Mapping the human connectome

Neurosurgery

Volumn 71, Issue 1, 2012, Pages 1-5

  Toga, Arthur W ^a   Clark, Kristi A ^a   Thompson, Paul M ^a   Shattuck, David W ^a   Van Horn, John Darrell ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BEHAVIOR; BRAIN MAPPING; CAENORHABDITIS ELEGANS; COGNITION; DIFFUSION WEIGHTED IMAGING; GENOMICS; HUMAN; NERVE CELL NETWORK; NEUROBIOLOGY; NEUROIMAGING; NONHUMAN; PRIORITY JOURNAL; REVIEW; TRACTOGRAPHY;

BRAIN; BRAIN MAPPING; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; NERVE FIBERS, MYELINATED; NEURAL PATHWAYS; NEUROIMAGING;

EID: 84862835733     PISSN: 0148396X     EISSN: None     Source Type: Journal    
DOI: 10.1227/NEU.0b013e318258e9ff     Document Type: Review

References (53)

1. White JG, Southgate E, Thomson JN, Brenner S. Factors that determine connectivity in the nervous system of Caenorhabditis elegans. Cold Spring Harb Symp Quant Biol. 1983;48(pt 2):633-640.
2. Lichtman JW, Livet J, Sanes JR. A technicolour approach to the connectome. Nat Rev Neurosci. 2008;9(6):417-422.
3. Kasthuri N, Lichtman JW. The rise of the 'projectome'. Nat Methods. 2007;4(4): 307-308.
4. Lichtman JW, Sanes JR. Ome sweet ome: what can the genome tell us about the connectome? Curr Opin Neurobiol. 2008;18(3):346-353.
5. Jahanshad N, Ryles A, McMahon KL, et al. Discovery of genes that affect human brain connectivity: a genome-wide analysis of the connectome. Paper presented at: International Symposium on Biomedical Imaging; May 2-5, 2012; Barcelona, Spain.
6. Jahanshad N, Kohannim O, Toga AW, et al. Diffusion imaging protocol effects on genetic associations. Paper presented at: International Symposium on Biomedical Imaging; May 2-5, 2012; Barcelona, Spain.
7. Zhan L, Leow AD, Aganj I, et al. Differential information content in staggered multiple shell HARDI measured by the tensor distribution function. Paper presented at: International Symposium on Biomedical Imaging; March 30-April 2, 2011; Chicago, Illinois.
8. Le Bihan D. Looking into the functional architecture of the brain with diffusion MRI. Nat Rev Neurosci. 2003;4(6):469-480. (Pubitemid 37280168)
9. Beaulieu C. The basis of anisotropic water diffusion in the nervous system-a technical review. NMR Biomed. 2002;15(7-8):435-455. (Pubitemid 36054508)
10. Basser PJ, Mattiello J, LeBihan D. Estimation of the effective self-diffusion tensor from the NMR spin echo. J Magn Reson B. 1994;103(3):247-254.
11. Moseley M, Bammer R, Illes J. Diffusion-tensor imaging of cognitive performance. Brain Cogn. 2002;50(3):396-413. (Pubitemid 36042965)
12. Wedeen VJ, Hagmann P, Tseng WY, Reese TG, Weisskoff RM. Mapping complex tissue architecture with diffusion spectrum magnetic resonance imaging. Magn Reson Med. 2005;54(6):1377-1386. (Pubitemid 41740767)
13. Zhan W, Kang GA, Glass GA, et al. Regional alterations of brain microstructure in Parkinson's disease using diffusion tensor imaging. Mov Disord. 2012;27(1): 90-97.
14. Dennis EL, Jahanshad N, Toga AW, et al. Test-retest reliability of graph theory measures of structural brain connectivity. Paper presented at: 15th International Conference on Medical Image Computing and Computer Assisted Intervention; October 1-5, 2012; Nice, France.
15. Lenglet C, Campbell JS, Descoteaux M, et al. Mathematical methods for diffusion MRI processing. Neuroimage. 2009;45(1 suppl):S111-S122.
