vol. 98, no. 2, pp. 676–682, 2001. View at Publisher · View at Google Scholar · View at PubMed
- M. Corbetta and G. L. Shulman, “Control of goal-directed and stimulus-driven attention in the brain,” Nature Reviews Neuroscience, vol. 3, no. 3, pp. 201–215, 2002. View at Publisher · View at Google Scholar · View at PubMed
- L. G. Ungerleider and J. V. Haxby, “‘What’ and ‘where’ in the human brain,” Current Opinion in Neurobiology, vol. 4, no. 2, pp. 157–165, 1994. View at Publisher · View at Google Scholar
- A. M. Achim and M. Lepage, “Neural correlates of memory for items and for associations: an event-related functional magnetic resonance imaging study,” Journal of Cognitive Neuroscience, vol. 17, no. 4, pp. 652–667, 2005. View at Publisher · View at Google Scholar · View at PubMed
- E. K. Miller and J. D. Cohen, “An integrative theory of prefrontal cortex function,” Annual Review of Neuroscience, vol. 24, pp. 167–202, 2001. View at Publisher · View at Google Scholar · View at PubMed
- L. G. Ungerleider, S. M. Courtney, and J. V. Haxby, “A neural system for human visual working memory,” Proceedings of the National Academy of Sciences of the United States of America, vol. 95, no. 3, pp. 883–890, 1998. View at Publisher · View at Google Scholar
- J. Doyon and H. Benali, “Reorganization and plasticity in the adult brain during learning of motor skills,” Current Opinion in Neurobiology, vol. 15, no. 2, pp. 161–167, 2005. View at Publisher · View at Google Scholar · View at PubMed
- T. Taniwaki, A. Okayama, T. Yoshiura, et al., “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, no. 2, pp. 745–753, 2006. View at Publisher · View at Google Scholar · View at PubMed
- E. Awh, E. K. Vogel, and S.-H. Oh, “Interactions between attention and working memory,” Neuroscience, vol. 139, no. 1, pp. 201–208, 2006. View at Publisher · View at Google Scholar · View at PubMed
- O. Gruber and T. Goschke, “Executive control emerging from dynamic interactions between brain systems mediating language,
working memory and attentional processes,” Acta Psychologica, vol. 115, no. 2-3, pp. 105–121, 2004. View at Publisher · View at Google Scholar · View at PubMed
- H. R. Naghavi and L. Nyberg, “Common fronto-parietal activity in attention, memory, and consciousness: shared demands on integration?,” Consciousness and Cognition, vol. 14, no. 2, pp. 390–425, 2005. View at Publisher · View at Google Scholar · View at PubMed
- A. B. Waites, A. Stanislavsky, D. F. Abbott, and G. D. Jackson, “Effect of prior cognitive state on resting state networks measured with functional connectivity,” Human Brain Mapping, vol. 24, no. 1, pp. 59–68, 2005. View at Publisher · View at Google Scholar · View at PubMed
- A. Mechelli, W. D. Penny, C. J. Price, D. R. Gitelman, and K. J. Friston, “Effective connectivity and intersubject variability:
using a multisubject network to test differences and commonalities,” NeuroImage, vol. 17, no. 3, pp. 1459–1469, 2002. View at Publisher · View at Google Scholar
- M. Kaiser and C. C. Hilgetag, “Modelling the development of cortical systems networks,” Neurocomputing, vol. 58–60, pp. 297–302, 2004. View at Publisher · View at Google Scholar
- T. Wu, Y. Zang, L. Wang, et al., “Aging influence on functional connectivity of the motor network in the resting state,” Neuroscience Letters, vol. 422, no. 3, pp. 164–168, 2007. View at Publisher · View at Google Scholar · View at PubMed
- A. K. Majewska and M. Sur, “Plasticity and specificity of cortical processing networks,” Trends in Neurosciences, vol. 29, no. 6, pp. 323–329, 2006. View at Publisher · View at Google Scholar · View at PubMed
- R. A. Poldrack, “Imaging brain plasticity: conceptual and methodological issues—a theoretical review,” NeuroImage, vol. 12, no. 1, pp. 1–13, 2000. View at Publisher · View at Google Scholar · View at PubMed
- C. Calautti and J.-C. Baron, “Functional neuroimaging studies of motor recovery after stroke in adults: a review,” Stroke, vol. 34, no. 6, pp. 1553–1566, 2003. View at Publisher · View at Google Scholar · View at PubMed
- N. S. Ward, “Plasticity and the functional reorganization of the human brain,” International Journal of Psychophysiology, vol. 58, no. 2-3, pp. 158–161, 2005. View at Publisher · View at Google Scholar · View at PubMed
- H. Duffau, “Lessons from brain mapping in surgery for low-grade glioma:
insights into associations between tumour and brain plasticity,” The Lancet Neurology, vol. 4, no. 8, pp. 476–486, 2005. View at Publisher · View at Google Scholar · View at PubMed
- A. Krainik, S. Lehéricy, H. Duffau, et al., “Postoperative speech disorder after medial frontal surgery: role of the supplementary motor area,” Neurology, vol. 60, no. 4, pp. 587–594, 2003.
