The VALiDATe29 MRI Based Multi-Channel Atlas of the Squirrel Monkey Brain

  • Kurt G. Schilling
  • Yurui Gao
  • Iwona Stepniewska
  • Tung-Lin Wu
  • Feng Wang
  • Bennett A. Landman
  • John C. Gore
  • Li Min Chen
  • Adam W. Anderson
Original Article

Abstract

We describe the development of the first digital atlas of the normal squirrel monkey brain and present the resulting product, VALiDATe29. The VALiDATe29 atlas is based on multiple types of magnetic resonance imaging (MRI) contrast acquired on 29 squirrel monkeys, and is created using unbiased, nonlinear registration techniques, resulting in a population-averaged stereotaxic coordinate system. The atlas consists of multiple anatomical templates (proton density, T1, and T2* weighted), diffusion MRI templates (fractional anisotropy and mean diffusivity), and ex vivo templates (fractional anisotropy and a structural MRI). In addition, the templates are combined with histologically defined cortical labels, and diffusion tractography defined white matter labels. The combination of intensity templates and image segmentations make this atlas suitable for the fundamental atlas applications of spatial normalization and label propagation. Together, this atlas facilitates 3D anatomical localization and region of interest delineation, and enables comparisons of experimental data across different subjects or across different experimental conditions. This article describes the atlas creation and its contents, and demonstrates the use of the VALiDATe29 atlas in typical applications. The atlas is freely available to the scientific community.

Keywords

Brain Atlas Squirrel monkey Magnetic Resonance Imaging Template Diffusion MRI Segmentation 

References

  1. Abee, C. R. (1989). The squirrel monkey in biomedical research. ILAR Journal, 31(1), 11–20. doi:10.1093/ilar.31.1.11.CrossRefGoogle Scholar
  2. Akert, R. E. K. (1963). Stereotaxic atlas of the brain of the squirrel monkey. Madison, Wisconsin: University of Wisconsin Press.Google Scholar
  3. Andersson, J. L., Skare, S., & Ashburner, J. (2003). How to correct susceptibility distortions in spin-echo echo-planar images: Application to diffusion tensor imaging. NeuroImage, 20(2), 870–888. doi:10.1016/S1053-8119(03)00336-7.CrossRefPubMedGoogle Scholar
  4. Ashburner, J., & Friston, K. J. (2000). Voxel-based morphometry--the methods. NeuroImage, 11(6 Pt 1), 805–821. doi:10.1006/nimg.2000.0582.CrossRefPubMedGoogle Scholar
  5. Azadbakht, H., Parkes, L. M., Haroon, H. A., Augath, M., Logothetis, N. K., de Crespigny, A., et al. (2015). Validation of high-resolution Tractography against in vivo tracing in the macaque visual cortex. Cerebral Cortex, 25(11), 4299–4309. doi:10.1093/cercor/bhu326.CrossRefPubMedPubMedCentralGoogle Scholar
  6. Bastiani, M., Oros-Peusquens, A. M., Seehaus, A., Brenner, D., Mollenhoff, K., Celik, A., et al. (2016). Automatic segmentation of human cortical layer-complexes and architectural areas using ex vivo diffusion MRI and its validation. Frontiers in Neuroscience, 10, 487. doi:10.3389/fnins.2016.00487.CrossRefPubMedPubMedCentralGoogle Scholar
  7. Cabezas, M., Oliver, A., Llado, X., Freixenet, J., & Cuadra, M. B. (2011). A review of atlas-based segmentation for magnetic resonance brain images. Computer Methods and Programs in Biomedicine, 104(3), e158–e177. doi:10.1016/j.cmpb.2011.07.015.CrossRefPubMedGoogle Scholar