16. Hagmann P, Cammoun L, Gigandet X, et al. Mapping the structural core of human cerebral cortex. PLoS Biol. 2008;6(7):e159.
17. Xue R, van Zijl PC, Crain BJ, Solaiyappan M, Mori S. In vivo three-dimensional reconstruction of rat brain axonal projections by diffusion tensor imaging. Magn Reson Med. 1999;42(6):1123-1127.
18. Basser PJ, Pajevic S, Pierpaoli C, Duda J, Aldroubi A. In vivo fiber tractography using DT-MRI data. Magn Reson Med. 2000;44(4):625-632.
19. Mori S, Crain BJ, Chacko VP, van Zijl PC. Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging. Ann Neurol. 1999;45(2): 265-269. (Pubitemid 29072377)
20. Jones DK, Travis AR, Eden G, Pierpaoli C, Basser PJ. PASTA: pointwise assessment of streamline tractography attributes. Magn Reson Med. 2005;53(6): 1462-1467. (Pubitemid 40734670)
21. Aganj I, Lenglet C, Jahanshad N, et al. A Hough transform global probabilistic approach to multiple-subject diffusion MRI tractography. Med Image Anal. 2011; 15(4):414-425.
22. Wakana S, Jiang H, Nagae-Poetscher LM, van Zijl PC, Mori S. Fiber tract-based atlas of human white matter anatomy. Radiology. 2004;230(1):77-87. (Pubitemid 37549786)
23. Wakana S, Caprihan A, Panzenboeck MM, et al. Reproducibility of quantitative tractography methods applied to cerebral white matter. Neuroimage. 2007;36(3): 630-644. (Pubitemid 46907616)
24. Shattuck DW, Mirza M, Adisetiyo V, et al. Construction of a 3D probabilistic atlas of human cortical structures. Neuroimage. 2008;39(3):1064-1080.
25. Tzourio-Mazoyer N, Landeau B, Papathanassiou D, et al. Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage. 2002;15(1):273-289. (Pubitemid 34852226)
26. Eickhoff SB, Stephan KE, Mohlberg H, et al. A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data. Neuroimage. 2005;25(4):1325-1335. (Pubitemid 40591672)
27. Hua K, Zhang J, Wakana S, et al. Tract probability maps in stereotaxic spaces: analyses of white matter anatomy and tract-specific quantification. Neuroimage. 2008;39(1):336-347. (Pubitemid 350102194)
28. Gerig G, Gouttard S, Corouge I. Analysis of brain white matter via fiber tract modeling. Paper presented at: Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE2004; September 1-5, 2004.
29. Maddah M, Zollei L, Grimson WE, Westin CF, Wells WM. A mathematical framework for incorporating anatomical knowledge in DT-MRI analysis. Proc IEEE Int Symp Biomed Imaging. 2008;4543943:105-108.
30. Li H, Xue Z, Guo L, Liu T, Hunter J, Wong ST. A hybrid approach to automatic clustering of white matter fibers. Neuroimage. 2010;49(2):1249-1258.
31. Li Y, Liu Y, Li J, et al. Brain anatomical network and intelligence. PLoS Comput Biol. 2009;5(5):e1000395.
32. O'Donnell LJ, Westin CF. Automatic tractography segmentation using a high-dimensional white matter atlas. IEEE Trans Med Imaging. 2007;26(11):1562-1575. (Pubitemid 350025491)
33. Xia Y, Turken U, Whitfield-Gabrieli SL, Gabrieli JD. Knowledge-based classification of neuronal fibers in entire brain. 2005;8(pt 1):205-212.
34. Shi Y, Dinov I, Toga AW. Cortical shape analysis in the Laplace-Beltrami feature space. Med Image Comput Comput Assist Interv. 2009;12(pt 2):208-215.
35. Shi Y, Lai R, Kern K, Sicotte N, Dinov I, Toga AW. Harmonic surface mapping with Laplace-Beltrami eigenmaps. Med Image Comput Comput Assist Interv. 2008; 11(Pt 2):147-154.