- A. Krainik, S. Lehéricy, H. Duffau, et al., “Role of the supplementary motor area in motor deficit following medial frontal lobe surgery,” Neurology, vol. 57, no. 5, pp. 871–878, 2001.
- A. Thiel, K. Herholz, A. Koyuncu, et al., “Plasticity of language networks in patients with brain tumors: a positron emission tomography activation study,” Annals of Neurology, vol. 50, no. 5, pp. 620–629, 2001. View at Publisher · View at Google Scholar
- B. J. He, A. Z. Snyder, J. L. Vincent, A. Epstein, G. L. Shulman, and M. Corbetta, “Breakdown of functional connectivity in frontoparietal networks underlies behavioral deficits in spatial neglect,” Neuron, vol. 53, no. 6, pp. 905–918, 2007. View at Publisher · View at Google Scholar · View at PubMed
- J. Gotman, C. Grova, A. Bagshaw, E. Kobayashi, Y. Aghakhani, and F. Dubeau, “Generalized epileptic discharges show thalamocortical activation and suspension of the default state of the brain,” Proceedings of the National Academy of Sciences of the United States of America, vol. 102, no. 42, pp. 15236–15240, 2005. View at Publisher · View at Google Scholar · View at PubMed
- R. L. Buckner, A. Z. Snyder, B. J. Shannon, et al., “Molecular, structural, and functional characterization of Alzheimer's disease:
evidence for a relationship between default activity, amyloid, and memory,” Journal of Neuroscience, vol. 25, no. 34, pp. 7709–7717, 2005. View at Publisher · View at Google Scholar · View at PubMed
- E. Başar, C. Başar-Eroğlu, S. Karakaş, and M. Schürmann, “Are cognitive processes manifested in event-related gamma, alpha, theta and delta oscillations in the EEG?,” Neuroscience Letters, vol. 259, no. 3, pp. 165–168, 1999. View at Publisher · View at Google Scholar
- E. Başar, M. Schürmann, and O. Sakowitz, “The selectively distributed theta system: functions,” International Journal of Psychophysiology, vol. 39, no. 2-3, pp. 197–212, 2000. View at Publisher · View at Google Scholar
- S. Karakaş, C. Başar-Eroğlu, Ç. Özesmi, H. Kafadar, and Ö. Ü. Erzengin, “Gamma response of the brain: a multifunctional oscillation that represents bottom-up with top-down processing,” International Journal of Psychophysiology, vol. 39, no. 2-3, pp. 137–150, 2000. View at Publisher · View at Google Scholar
- M. Schürmann and E. Başar, “Functional aspects of alpha oscillations in the EEG,” International Journal of Psychophysiology, vol. 39, no. 2-3, pp. 151–158, 2000. View at Publisher · View at Google Scholar
- D. A. Leopold, Y. Murayama, and N. K. Logothetis, “Very slow activity fluctuations in monkey visual cortex: implications for functional brain imaging,” Cerebral Cortex, vol. 13, no. 4, pp. 422–433, 2003. View at Publisher · View at Google Scholar
- N. K. Logothetis, “The underpinnings of the BOLD functional magnetic resonance imaging signal,” Journal of Neuroscience, vol. 23, no. 10, pp. 3963–3971, 2003.