  8. Calabrese, E., Badea, A., Coe, C. L., Lubach, G. R., Shi, Y., Styner, M. A., et al. (2015). A diffusion tensor MRI atlas of the postmortem rhesus macaque brain. NeuroImage, 117, 408–416. doi:10.1016/j.neuroimage.2015.05.072.CrossRefPubMedPubMedCentralGoogle Scholar
  9. Carpenter, M. B. (1963). A stereotaxic atlas of the brain of the squirrel monkey. Archives of Neurology, 9(1), 104–104. doi:10.1001/archneur.1963.00460070114017.CrossRefGoogle Scholar
  10. Caruyer, E., Lenglet, C., Sapiro, G., & Deriche, R. (2013). Design of multishell sampling schemes with uniform coverage in diffusion MRI. Magnetic Resonance in Medicine, 69(6), 1534–1540. doi:10.1002/mrm.24736.CrossRefPubMedPubMedCentralGoogle Scholar
  11. Chen, L. M., Friedman, R. M., & Roe, A. W. (2003). Optical imaging of a tactile illusion in area 3b of the primary somatosensory cortex. Science, 302(5646), 881–885. doi:10.1126/science.1087846.CrossRefPubMedGoogle Scholar
  12. Choe, A. S., Gao, Y., Li, X., Compton, K. B., Stepniewska, I., & Anderson, A. W. (2011). Accuracy of image registration between MRI and light microscopy in the ex vivo brain. [research support, N.I.H., extramural]. Magnetic Resonance Imaging, 29(5), 683–692. doi:10.1016/j.mri.2011.02.022.CrossRefPubMedPubMedCentralGoogle Scholar
  13. Choe, A. S., Stepniewska, I., Colvin, D. C., Ding, Z., & Anderson, A. W. (2012). Validation of diffusion tensor MRI in the central nervous system using light microscopy: Quantitative comparison of fiber properties. NMR in Biomedicine, 25(7), 900–908. doi:10.1002/nbm.1810.CrossRefPubMedPubMedCentralGoogle Scholar
  14. Collins, D. L., Holmes, C. J., Peters, T. M., & Evans, A. C. (1995). Automatic 3-D model-based neuroanatomical segmentation. Human Brain Mapping, 3(3), 190–208. doi:10.1002/hbm.460030304.CrossRefGoogle Scholar
  15. D'Arceuil, H. E., Westmoreland, S., & de Crespigny, A. J. (2007). An approach to high resolution diffusion tensor imaging in fixed primate brain. NeuroImage, 35(2), 553–565. doi:10.1016/j.neuroimage.2006.12.028.CrossRefPubMedGoogle Scholar
  16. Dyrby, T. B., Sogaard, L. V., Parker, G. J., Alexander, D. C., Lind, N. M., Baare, W. F., et al. (2007). Validation of in vitro probabilistic tractography. NeuroImage, 37(4), 1267–1277. doi:10.1016/j.neuroimage.2007.06.022.CrossRefPubMedGoogle Scholar
  17. Dyrby, T. B., Baare, W. F., Alexander, D. C., Jelsing, J., Garde, E., & Sogaard, L. V. (2011). An ex vivo imaging pipeline for producing high-quality and high-resolution diffusion-weighted imaging datasets. [research support, non-U.S. Gov't. Validation studies]. Human Brain Mapping, 32(4), 544–563. doi:10.1002/hbm.21043.CrossRefPubMedGoogle Scholar
  18. Eickhoff, S. B., Stephan, K. E., Mohlberg, H., Grefkes, C., Fink, G. R., Amunts, K., et al. (2005). A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data. NeuroImage, 25(4), 1325–1335. doi:10.1016/j.neuroimage.2004.12.034.CrossRefPubMedGoogle Scholar
  19. Evans, A. C., Marrett, S., Neelin, P., Collins, L., Worsley, K., Dai, W., et al. (1992). Anatomical mapping of functional activation in stereotactic coordinate space. NeuroImage, 1(1), 43–53.CrossRefPubMedGoogle Scholar
