Skip to main content
PMC home page
Neuroscience Bulletin logoLink to Neuroscience Bulletin
. 2012 Jun 9;28(4):375–388. doi: 10.1007/s12264-012-1245-3

Diffusion magnetic resonance imaging for Brainnetome: A critical review

Nianming Zuo 1, Jian Cheng 1, Tianzi Jiang 1,2,3,✉
PMCID: PMC5560260  PMID: 22833036

Abstract

Increasing evidence shows that the human brain is a highly self-organized system that shows attributes of smallworldness, hierarchy and modularity. The “connectome” was conceived several years ago to identify the underpinning physical connectivities of brain networks. The need for an integration of multi-spatial and -temporal approaches is becoming apparent. Therefore, the “Brainnetome” (brain-net-ome) project was proposed. Diffusion magnetic resonance imaging (dMRI) is a non-invasive way to study the anatomy of brain networks. Here, we review the principles of dMRI, its methodologies, and some of its clinical applications for the Brainnetome. Future research in this field is discussed.

Keywords: brain mapping, neural networks, magnetic resonance imaging, imaging

References

  • [1].Jiang T., He Y., Zang Y., Weng X. Modulation of functional connectivity during the resting state and the motor task. Hum Brain Mapp. 2004;22:63–71. doi: 10.1002/hbm.20012. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [2].Fornito A, Zalesky A, Pantelis C, Bullmore ET. Schizophrenia, neuroimaging and connectomics. Neuroimage 2012. [Epub ahead of print] [DOI] [PubMed]
  • [3].Sporns O. The human connectome: a complex network. Ann N Y Acad Sci. 2011;1224:109–125. doi: 10.1111/j.1749-6632.2010.05888.x. [DOI] [PubMed] [Google Scholar]
  • [4].Hulvershorn L.A., Cullen K., Anand A. Toward dysfunctional connectivity: a review of neuroimaging findings in pediatric major depressive disorder. Brain Imaging Behav. 2011;5:307–328. doi: 10.1007/s11682-011-9134-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [5].Calhoun V.D., Sui J., Kiehl K., Turner J., Allen E., Pearlson G. Exploring the psychosis functional connectome: aberrant intrinsic networks in schizophrenia and bipolar disorder. Front Psychiatry. 2011;2:75. doi: 10.3389/fpsyt.2011.00075. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [6].Xie T., He Y. Mapping the Alzheimer’s brain with connectomics. Front Psychiatry. 2011;2:77. doi: 10.3389/fpsyt.2011.00077. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [7].Tymofiyeva O., Hess C.P., Ziv E., Tian N., Bonifacio S.L., McQuillen P.S., et al. Towards the “baby connectome”: mapping the structural connectivity of the newborn brain. PLoS One. 2012;7:e31029. doi: 10.1371/journal.pone.0031029. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [8].Wahl M., Barkovich A.J., Mukherjee P. Diffusion imaging and tractography of congenital brain malformations. Pediatr Radiol. 2010;40:59–67. doi: 10.1007/s00247-009-1448-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [9].Madden D.J., Bennett I.J., Song A.W. Cerebral white matter integrity and cognitive aging: contributions from diffusion tensor imaging. Neuropsychol Rev. 2009;19:415–435. doi: 10.1007/s11065-009-9113-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [10].Sporns O., Tononi G., Kotter R. The human connectome: A structural description of the human brain. PLoS Comput Biol. 2005;1:e42. doi: 10.1371/journal.pcbi.0010042. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [11].The Human Connectome Project. http://www.humanconnectome.org.
  • [12].Milham M.P. Open neuroscience solutions for the connectome-wide association era. Neuron. 2012;73:214–218. doi: 10.1016/j.neuron.2011.11.004. [DOI] [PubMed] [Google Scholar]
  • [13].Yao Z., Zhang Y., Lin L., Zhou Y., Xu C., Jiang T. Abnormal cortical networks in mild cognitive impairment and Alzheimer’s disease. PLoS Comput Biol. 2010;6:e1001006. doi: 10.1371/journal.pcbi.1001006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [14].Brainnetome. http://www.brainnetome.org/.
  • [15].Heng S., Song A.W., Sim K. White matter abnormalities in bipolar disorder: insights from diffusion tensor imaging studies. J Neural Transm. 2010;117:639–654. doi: 10.1007/s00702-010-0368-9. [DOI] [PubMed] [Google Scholar]
  • [16].Li T.Q., Wahlund L.O. The search for neuroimaging biomarkers of Alzheimer’s disease with advanced MRI techniques. Acta Radiol. 2011;52:211–222. doi: 10.1258/ar.2010.100053. [DOI] [PubMed] [Google Scholar]
  • [17].Peters B.D., Blaas J., de Haan L. Diffusion tensor imaging in the early phase of schizophrenia: what have we learned? J Psychiatr Res. 2010;44:993–1004. doi: 10.1016/j.jpsychires.2010.05.003. [DOI] [PubMed] [Google Scholar]
  • [18].Gross D.W. Diffusion tensor imaging in temporal lobe epilepsy. Epilepsia. 2011;52(Suppl4):32–34. doi: 10.1111/j.1528-1167.2011.03149.x. [DOI] [PubMed] [Google Scholar]
  • [19].Zalesky A., Fornito A., Harding I.H., Cocchi L., Yucel M., Pantelis C., et al. Whole-brain anatomical networks: does the choice of nodes matter? Neuroimage. 2010;50:970–983. doi: 10.1016/j.neuroimage.2009.12.027. [DOI] [PubMed] [Google Scholar]
  • [20].Descoteaux M. High Angular Resolution Diffusion MRI: from Local Estimation to Segmentation and Tractography. Graduate School of Information and Communication Sciences 2008, PhD.