- N. K. Logothetis, J. Pauls, M. Augath, T. Trinath, and A. Oeltermann, “Neurophysiological investigation of the basis of the fMRI signal,” Nature, vol. 412, no. 6843, pp. 150–157, 2001. View at Publisher · View at Google Scholar · View at PubMed
- N. K. Logothetis and J. Pfeuffer, “On the nature of the BOLD fMRI contrast mechanism,” Magnetic Resonance Imaging, vol. 22, no. 10, pp. 1517–1531, 2004. View at Publisher · View at Google Scholar · View at PubMed
- G. Winterer, F. W. Carver, F. Musso, V. Mattay, D. R. Weinberger, and R. Coppola, “Complex relationship between BOLD signal and synchronization/desynchronization of human brain MEG oscillations,” Human Brain Mapping, vol. 28, no. 9, pp. 805–816, 2007. View at Publisher · View at Google Scholar · View at PubMed
- K. J. Friston, S. Williams, R. Howard, R. S. J. Frackowiak, and R. Turner, “Movement-related effects in fMRI time-series,” Magnetic Resonance in Medicine, vol. 35, no. 3, pp. 346–355, 1996.
- A. Gretton, A. Belitski, Y. Murayama, B. Schölkopf, and N. Logothetis, “The effect of artifacts on dependence measurement in fMRI,” Magnetic Resonance Imaging, vol. 24, no. 4, pp. 401–409, 2006. View at Publisher · View at Google Scholar · View at PubMed
- G. Krüger and G. H. Glover, “Physiological noise in oxygenation-sensitive magnetic resonance imaging,” Magnetic Resonance in Medicine, vol. 46, no. 4, pp. 631–637, 2001. View at Publisher · View at Google Scholar · View at PubMed
- M. S. Dagli, J. E. Ingeholm, and J. V. Haxby, “Localization of cardiac-induced signal change in fMRI,” NeuroImage, vol. 9, no. 4, pp. 407–415, 1999. View at Publisher · View at Google Scholar · View at PubMed
- D. Raj, A. W. Anderson, and J. C. Gore, “Respiratory effects in human functional magnetic resonance imaging due to bulk susceptibility changes,” Physics in Medicine and Biology, vol. 46, no. 12, pp. 3331–3340, 2001. View at Publisher · View at Google Scholar
- V. Perlbarg, P. Bellec, J.-L. Anton, M. Pélégrini-Issac, J. Doyon, and H. Benali, “CORSICA: correction of structured noise in fMRI by automatic identification of ICA components,” Magnetic Resonance Imaging, vol. 25, no. 1, pp. 35–46, 2007. View at Publisher · View at Google Scholar · View at PubMed
- C. G. Thomas, R. A. Harshman, and R. S. Menon, “Noise reduction in BOLD-based fMRI using component analysis,” NeuroImage, vol. 17, no. 3, pp. 1521–1537, 2002. View at Publisher · View at Google Scholar
- T. E. Lund and S.-J. Li, “fcMRI—mapping functional connectivity or correlating cardiac-induced noise?,” Magnetic Resonance in Medicine, vol. 46, no. 3, pp. 628–628, 2001. View at Publisher · View at Google Scholar · View at PubMed
- R. M. Birn, J. B. Diamond, M. A. Smith, and P. A. Bandettini, “Separating respiratory-variation-related fluctuations from neuronal-activity-related fluctuations in fMRI,” NeuroImage, vol. 31, no. 4, pp. 1536–1548, 2006. View at Publisher · View at Google Scholar · View at PubMed
- R. G. Wise, K. Ide, M. J. Poulin, and I. Tracey, “Resting fluctuations in arterial carbon dioxide induce significant low frequency variations in BOLD signal,” NeuroImage, vol. 21, no. 4, pp. 1652–1664, 2004. View at Publisher · View at Google Scholar · View at PubMed
- T. W. Anderson, An Introduction to Multivariate Statistical Analysis, Wiley Publications in Statistics, John Wiley & Sons, New York, NY, USA, 1958.