  20. Fonov, V., Evans, A. C., Botteron, K., Almli, C. R., McKinstry, R. C., & Collins, D. L. (2011). Unbiased average age-appropriate atlases for pediatric studies. NeuroImage, 54(1), 313–327. doi:10.1016/j.neuroimage.2010.07.033.CrossRefPubMedGoogle Scholar
  21. Frey, S., Pandya, D. N., Chakravarty, M. M., Bailey, L., Petrides, M., & Collins, D. L. (2011). An MRI based average macaque monkey stereotaxic atlas and space (MNI monkey space). NeuroImage, 55(4), 1435–1442. doi:10.1016/j.neuroimage.2011.01.040.CrossRefPubMedGoogle Scholar
  22. Gao, Y., Choe, A. S., Stepniewska, I., Li, X., Avison, M. J., & Anderson, A. W. (2013). Validation of DTI tractography-based measures of primary motor area connectivity in the squirrel monkey brain. [research support, N.I.H., extramural validation studies]. PloS One, 8(10), e75065. doi:10.1371/journal.pone.0075065.CrossRefPubMedPubMedCentralGoogle Scholar
  23. Gao, Y., Khare, S. P., Panda, S., Choe, A. S., Stepniewska, I., Li, X., et al. (2014). (PMC4013108). A brain MRI atlas of the common squirrel monkey, Saimiri sciureus. In Proc SPIE Int Soc Opt Eng, Mar 13 2014 (Vol. 9038, pp. 90380C). doi:10.1117/12.2043589.
  24. Gao, Y., Parvathaneni, P., Schilling, K., Zu, Z., Choe, A., Stepniewska, I., et al. (2016). A 3D high resolution ex vivo white matter atlas of the common squirrel monkey (Saimiri sciureus) based on diffusion tensor imaging. Paper presented at the in proceedings of the SPIE medical imaging conference. California, February: San Diego.Google Scholar
  25. Gee, J. C., Reivich, M., & Bajcsy, R. (1993). Elastically deforming 3D atlas to match anatomical brain images. Journal of Computer Assisted Tomography, 17(2), 225–236.CrossRefPubMedGoogle Scholar
  26. Grabner, G., Janke, A. L., Budge, M. M., Smith, D., Pruessner, J., & Collins, D. L. (2006). Symmetric atlasing and model based segmentation: An application to the hippocampus in older adults. Medical Image Computing Computer Assisted Intervention, 9(Pt 2), 58–66.PubMedGoogle Scholar
  27. Greer, P. J., Villemagne, V. L., Ruszkiewicz, J., Graves, A. K., Meltzer, C. C., Mathis, C. A., et al. (2002). MR atlas of the baboon brain for functional neuroimaging. Brain Research Bulletin, 58(4), 429–438.CrossRefPubMedGoogle Scholar
  28. Heffner, R. S., & Masterton, R. B. (1983). The role of the corticospinal tract in the evolution of human digital dexterity. Brain, Behavior and Evolution, 23(3–4), 165–183.PubMedGoogle Scholar
  29. Hikishima, K., Quallo, M. M., Komaki, Y., Yamada, M., Kawai, K., Momoshima, S., et al. (2011). Population-averaged standard template brain atlas for the common marmoset (Callithrix Jacchus). NeuroImage, 54(4), 2741–2749. doi:10.1016/j.neuroimage.2010.10.061.CrossRefPubMedGoogle Scholar
  30. Jenett, A., Schindelin, J. E., & Heisenberg, M. (2006). The virtual insect brain protocol: Creating and comparing standardized neuroanatomy. BMC Bioinformatics, 7, 544. doi:10.1186/1471-2105-7-544.CrossRefPubMedPubMedCentralGoogle Scholar
  31. Kaas, J. H., Nelson, R. J., Sur, M., Dykes, R. W., & Merzenich, M. M. (1984). The somatotopic organization of the ventroposterior thalamus of the squirrel monkey, Saimiri Sciureus. The Journal of Comparative Neurology, 226(1), 111–140. doi:10.1002/cne.902260109.CrossRefPubMedGoogle Scholar