  • [21].Mori S. Introduction to Diffusion Tensor Imaging. 1st ed. Amesterdam, The Netherlands: Elsevier; 2007. [Google Scholar]
  • [22].Stejskal E., Tanner J. Spin diffusion measurements: spin echoes in the presence of a time-dependent field gradient. J Chem Phys. 1965;42:288–292. [Google Scholar]
  • [23].Le Bihan D., Breton E., Lallemand D., Grenier P., Cabanis E., Laval-Jeantet M. MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders. Radiology. 1986;161:401–407. doi: 10.1148/radiology.161.2.3763909. [DOI] [PubMed] [Google Scholar]
  • [24].Basser P.J., Mattiello J., LeBihan D. MR diffusion tensor spectroscopy and imaging. Biophys J. 1994;66:259–267. doi: 10.1016/S0006-3495(94)80775-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [25].Moseley M., Cohen Y., Mintorovitch J., Kucharczyk J., Tsuruda J., Weinstein P., et al. Evidence of anisotropic self-diffusion. Radiology. 1990;176:439–445. doi: 10.1148/radiology.176.2.2367658. [DOI] [PubMed] [Google Scholar]
  • [26].Douek P., Turner R., Pekar J., Patronas N., Le Bihan D. MR color mapping of myelin fiber orientation. J Comput Assist Tomogr. 1991;15:923–929. doi: 10.1097/00004728-199111000-00003. [DOI] [PubMed] [Google Scholar]
  • [27].Tschumperle D., Deriche R. Proceedings of the Ninth International Conference on Computer Vision. Nice, France: IEEE Computer Society, IEEE Computer Society Press; 2003. Variational frameworks for DT-MRI estimation, regularization and visualization; pp. 116–121. [Google Scholar]
  • [28].Koay C.G., Chang L.C., Carew J.D., Pierpaoli C., Basser P.J. A unifying theoretical and algorithmic framework for least squares methods of estimation in diffusion tensor imaging. J Magn Reson. 2006;182:115–125. doi: 10.1016/j.jmr.2006.06.020. [DOI] [PubMed] [Google Scholar]
  • [29].Fillard P., Pennec X., Arsigny V., Ayache N. Clinical DT-MRI estimation, smoothing, and fiber tracking with log-Euclidean metrics. IEEE Trans Med Imaging. 2007;26:1472–1482. doi: 10.1109/TMI.2007.899173. [DOI] [PubMed] [Google Scholar]
  • [30].Jones D.K., Horsfield M.A., Simmons A. Optimal strategies for measuring diffusion in anisotropic systems by magnetic resonance imaging. Magn Reson Med. 1999;42:515–525. [PubMed] [Google Scholar]
  • [31].Alexander D.C., Barker G.J. Optimal imaging parameters for fiberorientation estimation in diffusion MRI. Neuroimage. 2005;27:357–367. doi: 10.1016/j.neuroimage.2005.04.008. [DOI] [PubMed] [Google Scholar]
  • [32].Pierpaoli C., Basser P.J. Toward a quantitative assessment of diffusion anisotropy. Magn Reson Med. 1996;36:893–906. doi: 10.1002/mrm.1910360612. [DOI] [PubMed] [Google Scholar]
  • [33].Johansen-Berg H., Behrens T.E.J. Diffusion MRI: From Quantitative Measurement to In vivo Neuroanatomy. Amsterdam: Academic Press; 2009. [Google Scholar]
  • [34].Boespflug EL, Storrs JM, Allendorfer JB, Lamy M, Eliassen JC, Page S. Mean diffusivity as a potential diffusion tensor biomarker of motor rehabilitation after electrical stimulation incorporating task specific exercise in stroke: a pilot study. Brain Imaging Behav 2011. [Epub ahead of print] [DOI] [PubMed]
  • [35].Callaghan P.T. Principles of Nuclear Magnetic Resonance Microscopy. Oxford: Oxford University Press; 1991. [Google Scholar]
  • [36].Tuch D, Weisskoff R, Belliveau J, Wedeen V. High angular resolution diffusion imaging of the human brain. The 7th Annual Meeting of ISMRM 1999.
  • [37].Tuch D.S., Reese T.G., Wiegell M.R., Makris N., Belliveau J.W., Wedeen V.J. High angular resolution diffusion imaging reveals intravoxel white matter fiber heterogeneity. Magn Reson Med. 2002;48:577–582. doi: 10.1002/mrm.10268. [DOI] [PubMed] [Google Scholar]
  • [38].Liu C., Bammer R., Acar B., Moseley M.E. Characterizing non-Gaussian diffusion by using generalized diffusion tensors. Magn Reson Med. 2004;51:924–937. doi: 10.1002/mrm.20071. [DOI] [PubMed] [Google Scholar]
  • [39].Assemlal H.E., Tschumperle D., Brun L. Efficient and robust computation of PDF features from diffusion MR signal. Med Image Anal. 2009;13:715–729. doi: 10.1016/j.media.2009.06.004. [DOI] [PubMed] [Google Scholar]
  • [40].Özarslan E, Koay C, Shepherd T, Blackband S, Basser PJ. Simple harmonic oscillator based reconstruction and estimation for three-dimensional q-space MRI. In: ISMRM 17th Annual Meeting and Exhibition, Honolulu, Hawai’i. April 18–24. 2009: 1396.