36. Shi Y, Morra J, Thompson PM, Toga AW. Inverse-consistent surface mapping with Laplace-Beltrami eigen-features. Inf Process Med Imaging. 2009;21:467-478.
37. Jin Y, Shi Y, Jahanshad N, et al. 3D elastic registration improves HARDI-derived fiber alignment and automated tract clustering. Paper presented at: International Symposium on Biomedical Imaging; March 30-April 2, 2011; Chicago, Illinois.
38. Prasad G, Jahanshad N, Aganj I, Sapiro G, Toga AW, Thompson PM. Atlas-based fiber clustering for multi-subject analysis of high angular resolution diffusion imaging tractography. Paper presented at: International Symposium on Biomedical Imaging; March 30-April 2, 2011; Chicago, Illinois.
39. Bassett DS, GazzanigaMS. Understanding complexity in the human brain. Trends Cogn Sci. 2011;15(5):200-209.
40. Bullmore E, Sporns O. Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci. 2009;10(3):186-198.
41. Watts DJ, Strogatz SH. Collective dynamics of 'small-world' networks. Nature. 1998;393(6684):440-442. (Pubitemid 28292183)
42. Sporns O, Zwi JD. The small world of the cerebral cortex. Neuroinformatics. 2004; 2(2):145-162. (Pubitemid 41214095)
43. van den Heuvel MP, Stam CJ, Kahn RS, Hulshoff Pol HE. Efficiency of functional brain networks and intellectual performance. J Neurosci. 2009;29(23): 7619-7624.
44. Gong G, Rosa-Neto P, Carbonell F, Chen ZJ, He Y, Evans AC. Age- and gender-related differences in the cortical anatomical network. J Neurosci. 2009;29(50): 15684-15693.
45. Dennis EL, Jahanshad N, Toga AW, et al. Changes in anatomical brain connectivity between ages 12 and 30: a HARDI study of 484 adolescents and adults. Paper presented at: International Symposium on Biomedical Imaging; May 2-5, 2012; Barcelona, Spain.
46. Shu N, Liu Y, Li J, Li Y, Yu C, Jiang T. Altered anatomical network in early blindness revealed by diffusion tensor tractography. PLoS One. 2009;4(9):e7228.
47. Wang L, Zhu C, He Y, et al. Altered small-world brain functional networks in children with attention-deficit/hyperactivity disorder. Hum Brain Mapp. 2009;30 (2):638-649.
48. Daianu M, JahanshadN,Dennis EL, et al. Left versus right hemisphere differences in brain connectivity: 4-Tesla HARDI tractography in 567 twins. Paper presented at: International Symposium on Biomedical Imaging; May 2-5, 2012; Barcelona, Spain.
49. Chiang MC, McMahon KL, de Zubicaray GI, et al. Genetics of white matter development: a DTI study of 705 twins and their siblings aged 12 to 29. Neuroimage. 2011;54(3):2308-2317.
50. Prasad G, Kohannim O, Joshi S, et al. White matter tract analysis in 454 adults using maximum density paths. Paper presented at: MICCAI 2011 Workshop on Computational Diffusion MRI; September 18-22, 2011; Toronto, Canada.
51. Jin Y, Shi Y, Joshi S, et al. Heritability of white matter fiber tract shapes: a HARDI study of 198 twins. Paper presented at: MICCAI 2011 Workshop on Multi-Modal Brain Image Analysis (MBIA); September 18-22, 2011; Toronto, Canada.
52. Dennis EL, Jahanshad N, Rudie JD, et al. Abnormal structural brain connectivity in healthy carriers of the autism risk gene, CNTNAP2 [published online ahead of print]. Brain Connect. 2012.
53. Nir T, Jahanshad N, Jack CR, et al. Small world network measures predict white matter degeneration in patients with early-stage mild cognitive impairment. Paper presented at: International Symposium on Biomedical Imaging; May 2-5, 2012; Barcelona, Spain.