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Brain Atlases: Their Development and Role in Functional Inference

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fMRI Techniques and Protocols

Part of the book series: Neuromethods ((NM,volume 119))

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Abstract

Imparting functional meaning to neuroanatomical location has been among the greatest challenges to neuroscientists. The characterization of the brain architecture responsible in human cognition received a boost in momentum with the emergence of in vivo functional and structural neuroimaging technology over the past 30 years. Yet, individual variability in cortical gyrification as well as the patterns of blood flow-related activity measured using fMRI and positron emission tomography complicated direct comparisons across subjects without spatially accounting for overall brain size and shape. This realization resulted in considerable effort now involving the collective efforts of neuroscientists, computer scientists, and mathematicians to develop common brain atlas spaces against which the regions of activity may be accurately referenced. We examine recent developments in brain imaging and computational anatomy that have greatly expanded our ability to analyze brain structure and function. The enormous diversity of brain maps and imaging methods has spurred the development of population-based digital brain atlases. Atlases store information on how the brain varies across age and gender, across time, in health and disease, and in large human populations. We describe how brain atlases, and the computational tools that align new datasets with them, facilitate comparison of brain data across experiments, laboratories, and from different imaging devices. The major philosophies are presented that underlie the construction of probabilistic atlases, which store information on anatomic and functional variability in a population. Algorithms which create composite brain maps and atlases based on multiple subjects are examined. We show that group patterns of cortical organization, asymmetry, and disease-specific trends can be resolved that may not be apparent in individual brain maps. Finally, we describe the development of four-dimensional maps that store information on the dynamics of brain change in development and disease.

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References

  1. Haas LF (2001) Phineas Gage and the science of brain localisation. J Neurol Neurosurg Psychiatry 71:761

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Cowie SE (2000) A place in history: Paul Broca and cerebral localization. J Invest Surg 13:297–298

    Article  CAS  PubMed  Google Scholar 

  3. Goedert M, Ghetti B (2007) Alois Alzheimer: his life and times. Brain Pathol 17:57–62

    Article  PubMed  Google Scholar 

  4. Roland PE, Zilles K (1994) Brain atlases – a new research tool. Trends Neurosci 17:458–467

    Article  CAS  PubMed  Google Scholar 

  5. Toga AW, Thompson PM (2001) Maps of the brain. Anat Rec 265:37–53

    Article  CAS  PubMed  Google Scholar 

  6. Toga AW, Thompson PM (2002) New approaches in brain morphometry. Am J Geriatr Psychiatry 10:13–23

    Article  PubMed  Google Scholar 

  7. Thompson P, Cannon TD, Toga AW (2002) Mapping genetic influences on human brain structure. Ann Med 34:523–536

    Article  CAS  PubMed  Google Scholar 

  8. Narr KL, Thompson PM, Sharma T, Moussai J, Cannestra AF, Toga AW (2000) Mapping morphology of the corpus callosum in schizophrenia. Cereb Cortex 10:40–49

    Article  CAS  PubMed  Google Scholar 

  9. Davatzikos C (1996) Spatial normalization of 3D brain images using deformable models. J Comput Assist Tomogr 20:656–665

    Article  CAS  PubMed  Google Scholar 

  10. Davatzikos C (1997) Spatial transformation and registration of brain images using elastically deformable models. Comput Vis Image Underst 66:207–222

    Article  CAS  PubMed  Google Scholar 

  11. Thompson PM, Woods RP, Mega MS, Toga AW (2000) Mathematical/computational challenges in creating deformable and probabilistic atlases of the human brain. Hum Brain Mapp 9:81–92

    Article  CAS  PubMed  Google Scholar 

  12. Weaver JB, Healy DM Jr, Periaswamy S, Kostelec PJ (1998) Elastic image registration using correlations. J Digit Imaging 11:59–65

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Barillot C, Lemoine D, Le Briquer L, Lachmann F, Gibaud B (1993) Data fusion in medical imaging: merging multimodal and multipatient images, identification of structures and 3D display aspects. Eur J Radiol 17:22–27

    Article  CAS  PubMed  Google Scholar 

  14. Woods RP, Grafton ST, Holmes CJ, Cherry SR, Mazziotta JC (1998) Automated image registration. I. General methods and intrasubject, intramodality validation. J Comput Assist Tomogr 22:139–152