  32. Kaas, J. H., Stepniewska, I., & Gharbawie, O. (2012). Cortical networks subserving upper limb movements in primates. European Journal of Physical and Rehabilitation Medicine, 48(2), 299–306.PubMedPubMedCentralGoogle Scholar
  33. Knosche, T. R., Anwander, A., Liptrot, M., & Dyrby, T. B. (2015). Validation of tractography: Comparison with manganese tracing. Human Brain Mapping, 36(10), 4116–4134. doi:10.1002/hbm.22902.CrossRefPubMedPubMedCentralGoogle Scholar
  34. Kovacevic, N., Henderson, J. T., Chan, E., Lifshitz, N., Bishop, J., Evans, A. C., et al. (2005). A three-dimensional MRI atlas of the mouse brain with estimates of the average and variability. Cerebral Cortex, 15(5), 639–645. doi:10.1093/cercor/bhh165.CrossRefPubMedGoogle Scholar
  35. Leergaard, T. B., White, N. S., de Crespigny, A., Bolstad, I., D'Arceuil, H., Bjaalie, J. G., et al. (2010). Quantitative histological validation of diffusion MRI fiber orientation distributions in the rat brain. PloS One, 5(1), e8595. doi:10.1371/journal.pone.0008595.CrossRefPubMedPubMedCentralGoogle Scholar
  36. MacLean, J. A. G. P. D. (1962). A stereotaxic atlas of the squirrel monkey's brain (Saimiri sciureus) U.S. Department of health, education, and welfare.Google Scholar
  37. Mazziotta, J. C., Toga, A. W., Evans, A., Fox, P., & Lancaster, J. (1995). A probabilistic atlas of the human brain: Theory and rationale for its development. The international consortium for brain mapping (ICBM). NeuroImage, 2(2), 89–101.CrossRefPubMedGoogle Scholar
  38. McNab, J. A., Jbabdi, S., Deoni, S. C., Douaud, G., Behrens, T. E., & Miller, K. L. (2009). High resolution diffusion-weighted imaging in fixed human brain using diffusion-weighted steady state free precession. [in vitro research support, non-U.S. Gov't]. NeuroImage, 46(3), 775–785. doi:10.1016/j.neuroimage.2009.01.008.CrossRefPubMedGoogle Scholar
  39. Mori, S., Oishi, K., Jiang, H., Jiang, L., Li, X., Akhter, K., et al. (2008). Stereotaxic white matter atlas based on diffusion tensor imaging in an ICBM template. NeuroImage, 40(2), 570–582. doi:10.1016/j.neuroimage.2007.12.035.CrossRefPubMedPubMedCentralGoogle Scholar
  40. Newman, J. D., Kenkel, W. M., Aronoff, E. C., Bock, N. A., Zametkin, M. R., & Silva, A. C. (2009). A combined histological and MRI brain atlas of the common marmoset monkey, Callithrix Jacchus. Brain Research Reviews, 62(1), 1–18. doi:10.1016/j.brainresrev.2009.09.001.CrossRefPubMedPubMedCentralGoogle Scholar
  41. Nudo, R. J., Sutherland, D. P., & Masterton, R. B. (1995). Variation and evolution of mammalian corticospinal somata with special reference to primates. The Journal of Comparative Neurology, 358(2), 181–205. doi:10.1002/cne.903580203.CrossRefPubMedGoogle Scholar
  42. Paxinos, G., & Franklin, K. B. J. (2004). The mouse brain in stereotaxic coordinates (compact 2nd ed.). Amsterdam: Elsevier academic press.Google Scholar
  43. Paxinos, G., & Watson, C. (2014). Paxino's and watson's the rat brain in stereotaxic coordinates (seventh edition. Ed.). Amsterdam: Elsevier/AP, academic press is an imprint of Elsevier.Google Scholar
  44. Rohlfing, T., Zahr, N. M., Sullivan, E. V., & Pfefferbaum, A. (2008). The SRI24 Multi-Channel brain atlas: Construction and applications. Proceedings of SPIE The International Society for Optical Engineering, 6914, 691409. doi:10.1117/12.770441.PubMedPubMedCentralGoogle Scholar