  • [41].Descoteaux M., Deriche R., Le Bihan D., Mangin J.F., Poupon C. Multiple q-shell diffusion propagator imaging. Med Image Anal. 2011;15:603–621. doi: 10.1016/j.media.2010.07.001. [DOI] [PubMed] [Google Scholar]
  • [42].Wedeen V.J., Hagmann P., Tseng W.Y., Reese T.G., Weisskoff R.M. Mapping complex tissue architecture with diffusion spectrum magnetic resonance imaging. Magn Reson Med. 2005;54:1377–1386. doi: 10.1002/mrm.20642. [DOI] [PubMed] [Google Scholar]
  • [43].Tuch D.S. Q-ball imaging. Magn Reson Med. 2004;52:1358–1372. doi: 10.1002/mrm.20279. [DOI] [PubMed] [Google Scholar]
  • [44].Descoteaux M., Angelino E., Fitzgibbons S., Deriche R. Regularized, fast, and robust analytical Q-ball imaging. Magn Reson Med. 2007;58:497–510. doi: 10.1002/mrm.21277. [DOI] [PubMed] [Google Scholar]
  • [45].Tournier J.D., Calamante F., Gadian D.G., Connelly A. Direct estimation of the fiber orientation density function from diffusion-weighted MRI data using spherical deconvolution. Neuroimage. 2004;23:1176–1185. doi: 10.1016/j.neuroimage.2004.07.037. [DOI] [PubMed] [Google Scholar]
  • [46].Tournier J.D., Calamante F., Connelly A. Robust determination of the fibre orientation distribution in diffusion MRI: non-negativity constrained super-resolved spherical deconvolution. Neuroimage. 2007;35:1459–1472. doi: 10.1016/j.neuroimage.2007.02.016. [DOI] [PubMed] [Google Scholar]
  • [47].Aganj I., Lenglet C., Sapiro G., Yacoub E., Ugurbil K., Harel N. Reconstruction of the orientation distribution function in single- and multiple-shell q-ball imaging within constant solid angle. Magn Reson Med. 2010;64:554–566. doi: 10.1002/mrm.22365. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [48].Ozarslan E., Shepherd T.M., Vemuri B.C., Blackband S.J., Mareci T.H. Resolution of complex tissue microarchitecture using the diffusion orientation transform (DOT) Neuroimage. 2006;31:1086–1103. doi: 10.1016/j.neuroimage.2006.01.024. [DOI] [PubMed] [Google Scholar]
  • [49].Prckovska V., Roebroeck A.F., Pullens W.L., Vilanova A., ter Haar Romeny B.M. Optimal acquisition schemes in high angular resolution diffusion weighted imaging. Med Image Comput Comput Assist Interv. 2008;11:9–17. doi: 10.1007/978-3-540-85990-1_2. [DOI] [PubMed] [Google Scholar]
  • [50].Cheng J., Ghosh A., Deriche R., Jiang T. Model-free, regularized, fast, and robust analytical orientation distribution function estimation. Med Image Comput Comput Assist Interv. 2010;13:648–656. doi: 10.1007/978-3-642-15705-9_79. [DOI] [PubMed] [Google Scholar]
  • [51].Cheng J., Ghosh A., Jiang T., Deriche R. Model-free and analytical EAP reconstruction via spherical polar Fourier diffusion MRI. Med Image Comput Comput Assist Interv. 2010;13:590–597. doi: 10.1007/978-3-642-15705-9_72. [DOI] [PubMed] [Google Scholar]
  • [52].Wedeen V.J., Rosene D.L., Wang R., Dai G., Mortazavi F., Hagmann P., et al. The geometric structure of the brain fiber pathways. Science. 2012;335:1628–1634. doi: 10.1126/science.1215280. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [53].Basser P.J., Pajevic S., Pierpaoli C., Duda J., Aldroubi A. In vivo fiber tractography using DT-MRI data. Magn Reson Med. 2000;44:625–632. doi: 10.1002/1522-2594(200010)44:4<625::aid-mrm17>3.0.co;2-o. [DOI] [PubMed] [Google Scholar]
  • [54].Mori S., Crain B.J., Chacko V.P., van Zijl P.C. Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging. Ann Neurol. 1999;45:265–269. doi: 10.1002/1531-8249(199902)45:2<265::aid-ana21>3.0.co;2-3. [DOI] [PubMed] [Google Scholar]
  • [55].Kreher B.W., Schneider J.F., Mader I., Martin E., Hennig J., Il’yasov K.A. Multitensor approach for analysis and tracking of complex fiber configurations. Magn Reson Med. 2005;54:1216–1225. doi: 10.1002/mrm.20670. [DOI] [PubMed] [Google Scholar]
  • [56].Chao Y.P., Chen J.H., Cho K.H., Yeh C.H., Chou K.H., Lin C.P. A multiple streamline approach to high angular resolution diffusion tractography. Med Eng Phys. 2008;30:989–996. doi: 10.1016/j.medengphy.2008.01.010. [DOI] [PubMed] [Google Scholar]
  • [57].Wedeen V.J., Wang R.P., Schmahmann J.D., Benner T., Tseng W.Y., Dai G., et al. Diffusion spectrum magnetic resonance imaging (DSI) tractography of crossing fibers. Neuroimage. 2008;41:1267–1277. doi: 10.1016/j.neuroimage.2008.03.036. [DOI] [PubMed] [Google Scholar]
  • [58].Jbabdi S., Woolrich M.W., Andersson J.L., Behrens T.E. A Bayesian framework for global tractography. Neuroimage. 2007;37:116–129. doi: 10.1016/j.neuroimage.2007.04.039. [DOI] [PubMed] [Google Scholar]
  • [59].Iturria-Medina Y., Canales-Rodriguez E.J., Melie-Garcia L., Valdes-Hernandez P.A., Martinez-Montes E., Aleman-Gomez Y., et al. Characterizing brain anatomical connections using diffusion weighted MRI and graph theory. Neuroimage. 2007;36:645–660. doi: 10.1016/j.neuroimage.2007.02.012. [DOI] [PubMed] [Google Scholar]
  • [60].Reisert M., Mader I., Anastasopoulos C., Weigel M., Schnell S., Kiselev V. Global fiber reconstruction becomes practical. Neuroimage. 2011;54:955–962. doi: 10.1016/j.neuroimage.2010.09.016. [DOI] [PubMed] [Google Scholar]