    Article  CAS  PubMed  Google Scholar 

  15. Toga AW, Thompson PM, Mori S, Amunts K, Zilles K (2006) Towards multimodal atlases of the human brain. Nat Rev Neurosci 7:952–966

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Woods RP (2003) Characterizing volume and surface deformations in an atlas framework: theory, applications, and implementation. Neuroimage 18:769–788

    Article  PubMed  Google Scholar 

  17. Avants B, Gee JC (2004) Geodesic estimation for large deformation anatomical shape averaging and interpolation. Neuroimage 23(Suppl 1):S139–S150

    Article  PubMed  Google Scholar 

  18. Avants BB, Schoenemann PT, Gee JC (2006) Lagrangian frame diffeomorphic image registration: morphometric comparison of human and chimpanzee cortex. Med Image Anal 10:397–412

    Article  PubMed  Google Scholar 

  19. Evans AC, Collins DL, Milner B (1992) An MRI-based stereotactic atlas from 250 young normal subjects. J Neurosci Abstr 18:408

    Google Scholar 

  20. Durrleman S, Pennec X, Trouve A, Ayache N (2007) Measuring brain variability via sulcal lines registration: a diffeomorphic approach. Med Image Comput Comput Assist Interv 10(Pt 1):675–682

    PubMed  Google Scholar 

  21. Alayon S, Robertson R, Warfield SK, Ruiz-Alzola J (2007) A fuzzy system for helping medical diagnosis of malformations of cortical development. J Biomed Inform 40:221–235

    Article  PubMed  Google Scholar 

  22. Rohlfing T, Maurer CR Jr (2007) Shape-based averaging. IEEE Trans Image Process 16:153–161

    Article  PubMed  Google Scholar 

  23. Narr KL, Bilder RM, Luders E et al (2007) Asymmetries of cortical shape: effects of handedness, sex and schizophrenia. Neuroimage 34:939–948

    Article  PubMed  Google Scholar 

  24. Thompson PM, Giedd JN, Woods RP, MacDonald D, Evans AC, Toga AW (2000) Growth patterns in the developing brain detected by using continuum mechanical tensor maps. Nature 404:190–193

    Article  CAS  PubMed  Google Scholar 

  25. Corouge I, Dojat M, Barillot C (2004) Statistical shape modeling of low level visual area borders. Med Image Anal 8:353–360

    Article  PubMed  Google Scholar 

  26. Cardenas VA, Boxer AL, Chao LL et al (2007) Deformation-based morphometry reveals brain atrophy in frontotemporal dementia. Arch Neurol 64:873–877

    Article  PubMed  PubMed Central  Google Scholar 

  27. Leow AD, Klunder AD, Jack CR Jr et al (2006) Longitudinal stability of MRI for mapping brain change using tensor-based morphometry. Neuroimage 31:627–640

    Article  PubMed  PubMed Central  Google Scholar 

  28. Diedrichsen J (2006) A spatially unbiased atlas template of the human cerebellum. Neuroimage 33:127–138

    Article  PubMed  Google Scholar 

  29. Toga AW, Thompson PM (2005) Genetics of brain structure and intelligence. Annu Rev Neurosci 28:1–23

    Article  CAS  PubMed  Google Scholar 

  30. Toga AW, Thompson PM, Sowell ER (2006) Mapping brain maturation. Trends Neurosci 29:148–159

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Apostolova LG, Thompson PM (2007) Brain mapping as a tool to study neurodegeneration. Neurotherapeutics 4(3):387–400

    Article  PubMed  PubMed Central  Google Scholar 

  32. Apostolova LG, Akopyan GG, Partiali N et al (2007) Structural correlates of apathy in Alzheimer’s disease. Dement Geriatr Cogn Disord 24:91–97

    Article  PubMed  Google Scholar 

  33. Apostolova LG, Lu P, Rogers S et al (2008) 3D mapping of language networks in clinical and pre-clinical Alzheimer’s disease. Brain Lang 104:33–41

    Article  PubMed  Google Scholar 

  34. Scher AI, Xu Y, Korf ES et al (2007) Hippocampal shape analysis in Alzheimer’s disease: a population-based study. Neuroimage 36:8–18