  45. Rohlfing, T., Kroenke, C. D., Sullivan, E. V., Dubach, M. F., Bowden, D. M., Grant, K. A., et al. (2012). The INIA19 template and NeuroMaps atlas for primate brain image Parcellation and spatial normalization. Frontiers in Neuroinformatics, 6, 27. doi:10.3389/fninf.2012.00027.CrossRefPubMedPubMedCentralGoogle Scholar
  46. Schilling, K., Janve, V., Gao, Y., Stepniewska, I., Landman, B. A., & Anderson, A. W. (2016). Comparison of 3D orientation distribution functions measured with confocal microscopy and diffusion MRI. NeuroImage, 129, 185–197. doi:10.1016/j.neuroimage.2016.01.022.CrossRefPubMedPubMedCentralGoogle Scholar
  47. Schilling, K., Gao, Y., Stepniewska, I., Choe, A. S., Landman, B. A., & Anderson, A. W. (2017). Reproducibility and variation of diffusion measures in the squirrel monkey brain, in vivo and ex vivo. Magnetic Resonance Imaging, 35, 29–38. doi:10.1016/j.mri.2016.08.015.CrossRefPubMedGoogle Scholar
  48. Schmahmann, J. D., & Pandya, D. (2009). Fiber pathways of the brain. OUP: USA.Google Scholar
  49. Schwarz, A. J., Danckaert, A., Reese, T., Gozzi, A., Paxinos, G., Watson, C., et al. (2006). A stereotaxic MRI template set for the rat brain with tissue class distribution maps and co-registered anatomical atlas: Application to pharmacological MRI. NeuroImage, 32(2), 538–550. doi:10.1016/j.neuroimage.2006.04.214.CrossRefPubMedGoogle Scholar
  50. Shepherd, T. M., Thelwall, P. E., Stanisz, G. J., & Blackband, S. J. (2009). Aldehyde fixative solutions alter the water relaxation and diffusion properties of nervous tissue. [research support, N.I.H., extramural]. Magnetic Resonance in Medicine, 62(1), 26–34. doi:10.1002/mrm.21977.CrossRefPubMedPubMedCentralGoogle Scholar
  51. Shi, Z., Rogers, B. P., Chen, L. M., Morgan, V. L., Mishra, A., Wilkes, D. M., et al. (2016). Realistic models of apparent dynamic changes in resting-state connectivity in somatosensory cortex. Human Brain Mapping, 37(11), 3897–3910. doi:10.1002/hbm.23284.CrossRefPubMedGoogle Scholar
  52. Sled, J. G., Zijdenbos, A. P., & Evans, A. C. (1998). A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Transactions on Medical Imaging, 17(1), 87–97. doi:10.1109/42.668698.CrossRefPubMedGoogle Scholar
  53. Smith, S. M. (2002). Fast robust automated brain extraction. Human Brain Mapping, 17(3), 143–155. doi:10.1002/hbm.10062.CrossRefPubMedGoogle Scholar
  54. Smith, S. M., Johansen-Berg, H., Jenkinson, M., Rueckert, D., Nichols, T. E., Miller, K. L., et al. (2007). Acquisition and voxelwise analysis of multi-subject diffusion data with tract-based spatial statistics. Nature Protocols, 2(3), 499–503. doi:10.1038/nprot.2007.45.CrossRefPubMedGoogle Scholar
  55. Stepniewska, I., Gharbawie, O. A., Burish, M. J., & Kaas, J. H. (2014). Effects of muscimol inactivations of functional domains in motor, premotor, and posterior parietal cortex on complex movements evoked by electrical stimulation. Journal of Neurophysiology, 111(5), 1100–1119. doi:10.1152/jn.00491.2013.CrossRefPubMedGoogle Scholar
  56. Sun, P., Parvathaneni, P., Schilling, K. G., Gao, Y., Janve, V., Anderson, A., et al. (2015). Integrating histology and MRI in the first digital brain of common squirrel monkey, Saimiri sciureus Proceedings of SPIE The International Society Optical Engineering, pp. 9417 T. doi:10.1117/12.2081443.