  • [61].Staempfli P., Jaermann T., Crelier G.R., Kollias S., Valavanis A., Boesiger P. Resolving fiber crossing using advanced fast marching tractography based on diffusion tensor imaging. Neuroimage. 2006;30:110–120. doi: 10.1016/j.neuroimage.2005.09.027. [DOI] [PubMed] [Google Scholar]
  • [62].Parker G.J., Wheeler-Kingshott C.A., Barker G.J. Estimating distributed anatomical connectivity using fast marching methods and diffusion tensor imaging. IEEE Trans Med Imaging. 2002;21:505–512. doi: 10.1109/TMI.2002.1009386. [DOI] [PubMed] [Google Scholar]
  • [63].Zalesky A., Fornito A. A DTI-derived measure of cortico-cortical connectivity. IEEE Trans Med Imaging. 2009;28:1023–1036. doi: 10.1109/TMI.2008.2012113. [DOI] [PubMed] [Google Scholar]
  • [64].Friman O., Farneback G., Westin C.F. A Bayesian approach for stochastic white matter tractography. IEEE Trans Med Imaging. 2006;25:965–978. doi: 10.1109/tmi.2006.877093. [DOI] [PubMed] [Google Scholar]
  • [65].Sherbondy A.J., Dougherty R.F., Ben-Shachar M., Napel S., Wandell B.A. ConTrack: finding the most likely pathways between brain regions using diffusion tractography. J Vis. 2008;8:1–16. doi: 10.1167/8.9.15. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [66].Behrens T.E., Woolrich M.W., Jenkinson M., Johansen-Berg H., Nunes R.G., Clare S., et al. Characterization and propagation of uncertainty in diffusion-weighted MR imaging. Magn Reson Med. 2003;50:1077–1088. doi: 10.1002/mrm.10609. [DOI] [PubMed] [Google Scholar]
  • [67].Behrens T.E., Berg H.J., Jbabdi S., Rushworth M.F., Woolrich M.W. Probabilistic diffusion tractography with multiple fibre orientations: What can we gain? Neuroimage. 2007;34:144–155. doi: 10.1016/j.neuroimage.2006.09.018. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [68].Tzourio-Mazoyer N., Landeau B., Papathanassiou D., Crivello F., Etard O., Delcroix N., et al. Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage. 2002;15:273–289. doi: 10.1006/nimg.2001.0978. [DOI] [PubMed] [Google Scholar]
  • [69].Kennedy D.N., Lange N., Makris N., Bates J., Meyer J., Caviness V.S., Jr. Gyri of the human neocortex: an MRI-based analysis of volume and variance. Cereb Cortex. 1998;8:372–384. doi: 10.1093/cercor/8.4.372. [DOI] [PubMed] [Google Scholar]
  • [70].Makris N., Meyer J.W., Bates J.F., Yeterian E.H., Kennedy D.N., Caviness V.S. MRI-Based topographic parcellation of human cerebral white matter and nuclei II. Rationale and applications with systematics of cerebral connectivity. Neuroimage. 1999;9:18–45. doi: 10.1006/nimg.1998.0384. [DOI] [PubMed] [Google Scholar]
  • [71].Dosenbach N.U., Nardos B., Cohen A.L., Fair D.A., Power J.D., Church J.A., et al. Prediction of individual brain maturity using fMRI. Science. 2010;329:1358–1361. doi: 10.1126/science.1194144. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [72].Dosenbach N.U., Visscher K.M., Palmer E.D., Miezin F.M., Wenger K.K., Kang H.C., et al. A core system for the implementation of task sets. Neuron. 2006;50:799–812. doi: 10.1016/j.neuron.2006.04.031. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [73].Zhu D., Li K., Faraco C.C., Deng F., Zhang D., Guo L., et al. Optimization of functional brain ROIs via maximization of consistency of structural connectivity profiles. Neuroimage. 2012;59:1382–1393. doi: 10.1016/j.neuroimage.2011.08.037. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [74].Li K., Guo L., Faraco C., Zhu D., Chen H., Yuan Y., et al. Visual analytics of brain networks. Neuroimage. 2012;61:82–97. doi: 10.1016/j.neuroimage.2012.02.075. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [75].Cullen K.R., Klimes-Dougan B., Muetzel R., Mueller B.A., Camchong J., Houri A., et al. Altered white matter microstructure in adolescents with major depression: a preliminary study. J Am Acad Child Adolesc Psychiatry. 2010;49:173–183.e1. doi: 10.1097/00004583-201002000-00011. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [76].Bae J.N., MacFall J.R., Krishnan K.R., Payne M.E., Steffens D.C., Taylor W.D. Dorsolateral prefrontal cortex and anterior cingulate cortex white matter alterations in late-life depression. Biol Psychiatry. 2006;60:1356–1363. doi: 10.1016/j.biopsych.2006.03.052. [DOI] [PubMed] [Google Scholar]
  • [77].Versace A., Almeida J.R., Hassel S., Walsh N.D., Novelli M., Klein C.R., et al. Elevated left and reduced right orbitomedial prefrontal fractional anisotropy in adults with bipolar disorder revealed by tractbased spatial statistics. Arch Gen Psychiatry. 2008;65:1041–1052. doi: 10.1001/archpsyc.65.9.1041. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [78].Vulliemoz S., Vollmar C., Koepp M.J., Yogarajah M., O’Muircheartaigh J., Carmichael D.W., et al. Connectivity of the supplementary motor area in juvenile myoclonic epilepsy and frontal lobe epilepsy. Epilepsia. 2011;52:507–514. doi: 10.1111/j.1528-1167.2010.02770.x. [DOI] [PubMed] [Google Scholar]