- G. Marrelec, P. Bellec, H. Duffau, et al., “Regions, systems, and the brain: hierarchical measures of functional integration in fMRI,” to appear in Medical Image Analysis. View at Publisher · View at Google Scholar · View at PubMed
- G. Marrelec, P. Bellec, and H. Benali, “Exploring large-scale brain networks in functional MRI,” Journal of Physiology Paris, vol. 100, no. 4, pp. 171–181, 2006. View at Publisher · View at Google Scholar · View at PubMed
- G. Marrelec, B. Horwitz, J. Kim, M. Pélégrini-Issac, H. Benali, and J. Doyon, “Using partial correlation to enhance structural equation modeling of functional MRI data,” Magnetic Resonance Imaging, vol. 25, no. 8, pp. 1181–1189, 2007. View at Publisher · View at Google Scholar · View at PubMed
- G. Marrelec, A. Krainik, H. Duffau, et al., “Partial correlation for functional brain interactivity investigation in functional MRI,” NeuroImage, vol. 32, no. 1, pp. 228–237, 2006. View at Publisher · View at Google Scholar · View at PubMed
- G. Marrelec, J. Kim, J. Doyon, and B. Horwitz, “Large scale model validation of partial correlation analysis for effective connectivity Investigation in functional MRI,” to appear in Human Brain Mapping.
- B. Abler, A. Roebroeck, R. Goebel, et al., “Investigating directed influences between activated brain areas in a motor-response task using fMRI,” Magnetic Resonance Imaging, vol. 24, no. 2, pp. 181–185, 2006. View at Publisher · View at Google Scholar · View at PubMed
- R. Goebel, A. Roebroeck, D.-S. Kim, and E. Formisano, “Investigating directed cortical interactions in time-resolved fMRI data using
vector autoregressive modeling and Granger causality mapping,” Magnetic Resonance Imaging, vol. 21, no. 10, pp. 1251–1261, 2003. View at Publisher · View at Google Scholar
- A. Roebroeck, E. Formisano, and R. Goebel, “Mapping directed influence over the brain using Granger causality and fMRI,” NeuroImage, vol. 25, no. 1, pp. 230–242, 2005. View at Publisher · View at Google Scholar · View at PubMed
- O. David and K. J. Friston, “A neural mass model for MEG/EEG: coupling and neuronal dynamics,” NeuroImage, vol. 20, no. 3, pp. 1743–1755, 2003. View at Publisher · View at Google Scholar
- R. Kötter and F. T. Sommer, “Global relationship between anatomical connectivity and activity propagation in the cerebral cortex,” Philosophical Transactions of the Royal Society of London Series B, vol. 355, no. 1393, pp. 127–134, 2000.
- 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, no. 4, pp. 310–320, 1998. View at Publisher · View at Google Scholar
- G. Tononi, O. Sporns, and G. M. Edelman, “Reentry and the problem of integrating multiple cortical areas:
simulation of dynamic integration in the visual system,” Cerebral Cortex, vol. 2, no. 4, pp. 310–335, 1992. View at Publisher · View at Google Scholar
- C. Büchel and K. Friston, “Assessing interactions among neuronal systems using functional neuroimaging,” Neural Networks, vol. 13, no. 8-9, pp. 871–882, 2000. View at Publisher · View at Google Scholar
- A. R. McIntosh, “Towards a network theory of cognition,” Neural Networks, vol. 13, no. 8-9, pp. 861–870, 2000. View at Publisher · View at Google Scholar
- 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, no. 1-2, pp. 2–22, 1994. View at Publisher · View at Google Scholar
- A. R. McIntosh, C. L. Grady, L. G. Ungerleider, J. V. Haxby, S. I. Rapoport, and B. Horwitz, “Network analysis of cortical visual pathways mapped with PET,” Journal of Neuroscience, vol. 14, no. 2, pp. 655–666, 1994.