  57. Talairach, J. (1967). Atlas d'anatomie stéréotaxique du télencéphale, études anatomo-radiologiques. Paris: Masson et Cie.Google Scholar
  58. Talairach, J., & Tournoux, P. (1988). Co-planar stereotaxic atlas of the human brain : 3-dimensional proportional system : An approach to cerebral imaging. Stuttgart: Georg Thieme.Google Scholar
  59. Tiede, U., Bomans, M., Hohne, K. H., Pommert, A., Riemer, M., Schiemann, T., et al. (1993). A computerized three-dimensional atlas of the human skull and brain. AJNR. American Journal of Neuroradiology, 14(3), 551–559 discussion 560-551.PubMedGoogle Scholar
  60. Toga, A. W. (1999). Brain warping. San Diego: Academic Press.Google Scholar
  61. Wang, Z., Chen, L. M., Negyessy, L., Friedman, R. M., Mishra, A., Gore, J. C., et al. (2013). The relationship of anatomical and functional connectivity to resting-state connectivity in primate somatosensory cortex. Neuron, 78(6), 1116–1126. doi:10.1016/j.neuron.2013.04.023.CrossRefPubMedPubMedCentralGoogle Scholar
  62. Wehrl, H. F., Bezrukov, I., Wiehr, S., Lehnhoff, M., Fuchs, K., Mannheim, J. G., et al. (2015). Assessment of murine brain tissue shrinkage caused by different histological fixatives using magnetic resonance and computed tomography imaging. Histology and Histopathology, 30(5), 601–613.PubMedGoogle Scholar
  63. Wilson 3rd, G. H., Yang, P. F., Gore, J. C., & Chen, L. M. (2016). Correlated inter-regional variations in low frequency local field potentials and resting state BOLD signals within S1 cortex of monkeys. Human Brain Mapping, 37(8), 2755–2766. doi:10.1002/hbm.23207.CrossRefPubMedGoogle Scholar
  64. Wisner, K., Odintsov, B., Brozoski, D., & Brozoski, T. J. (2016). Ratat1: A digital rat brain stereotaxic atlas derived from high-resolution MRI images scanned in three dimensions. Frontiers in Systems Neuroscience, 10, 64. doi:10.3389/fnsys.2016.00064.CrossRefPubMedPubMedCentralGoogle Scholar
  65. Woods, R. P., Fears, S. C., Jorgensen, M. J., Fairbanks, L. A., Toga, A. W., & Freimer, N. B. (2011). A web-based brain atlas of the vervet monkey, Chlorocebus Aethiops. NeuroImage, 54(3), 1872–1880. doi:10.1016/j.neuroimage.2010.09.070.CrossRefPubMedGoogle Scholar
  66. Yeh, F. C., Verstynen, T. D., Wang, Y., Fernandez-Miranda, J. C., & Tseng, W. Y. (2013). Deterministic diffusion fiber tracking improved by quantitative anisotropy. PloS One, 8(11), e80713. doi:10.1371/journal.pone.0080713.CrossRefPubMedPubMedCentralGoogle Scholar

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Authors and Affiliations

  1. 1.Vanderbilt University Institute of Imaging ScienceVanderbilt UniversityNashvilleUSA
  2. 2.Department of Biomedical EngineeringVanderbilt UniversityNashvilleUSA
  3. 3.Department of PsychologyVanderbilt UniversityNashvilleUSA
  4. 4.Radiology and Radiological SciencesVanderbilt UniversityNashvilleUSA
  5. 5.Department of Electrical EngineeringVanderbilt UniversityNashvilleUSA

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