  • [79].Wu X., Xie M., Zhou J., Anderson A.W., Gore J.C., Ding Z. Globally optimized fiber tracking and hierarchical clustering — a unified framework. Magn Reson Imaging. 2012;304:485–495. doi: 10.1016/j.mri.2011.12.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [80].Barbieri S., Bauer M.H., Klein J., Moltz J., Nimsky C., Hahn H.K. DTI segmentation via the combined analysis of connectivity maps and tensor distances. Neuroimage. 2012;60:1025–1035. doi: 10.1016/j.neuroimage.2012.01.076. [DOI] [PubMed] [Google Scholar]
  • [81].Zhang T., Guo L., Li K., Zhu D., Cui G., Liu T. Predicting functional brain ROIs via fiber shape models. Med Image Comput Comput Assist Interv. 2011;14:42–49. doi: 10.1007/978-3-642-23629-7_6. [DOI] [PubMed] [Google Scholar]
  • [82].Ge B., Guo L., Lv J., Hu X., Han J., Zhang T., et al. Resting state fMRI-guided fiber clustering. Med Image Comput Comput Assist Interv. 2011;14:149–156. doi: 10.1007/978-3-642-23629-7_19. [DOI] [PubMed] [Google Scholar]
  • [83].Gong G., Rosa-Neto P., Carbonell F., Chen Z.J., He Y., Evans A.C. Age- and gender-related differences in the cortical anatomical network. J Neurosci. 2009;29:15684–15693. doi: 10.1523/JNEUROSCI.2308-09.2009. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [84].Yan C., Gong G., Wang J., Wang D., Liu D., Zhu C., et al. Sex- and brain size-related small-world structural cortical networks in young adults: a DTI tractography study. Cereb Cortex. 2011;21:449–458. doi: 10.1093/cercor/bhq111. [DOI] [PubMed] [Google Scholar]
  • [85].Li Y., Liu Y., Li J., Qin W., Li K., Yu C., et al. Brain anatomical network and intelligence. PLoS Comput Biol. 2009;5:e1000395. doi: 10.1371/journal.pcbi.1000395. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [86].Friston K.J., Frith C.D. Schizophrenia: a disconnection syndrome? Clin Neurosci. 1995;3:89–97. [PubMed] [Google Scholar]
  • [87].Wee C.Y., Yap P.T., Zhang D., Denny K., Browndyke J.N., Potter G.G., et al. Identification of MCI individuals using structural and functional connectivity networks. Neuroimage. 2012;59:2045–2056. doi: 10.1016/j.neuroimage.2011.10.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [88].Thomason M.E., Thompson P.M. Diffusion imaging, white matter, and psychopathology. Annu Rev Clin Psychol. 2011;7:63–85. doi: 10.1146/annurev-clinpsy-032210-104507. [DOI] [PubMed] [Google Scholar]
  • [89].Smits M., Visch-Brink E.G., van de Sandt-Koenderman M.E., van der Lugt A. Advanced magnetic resonance neuroimaging of language function recovery after aphasic stroke: a technical review. Arch Phys Med Rehabil. 2012;93:S4–14. doi: 10.1016/j.apmr.2011.02.023. [DOI] [PubMed] [Google Scholar]
  • [90].Jang S.H. A review of diffusion tensor imaging studies on motor recovery mechanisms in stroke patients. NeuroRehabilitation. 2011;28:345–352. doi: 10.3233/NRE-2011-0662. [DOI] [PubMed] [Google Scholar]
  • [91].Maller J.J., Thomson R.H., Lewis P.M., Rose S.E., Pannek K., Fitzgerald P.B. Traumatic brain injury, major depression, and diffusion tensor imaging: making connections. Brain Res Rev. 2010;64:213–240. doi: 10.1016/j.brainresrev.2010.04.003. [DOI] [PubMed] [Google Scholar]
  • [92].Sharp D.J., Ham T.E. Investigating white matter injury after mild traumatic brain injury. Curr Opin Neurol. 2011;24:558–563. doi: 10.1097/WCO.0b013e32834cd523. [DOI] [PubMed] [Google Scholar]
  • [93].Wang F., Sun Z., Cui L., Du X., Wang X., Zhang H., et al. Anterior cingulum abnormalities in male patients with schizophrenia determined through diffusion tensor imaging. Am J Psychiatry. 2004;161:573–575. doi: 10.1176/appi.ajp.161.3.573. [DOI] [PubMed] [Google Scholar]
  • [94].Mielke M.M., Kozauer N.A., Chan K.C., George M., Toroney J., Zerrate M., et al. Regionally-specific diffusion tensor imaging in mild cognitive impairment and Alzheimer’s disease. Neuroimage. 2009;46:47–55. doi: 10.1016/j.neuroimage.2009.01.054. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [95].Bae M.S., Jahng G.H., Ryu C.W., Kim E.J., Choi W.S., Yang D.M. Effect of intravenous gadolinium-DTPA on diffusion tensor MR imaging for the evaluation of brain tumors. Neuroradiology. 2009;51:793–802. doi: 10.1007/s00234-009-0571-2. [DOI] [PubMed] [Google Scholar]
  • [96].Awasthi R., Verma S.K., Haris M., Singh A., Behari S., Jaiswal A.K., et al. Comparative evaluation of dynamic contrast-enhanced perfusion with diffusion tensor imaging metrics in assessment of corticospinal tract infiltration in malignant glioma. J Comput Assist Tomogr. 2010;34:82–88. doi: 10.1097/RCT.0b013e3181ae29f0. [DOI] [PubMed] [Google Scholar]
  • [97].Trivedi R., Husain N., Rathore R.K., Saksena S., Srivastava S., Malik G.K., et al. Correlation of diffusion tensor imaging with histology in the developing human frontal cerebrum. Dev Neurosci. 2009;31:487–496. doi: 10.1159/000229500. [DOI] [PubMed] [Google Scholar]