- K. J. Friston, L. Harrison, and W. Penny, “Dynamic causal modelling,” NeuroImage, vol. 19, no. 4, pp. 1273–1302, 2003. View at Publisher · View at Google Scholar
- W. D. Penny, K. E. Stephan, A. Mechelli, and K. J. Friston, “Comparing dynamic causal models,” NeuroImage, vol. 22, no. 3, pp. 1157–1172, 2004. View at Publisher · View at Google Scholar · View at PubMed
- W. D. Penny, K. E. Stephan, A. Mechelli, and K. J. Friston, “Modelling functional integration: a comparison of structural equation and dynamic causal models,” NeuroImage, vol. 23, pp. S264–S274, 2004. View at Publisher · View at Google Scholar · View at PubMed
- O. David, D. Cosmelli, and K. J. Friston, “Evaluation of different measures of functional connectivity using a neural mass model,” NeuroImage, vol. 21, no. 2, pp. 659–673, 2004. View at Publisher · View at Google Scholar · View at PubMed
- B. Horwitz, “Relating fMRI and PET signals to neural activity by means of large-scale neural models,” Neuroinformatics, vol. 2, no. 2, pp. 251–266, 2004. View at Publisher · View at Google Scholar · View at PubMed
- B. Horwitz and A. R. Braun, “Brain network interactions in auditory, visual and linguistic processing,” Brain and Language, vol. 89, no. 2, pp. 377–384, 2004. View at Publisher · View at Google Scholar · View at PubMed
- F. T. Husain, M.-A. Tagamets, S. J. Fromm, A. R. Braun, and B. Horwitz, “Relating neuronal dynamics for auditory object processing to neuroimaging activity:
a computational modeling and an fMRI study,” NeuroImage, vol. 21, no. 4, pp. 1701–1720, 2004. View at Publisher · View at Google Scholar · View at PubMed
- C. J. 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 of the United States of America, vol. 104, no. 24, pp. 10240–10245, 2007. View at Publisher · View at Google Scholar · View at PubMed
- N. Gupte, B. K. Singh, and T. M. Janaki, “Networks: structure, function and optimisation,” Physica A, vol. 346, no. 1-2, pp. 75–81, 2005. View at Publisher · View at Google Scholar
- M. E. J. Newman, “The structure and function of complex networks,” SIAM Review, vol. 45, no. 2, pp. 167–256, 2003. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
- S. H. Strogatz, “Exploring complex networks,” Nature, vol. 410, no. 6825, pp. 268–276, 2001. View at Publisher · View at Google Scholar · View at PubMed
- R. Albert and A.-L. Barabási, “Statistical mechanics of complex networks,” Reviews of Modern Physics, vol. 74, no. 1, pp. 47–97, 2002. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
- A.-L. Barabási and R. Albert, “Emergence of scaring in random networks,” Science, vol. 286, no. 5439, pp. 509–512, 1999. View at Publisher · View at Google Scholar · View at MathSciNet
- S. Achard and E. Bullmore, “Efficiency and cost of economical brain functional networks,” PLoS Computational Biology, vol. 3, no. 2, p. e17, 2007. View at Publisher · View at Google Scholar · View at PubMed
- D. S. Bassett and E. Bullmore, “Small-world brain networks,” The Neuroscientist, vol. 12, no. 6, pp. 512–523, 2006. View at Publisher · View at Google Scholar · View at PubMed
- D. S. Bassett, A. Meyer-Lindenberg, S. Achard, T. Duke, and E. Bullmore, “Adaptive reconfiguration of fractal small-world human brain functional networks,” Proceedings of the National Academy of Sciences of the United States of America, vol. 103, no. 51, pp. 19518–19523, 2006. View at Publisher · View at Google Scholar · View at PubMed
- O. Sporns and J. D. Zwi, “The small world of the cerebral cortex,” Neuroinformatics, vol. 2, no. 2, pp. 145–162, 2004. View at Publisher · View at Google Scholar · View at PubMed
- D. J. Watts and S. H. Strogatz, “Collective dynamics of ‘small-world’ networks,” Nature, vol. 393, no. 6684, pp. 440–442, 1998. View at Publisher · View at Google Scholar · View at PubMed
- D. R. Chialvo, “Critical brain networks,” Physica A, vol. 340, no. 4, pp. 756–765, 2004. View at Publisher · View at Google Scholar
- V. M. Eguíluz, D. R. Chialvo, G. A. Cecchi, M. Baliki, and A. V. Apkarian, “Scale-free brain functional networks,” Physical Review Letters, vol. 94, no. 1, Article ID 018102, 4 pages, 2005. View at Publisher · View at Google Scholar
- M. Kaiser, R. Martin, P. Andras, and M. P. Young, “Simulation of robustness against lesions of cortical networks,” European Journal of Neuroscience, vol. 25, no. 10, pp. 3185–3192, 2007. View at Publisher · View at Google Scholar · View at PubMed
- S. Micheloyannis, E. Pachou, C. J. Stam, et al., “Small-world networks and disturbed functional connectivity in schizophrenia,” Schizophrenia Research, vol. 87, no. 1–3, pp. 60–66, 2006. View at Publisher · View at Google Scholar · View at PubMed
- C.-W. Shin and S. Kim, “Self-organized criticality and scale-free properties in emergent functional neural networks,” Physical Review E, vol. 74, no. 4, Article ID 045101, 4 pages, 2006. View at Publisher · View at Google Scholar
- C. F. Beckmann and S. M. Smith, “Probabilistic independent component analysis for functional magnetic resonance imaging,” IEEE Transactions on Medical Imaging, vol. 23, no. 2, pp. 137–152, 2004. View at Publisher · View at Google Scholar · View at PubMed
- J. Himberg, A. Hyvärinen, and F. Esposito, “Validating the independent components of neuroimaging time series via clustering and visualization,” NeuroImage, vol. 22, no. 3, pp. 1214–1222, 2004. View at Publisher · View at Google Scholar · View at PubMed
- O. Friman and C.-F. Westin, “Resampling fMRI time series,” NeuroImage, vol. 25, no. 3, pp. 859–867, 2005. View at Publisher · View at Google Scholar · View at PubMed
- “A bootstrap test to investigate changes in brain connectivity for functional MRI,” to appear in Statistica Sinica http://www3.stat.sinica.edu.tw/preprint/SS-07-138_1.pdf.