    Article  CAS  PubMed  Google Scholar 

  35. Thompson PM, Hayashi KM, Dutton RA et al (2007) Tracking Alzheimer’s disease. Ann N Y Acad Sci 1097:183–214

    Article  PubMed  PubMed Central  Google Scholar 

  36. Mazziotta JC, Toga AW, Evans AC, Fox PT, Lancaster JL (1995) Digital brain atlases. Trends Neurosci 18:210–211

    Article  CAS  PubMed  Google Scholar 

  37. Toga AW, Thompson PM, Mega MS, Narr KL, Blanton RE (2001) Probabilistic approaches for atlasing normal and disease-specific brain variability. Anat Embryol (Berl) 204:267–282

    Article  CAS  Google Scholar 

  38. Wakana S, Jiang H, Nagae-Poetscher LM, van Zijl PC, Mori S (2004) Fiber tract-based atlas of human white matter anatomy. Radiology 230:77–87

    Article  PubMed  Google Scholar 

  39. Van Essen DC (2005) A Population-Average, Landmark- and Surface-based (PALS) atlas of human cerebral cortex. Neuroimage 15:635–662

    Article  Google Scholar 

  40. Fox PT, Perlmutter JS, Raichle ME (1984) Stereotactic method for determining anatomical localization in physiological brain images. J Cereb Blood Flow Metab 4:634

    Article  CAS  PubMed  Google Scholar 

  41. Evans AC, Marrett S, Neelin P et al (1992) Anatomical mapping of functional activation in stereotactic coordinate space. Neuroimage 1:43–53

    Article  CAS  PubMed  Google Scholar 

  42. Nowinski WL, Thirunavuukarasuu A (2001) Atlas-assisted localization analysis of functional images. Med Image Anal 5:207–220

    Article  CAS  PubMed  Google Scholar 

  43. Crivello F, Schormann T, Tzourio-Mazoyer N, Roland PE, Zilles K, Mazoyer BM (2002) Comparison of spatial normalization procedures and their impact on functional maps. Hum Brain Mapp 16:228–250

    Article  PubMed  Google Scholar 

  44. Swallow KM, Braver TS, Snyder AZ, Speer NK, Zacks JM (2003) Reliability of functional localization using fMRI. Neuroimage 20:1561–1577

    Article  PubMed  Google Scholar 

  45. Tu Z, Zheng S, Yuille AL et al (2007) Automated extraction of the cortical sulci based on a supervised learning approach. IEEE Trans Med Imaging 26:541–552

    Article  PubMed  Google Scholar 

  46. Luders E, Thompson PM, Narr KL, Toga AW, Jancke L, Gaser C (2006) A curvature-based approach to estimate local gyrification on the cortical surface. Neuroimage 29:1224–1230

    Article  CAS  PubMed  Google Scholar 

  47. Ashburner J, Friston KJ (1999) Nonlinear spatial normalization using basis functions. Hum Brain Mapp 7:254–266

    Article  CAS  PubMed  Google Scholar 

  48. Friston KJ, Stephan KE, Lund TE, Morcom A, Kiebel S (2005) Mixed-effects and fMRI studies. Neuroimage 24:244–252

    Article  CAS  PubMed  Google Scholar 

  49. Miller MB, Van Horn JD, Wolford GL et al (2002) Extensive individual differences in brain activations associated with episodic retrieval are reliable over time. J Cogn Neurosci 14:1200–1214

    Article  PubMed  Google Scholar 

  50. Fox PT, Parsons LM, Lancaster JL (1998) Beyond the single study: function/location metanalysis in cognitive neuroimaging. Curr Opin Neurobiol 8:178–187

    Article  CAS  PubMed  Google Scholar 

  51. Nowinski WL (2005) The cerefy brain atlases: continuous enhancement of the electronic talairach-tournoux brain atlas. Neuroinformatics 3:293–300

    Article  PubMed  Google Scholar 

  52. Amunts K, Schleicher A, Zilles K (2007) Cytoarchitecture of the cerebral cortex – more than localization. Neuroimage 37:1061–1065, discussion 6–8

    Article  CAS  PubMed  Google Scholar 

  53. Mazziotta J, Toga AW, Evans A et al (2001) A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM). Philos Trans R Soc Lond B Biol Sci 356:1293–1322

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Nowinski WL (2001) Modified Talairach landmarks. Acta Neurochir (Wien) 143:1045–1057

    Article  CAS  Google Scholar 

  55. Bookstein FL (2001) Voxel-based morphometry” should not be used with imperfectly registered images. Neuroimage 14:1454–1462