  • [98].Pal D., Trivedi R., Saksena S., Yadav A., Kumar M., Pandey C.M., et al. Quantification of age- and gender-related changes in diffusion tensor imaging indices in deep grey matter of the normal human brain. J Clin Neurosci. 2011;18:193–196. doi: 10.1016/j.jocn.2010.05.033. [DOI] [PubMed] [Google Scholar]
  • [99].Raichle M.E., MacLeod A.M., Snyder A.Z., Powers W.J., Gusnard D.A., Shulman G.L. A default mode of brain function. Proc Natl Acad Sci U S A. 2001;98:676–682. doi: 10.1073/pnas.98.2.676. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [100].Teipel S.J., Bokde A.L., Meindl T., Amaro E., Jr, Soldner J., Reiser M.F., et al. White matter microstructure underlying default mode network connectivity in the human brain. Neuroimage. 2010;49:2021–2032. doi: 10.1016/j.neuroimage.2009.10.067. [DOI] [PubMed] [Google Scholar]
  • [101].Greicius M.D., Supekar K., Menon V., Dougherty R.F. Resting-state functional connectivity reflects structural connectivity in the default mode network. Cereb Cortex. 2009;19:72–78. doi: 10.1093/cercor/bhn059. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [102].Camchong J., MacDonald A.W., 3rd, Bell C., Mueller B.A., Lim K.O. Altered functional and anatomical connectivity in schizophrenia. Schizophr Bull. 2011;37:640–650. doi: 10.1093/schbul/sbp131. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [103].Soldner J, Meindl T, Koch W, Bokde AL, Reiser MF, Moller HJ, et al. Structural and functional neuronal connectivity in Alzheimer’s disease: A combined DTI and fMRI study. Nervenarzt 2011. [Epub ahead of print] (Article in German) [DOI] [PubMed]
  • [104].Bokde A.L., Ewers M., Hampel H. Assessing neuronal networks: understanding Alzheimer’s disease. Prog Neurobiol. 2009;89:125–133. doi: 10.1016/j.pneurobio.2009.06.004. [DOI] [PubMed] [Google Scholar]
  • [105].Bozzali M., Padovani A., Caltagirone C., Borroni B. Regional grey matter loss and brain disconnection across Alzheimer disease evolution. Curr Med Chem. 2011;18:2452–2458. doi: 10.2174/092986711795843263. [DOI] [PubMed] [Google Scholar]
  • [106].Liao W., Zhang Z., Pan Z., Mantini D., Ding J., Duan X., et al. Default mode network abnormalities in mesial temporal lobe epilepsy: a study combining fMRI and DTI. Hum Brain Mapp. 2011;32:883–895. doi: 10.1002/hbm.21076. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [107].Gutman D.A., Holtzheimer P.E., Behrens T.E., Johansen-Berg H., Mayberg H.S. A tractography analysis of two deep brain stimulation white matter targets for depression. Biol Psychiatry. 2009;65:276–282. doi: 10.1016/j.biopsych.2008.09.021. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [108].McDonald C.R., Ahmadi M.E., Hagler D.J., Tecoma E.S., Iragui V.J., Gharapetian L., et al. Diffusion tensor imaging correlates of memory and language impairments in temporal lobe epilepsy. Neurology. 2008;71:1869–1876. doi: 10.1212/01.wnl.0000327824.05348.3b. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [109].Brauer J., Anwander A., Friederici A.D. Neuroanatomical prerequisites for language functions in the maturing brain. Cereb Cortex. 2011;21:459–466. doi: 10.1093/cercor/bhq108. [DOI] [PubMed] [Google Scholar]
  • [110].Ostby Y., Tamnes C.K., Fjell A.M., Walhovd K.B. Morphometry and connectivity of the fronto-parietal verbal working memory network in development. Neuropsychologia. 2011;49:3854–3862. doi: 10.1016/j.neuropsychologia.2011.10.001. [DOI] [PubMed] [Google Scholar]
  • [111].Supekar K., Menon V. Developmental maturation of dynamic causal control signals in higher-order cognition: a neurocognitive network model. PLoS Comput Biol. 2012;8:e1002374. doi: 10.1371/journal.pcbi.1002374. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [112].Ystad M., Hodneland E., Adolfsdottir S., Haasz J., Lundervold A.J., Eichele T., et al. Cortico-striatal connectivity and cognition in normal aging: a combined DTI and resting state fMRI study. Neuroimage. 2011;55:24–31. doi: 10.1016/j.neuroimage.2010.11.016. [DOI] [PubMed] [Google Scholar]
  • [113].Sexton C.E., Mackay C.E., Ebmeier K.P. A systematic review of diffusion tensor imaging studies in affective disorders. Biol Psychiatry. 2009;66:814–823. doi: 10.1016/j.biopsych.2009.05.024. [DOI] [PubMed] [Google Scholar]
  • [114].Clark L., Chamberlain S.R., Sahakian B.J. Neurocognitive mechanisms in depression: implications for treatment. Annu Rev Neurosci. 2009;32:57–74. doi: 10.1146/annurev.neuro.31.060407.125618. [DOI] [PubMed] [Google Scholar]
  • [115].Drevets W.C., Price J.L., Furey M.L. Brain structural and functional abnormalities in mood disorders: implications for neurocircuitry models of depression. Brain Struct Funct. 2008;213:93–118. doi: 10.1007/s00429-008-0189-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [116].Lin J.J., Riley J.D., Juranek J., Cramer S.C. Vulnerability of the frontaltemporal connections in temporal lobe epilepsy. Epilepsy Res. 2008;82:162–170. doi: 10.1016/j.eplepsyres.2008.07.020. [DOI] [PubMed] [Google Scholar]