- V. D. Calhoun, T. Adali, and J. J. Pekar, “A method for comparing group fMRI data using independent component analysis:
application to visual, motor and visuomotor tasks,” Magnetic Resonance Imaging, vol. 22, no. 9, pp. 1181–1191, 2004. View at Publisher · View at Google Scholar · View at PubMed
- S. Dodel, N. Golestani, C. Pallier, V. ElKouby, D. Le Bihan, and J.-B. Poline, “Condition-dependent functional connectivity: syntax networks in bilinguals,” Philosophical Transactions of the Royal Society of London Series B, vol. 360, no. 1457, pp. 921–935, 2005. View at Publisher · View at Google Scholar · View at PubMed
- K. J. Fristen, C. D. Frith, P. Fletcher, P. F. Liddle, and R. S. J. Frackowiak, “Functional topography: multidimensional scaling and functional connectivity in the brain,” Cerebral Cortex, vol. 6, no. 2, pp. 156–164, 1996. View at Publisher · View at Google Scholar
- R. Toro and Y. Burnod, “Geometric atlas: modeling the cortex as an organized surface,” NeuroImage, vol. 20, no. 3, pp. 1468–1484, 2003. View at Publisher · View at Google Scholar
- A. Unwin, M. Theus, and H. Hofmann, Graphics of Large Datasets. Visualizing A Million, Springer, New York, NY, USA, 2006.
- H. Mizuhara, L.-Q. Wang, K. Kobayashi, and Y. Yamaguchi, “Long-range EEG phase synchronization during an arithmetic task indexes a coherent
cortical network simultaneously measured by fMRI,” NeuroImage, vol. 27, no. 3, pp. 553–563, 2005. View at Publisher · View at Google Scholar · View at PubMed
- L. A. Wheaton, G. Nolte, S. Bohlhalter, E. Fridman, and M. Hallett, “Synchronization of parietal and premotor areas during preparation and execution of praxis hand movements,” Clinical Neurophysiology, vol. 116, no. 6, pp. 1382–1390, 2005. View at Publisher · View at Google Scholar · View at PubMed
- P. J. Basser, J. Mattiello, and D. LeBihan, “Estimation of the effective self-diffusion tensor from the NMR spin echo,” Journal of Magnetic Resonance, Series B, vol. 103, no. 3, pp. 247–254, 1994. View at Publisher · View at Google Scholar
- T. E. J. Behrens and H. Johansen-Berg, “Relating connectional architecture to grey matter function using diffusion imaging,” Philosophical Transactions of the Royal Society of London Series B, vol. 360, no. 1457, pp. 903–911, 2005. View at Publisher · View at Google Scholar · View at PubMed
- T. E. J. Behrens, H. Johansen-Berg, M. W. Woolrich, et al., “Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging,” Nature Neuroscience, vol. 6, no. 7, pp. 750–757, 2003. View at Publisher · View at Google Scholar · View at PubMed
- H. Johansen-Berg, T. E. J. Behrens, M. D. Robson, et al., “Changes in connectivity profiles define functionally distinct regions in human medial frontal cortex,” Proceedings of the National Academy of Sciences of the United States of America, vol. 101, no. 36, pp. 13335–13340, 2004. View at Publisher · View at Google Scholar · View at PubMed