    Article  CAS  PubMed  Google Scholar 

  56. Talairach J, Tournoux P (1988) Co-planar stereotactic atlas of the human brain. Tieme, New York

    Google Scholar 

  57. Maldjian JA, Laurienti PJ, Burdette JH (2004) Precentral gyrus discrepancy in electronic versions of the Talairach atlas. Neuroimage 21:450–455

    Article  PubMed  Google Scholar 

  58. Shattuck DW, Mirza M, Adisetiyo V et al (2008) Construction of a 3D probabilistic atlas of human cortical structures. Neuroimage 39:1064–1080

    Article  PubMed  Google Scholar 

  59. Woods RP, Grafton ST, Watson JD, Sicotte NL, Mazziotta JC (1998) Automated image registration. II. Intersubject validation of linear and nonlinear models. J Comput Assist Tomogr 22:153–165

    Article  CAS  PubMed  Google Scholar 

  60. Rex DE, Ma JQ, The TAW, LONI (2003) Pipeline processing environment. Neuroimage 19:1033–1048

    Article  PubMed  Google Scholar 

  61. Smith SM, Jenkinson M, Woolrich MW et al (2004) Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage 23(Suppl 1):S208–S219

    Article  PubMed  Google Scholar 

  62. Ashburner J, Friston KJ (2005) Unified segmentation. Neuroimage 26:839–851

    Article  PubMed  Google Scholar 

  63. Van Essen DC (2002) Windows on the brain: the emerging role of atlases and databases in neuroscience. Curr Opin Neurobiol 12:574–579

    Article  PubMed  Google Scholar 

  64. Mazziotta J, Toga A, Evans A et al (2001) A four-dimensional probabilistic atlas of the human brain. J Am Med Inform Assoc 8:401–430

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Mega MS, Dinov ID, Mazziotta JC et al (2005) Automated brain tissue assessment in the elderly and demented population: construction and validation of a sub-volume probabilistic brain atlas. Neuroimage 26:1009–1018

    Article  PubMed  Google Scholar 

  66. Yoon U, Lee JM, Koo BB et al (2005) Quantitative analysis of group-specific brain tissue probability map for schizophrenic patients. Neuroimage 26:502–512

    Article  PubMed  Google Scholar 

  67. Cannon TD, Thompson PM, van Erp TG et al (2006) Mapping heritability and molecular genetic associations with cortical features using probabilistic brain atlases: methods and applications to schizophrenia. Neuroinformatics 4:5–19

    Article  PubMed  Google Scholar 

  68. Wilke M, Schmithorst VJ, Holland SK (2002) Assessment of spatial normalization of whole-brain magnetic resonance images in children. Hum Brain Mapp 17:48–60

    Article  PubMed  Google Scholar 

  69. Jelacic S, de Regt D, Weinberger E (2006) Interactive digital MR atlas of the pediatric brain. Radiographics 26:497–501

    Article  PubMed  Google Scholar 

  70. Joshi S, Davis B, Jomier M, Gerig G (2004) Unbiased diffeomorphic atlas construction for computational anatomy. Neuroimage 23(Suppl 1):S151–S160

    Article  PubMed  Google Scholar 

  71. Mazziotta J, Toga A, Evans A et al (2001) A four-dimensional probabilistic atlas of the human brain. J Am Med Inform Assoc 8:401–430

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Narr K, Thompson P, Sharma T et al (2001) Three-dimensional mapping of gyral shape and cortical surface asymmetries in schizophrenia: gender effects. Am J Psychiatry 158:244–255

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Amunts K, Hawrylycz MJ, Van Essen DC et al (2014) Interoperable atlases of the human brain. Neuroimage 99:525–532

    Article  CAS  PubMed  Google Scholar 

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Authors and Affiliations

  1. USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, 2001 North Soto Street SSB1-102, Los Angeles, CA, 90032, USA

    John Darrell Van Horn & Arthur W. Toga

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  1. John Darrell Van Horn
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  2. Arthur W. Toga
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Correspondence to Arthur W. Toga .

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Editors and Affiliations

  1. Neuroimaging Research Unit, INSPE, Division of Neuroscience, San Raffaele Scientific Institute and Vita-Salute San Raffaele University, Milan, Italy

    Massimo Filippi

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Van Horn, J.D., Toga, A.W. (2016). Brain Atlases: Their Development and Role in Functional Inference. In: Filippi, M. (eds) fMRI Techniques and Protocols. Neuromethods, vol 119. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-5611-1_9

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  • DOI: https://doi.org/10.1007/978-1-4939-5611-1_9

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-5609-8

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