  • [117].Rimrodt S.L., Peterson D.J., Denckla M.B., Kaufmann W.E., Cutting L.E. White matter microstructural differences linked to left perisylvian language network in children with dyslexia. Cortex. 2010;46:739–749. doi: 10.1016/j.cortex.2009.07.008. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [118].Gharabaghi A., Kunath F., Erb M., Saur R., Heckl S., Tatagiba M., et al. Perisylvian white matter connectivity in the human right hemisphere. BMC neuroscience. 2009;10:15. doi: 10.1186/1471-2202-10-15. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [119].Cheon K.A., Kim Y.S., Oh S.H., Park S.Y., Yoon H.W., Herrington J., et al. Involvement of the anterior thalamic radiation in boys with high functioning autism spectrum disorders: a Diffusion Tensor Imaging study. Brain Res. 2011;1417:77–86. doi: 10.1016/j.brainres.2011.08.020. [DOI] [PubMed] [Google Scholar]
  • [120].Zarei M., Patenaude B., Damoiseaux J., Morgese C., Smith S., Matthews P.M., et al. Combining shape and connectivity analysis: an MRI study of thalamic degeneration in Alzheimer’s disease. Neuroimage. 2010;49:1–8. doi: 10.1016/j.neuroimage.2009.09.001. [DOI] [PubMed] [Google Scholar]
  • [121].Dudink J, Counsell SJ, Lequin MH, Govaert PP. DTI reveals network injury in perinatal stroke. Arch Dis Child Fetal Neonatal Ed 2011. [Epub ahead of print] [DOI] [PubMed]
  • [122].Forster A., Griebe M., Ottomeyer C., Rossmanith C., Gass A., Kern R., et al. Cerebral network disruption as a possible mechanism for impaired recovery after acute pontine stroke. Cerebrovasc Dis. 2011;31:499–505. doi: 10.1159/000324390. [DOI] [PubMed] [Google Scholar]
  • [123].Liu H., Fan G., Xu K., Wang F. Changes in cerebellar functional connectivity and anatomical connectivity in schizophrenia: a combined resting-state functional MRI and diffusion tensor imaging study. J Magn Reson Imaging. 2011;34:1430–1438. doi: 10.1002/jmri.22784. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [124].Wang Q., Su T.P., Zhou Y., Chou K.H., Chen I.Y., Jiang T., et al. Anatomical insights into disrupted small-world networks in schizophrenia. Neuroimage. 2012;59:1085–1093. doi: 10.1016/j.neuroimage.2011.09.035. [DOI] [PubMed] [Google Scholar]
  • [125].Cammoun L., Gigandet X., Sporns O., Thiran J.P., Deppen P., Krieger E., et al. Connectome alterations in schizophrenia. Neuroimage. 2009;47:S157. [Google Scholar]
  • [126].Lo C.Y., Wang P.N., Chou K.H., Wang J., He Y., Lin C.P. Diffusion tensor tractography reveals abnormal topological organization in structural cortical networks in Alzheimer’s disease. J Neurosci. 2010;30:16876–16885. doi: 10.1523/JNEUROSCI.4136-10.2010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [127].Li J, Liu Y, Qin W, Jiang J, Qiu Z, Xu J, et al. Age of onset of blindness affects brain anatomical networks constructed using diffusion tensor tractography. Cereb Cortex 2012. [Epub ahead of print] [DOI] [PubMed]
  • [128].Weinstein M., Ben-Sira L., Levy Y., Zachor D.A., Ben Itzhak E., Artzi M., et al. Abnormal white matter integrity in young children with autism. Hum Brain Mapp. 2011;32:534–543. doi: 10.1002/hbm.21042. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [129].Müller R.A. The study of autism as a distributed disorder. Ment Retard Dev Disabil Res Rev. 2007;13:85–95. doi: 10.1002/mrdd.20141. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [130].Bohanna I., Georgiou-Karistianis N., Hannan A.J., Egan G.F. Magnetic resonance imaging as an approach towards identifying neuropathological biomarkers for Huntington’s disease. Brain Res Rev. 2008;58:209–225. doi: 10.1016/j.brainresrev.2008.04.001. [DOI] [PubMed] [Google Scholar]
  • [131].Scholz J., Klein M.C., Behrens T.E., Johansen-Berg H. Training induces changes in white-matter architecture. Nat Neurosci. 2009;12:1370–1371. doi: 10.1038/nn.2412. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [132].Sagi Y., Tavor I., Hofstetter S., Tzur-Moryosef S., Blumenfeld-Katzir T., Assaf Y. Learning in the fast lane: new insights into neuroplasticity. Neuron. 2012;73:1195–1203. doi: 10.1016/j.neuron.2012.01.025. [DOI] [PubMed] [Google Scholar]
  • [133].Raj A., Kuceyeski A., Weiner M. A network diffusion model of disease progression in dementia. Neuron. 2012;73:1204–1215. doi: 10.1016/j.neuron.2011.12.040. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [134].Jones D.K., Cercignani M. Twenty-five pitfalls in the analysis of diffusion MRI data. NMR Biomed. 2010;23:803–820. doi: 10.1002/nbm.1543. [DOI] [PubMed] [Google Scholar]
  • [135].Jbabdi S., Johansen-Berg H. Tractography: where do we go from here? Brain Connect. 2011;1:169–183. doi: 10.1089/brain.2011.0033. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [136].Van Essen DC, Ugurbil K. The future of the human connectome. Neuroimage 2012. [Epub ahead of print] [DOI] [PMC free article] [PubMed]
  • [137].Cheng H., Wang Y., Sheng J., Sporns O., Kronenberger W.G., Mathews V.P., et al. Optimization of seed density in DTI tractography for structural networks. J Neurosci Methods. 2012;203:264–272. doi: 10.1016/j.jneumeth.2011.09.021. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [138].Li L, Rilling JK, Preuss TM, Glasser MF, Hu X. The effects of connection reconstruction method on the interregional connectivity of brain networks via diffusion tractography. Hum Brain Mapp 2011. [Epub ahead of print] [DOI] [PMC free article] [PubMed]
  • [139].Bassett D.S., Brown J.A., Deshpande V., Carlson J.M., Grafton S.T. Conserved and variable architecture of human white matter connectivity. Neuroimage. 2011;54:1262–1279. doi: 10.1016/j.neuroimage.2010.09.006. [DOI] [PubMed] [Google Scholar]
  • [140].Konarski J.Z., McIntyre R.S., Soczynska J.K., Kennedy S.H. Neuroimaging approaches in mood disorders: technique and clinical implications. Ann Clin Psychiatry. 2007;19:265–277. doi: 10.1080/10401230701653435. [DOI] [PubMed] [Google Scholar]
  • [141].Liu B., Song M., Li J., Liu Y., Li K., Yu C., et al. Prefrontal-related functional connectivities within the default network are modulated by COMT val158met in healthy young adults. J Neurosci. 2010;30:64–69. doi: 10.1523/JNEUROSCI.3941-09.2010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [142].Liu B., Li J., Yu C., Li Y., Liu Y., Song M., et al. Haplotypes of catechol-O-methyltransferase modulate intelligence-related brain white matter integrity. Neuroimage. 2010;50:243–249. doi: 10.1016/j.neuroimage.2009.12.020. [DOI] [PubMed] [Google Scholar]
  • [143].Brown J.A., Terashima K.H., Burggren A.C., Ercoli L.M., Miller K.J., Small G.W., et al. Brain network local interconnectivity loss in aging APOE-4 allele carriers. Proc Natl Acad Sci U S A. 2011;108:20760–20765. doi: 10.1073/pnas.1109038108. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [144].Teipel S.J., Pogarell O., Meindl T., Dietrich O., Sydykova D., Hunklinger U., et al. Regional networks underlying interhemispheric connectivity: an EEG and DTI study in healthy ageing and amnestic mild cognitive impairment. Hum Brain Mapp. 2009;30:2098–2119. doi: 10.1002/hbm.20652. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [145].Mohamed I.S., Otsubo H., Shroff M., Donner E., Drake J., Snead O.C., 3rd Magnetoencephalography and diffusion tensor imaging in gelastic seizures secondary to a cingulate gyrus lesion. Clin Neurol Neurosurg. 2007;109:182–187. [Google Scholar]
  • [146].Luat A.F., Chugani H.T. Molecular and diffusion tensor imaging of epileptic networks. Epilepsia. 2008;49(Suppl3):15–22. doi: 10.1111/j.1528-1167.2008.01506.x. [DOI] [PubMed] [Google Scholar]
  • [147].Rowland L.M., Spieker E.A., Francis A., Barker P.B., Carpenter W.T., Buchanan R.W. White matter alterations in deficit schizophrenia. Neuropsychopharmacology. 2009;34:1514–1522. doi: 10.1038/npp.2008.207. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [148].Park B., Kim J.I., Lee D., Jeong S.O., Lee J.D., Park H.J. Are brain networks stable during a 24-hour period? Neuroimage. 2012;59:456–466. doi: 10.1016/j.neuroimage.2011.07.049. [DOI] [PubMed] [Google Scholar]
  • [149].Liang X., Wang J., Yan C., Shu N., Xu K., Gong G., et al. Effects of different correlation metrics and preprocessing factors on smallworld brain functional networks: a resting-state functional MRI study. PLoS One. 2012;7:e32766. doi: 10.1371/journal.pone.0032766. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [150].Vaessen M.J., Hofman P.A., Tijssen H.N., Aldenkamp A.P., Jansen J.F., Backes W.H. The effect and reproducibility of different clinical DTI gradient sets on small world brain connectivity measures. Neuroimage. 2010;51:1106–1116. doi: 10.1016/j.neuroimage.2010.03.011. [DOI] [PubMed] [Google Scholar]
  • [151].You X., Adjouadi M., Guillen M.R., Ayala M., Barreto A., Rishe N., et al. Sub-patterns of language network reorganization in pediatric localization related epilepsy: a multisite study. Hum Brain Mapp. 2011;32:784–799. doi: 10.1002/hbm.21066. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [152].Teipel S.J., Reuter S., Stieltjes B., Acosta-Cabronero J., Ernemann U., Fellgiebel A., et al. Multicenter stability of diffusion tensor imaging measures: a European clinical and physical phantom study. Psychiatry Res. 2011;194:363–371. doi: 10.1016/j.pscychresns.2011.05.012. [DOI] [PubMed] [Google Scholar]
  • [153].Wang J.H., Zuo X.N., Gohel S., Milham M.P., Biswal B.B., He Y. Graph theoretical analysis of functional brain networks: test-retest evaluation on short- and long-term resting-state functional MRI data. PLoS One. 2011;6:e21976. doi: 10.1371/journal.pone.0021976. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [154].Hagmann P., Cammoun L., Gigandet X., Meuli R., Honey C.J., Wedeen V.J., et al. Mapping the structural core of human cerebral cortex. PLoS Biol. 2008;6:e159. doi: 10.1371/journal.pbio.0060159. [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from Neuroscience Bulletin are provided here courtesy of Springer

RESOURCES