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High thickness histological sections as alternative to study the three-dimensional microscopic human sub-cortical neuroanatomy

Abstract

Stereotaxy is based on the precise image-guided spatial localization of targets within the human brain. Even with the recent advances in MRI technology, histological examination renders different (and complementary) information of the nervous tissue. Although several maps have been selected as a basis for correlating imaging results with the anatomical locations of sub-cortical structures, technical limitations interfere in a point-to-point correlation between imaging and anatomy due to the lack of precise correction for post-mortem tissue deformations caused by tissue fixation and processing. We present an alternative method to parcellate human brain cytoarchitectural regions, minimizing deformations caused by post-mortem and tissue-processing artifacts and enhancing segmentation by means of modified high thickness histological techniques and registration with MRI of the same specimen and into MNI space (ICBM152). A three-dimensional (3D) histological atlas of the human thalamus, basal ganglia, and basal forebrain cholinergic system is displayed. Structure’s segmentations were performed in high-resolution dark-field and light-field microscopy. Bidimensional non-linear registration of the histological slices was followed by 3D registration with in situ MRI of the same subject. Manual and automated registration procedures were adopted and compared. To evaluate the quality of the registration procedures, Dice similarity coefficient and normalized weighted spectral distance were calculated and the results indicate good overlap between registered volumes and a small shape difference between them in both manual and automated registration methods. High thickness high-resolution histological slices in combination with registration to in situ MRI of the same subject provide an effective alternative method to study nuclear boundaries in the human brain, enhancing segmentation and demanding less resources and time for tissue processing than traditional methods.

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Color coding follows Grinberg and Heinsen (2007), Mesulam’s nomenclature is adapted from Mesulam et al. (1983)

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References

  1. Afshar F, Watkins ES, Yap JC (1978) Stereotaxic atlas of the human brainstem and cerebellar nuclei: a variability study. Raven Press, New York

    Google Scholar 

  2. Alegro M, Loring B, Alho E et al (2016) Multimodal whole brain registration: MRI and high resolution histology. http://www.cv-foundation.org/openaccess/content_cvpr_2016_workshops/w15/papers/Alegro_Multimodal_Whole_Brain_CVPR_2016_paper.pdf. Accessed 9 Sep 2016

  3. Alho ATDL, Hamani C, Alho EJL et al (2017) Magnetic resonance diffusion tensor imaging for the pedunculopontine nucleus: proof of concept and histological correlation. Brain Struct Funct. https://doi.org/10.1007/s00429-016-1356-0

    Google Scholar 

  4. Alic L, Haeck JH (2010) Multi-modal image registration: matching MRI with histology. SPIE Medical Imaging, San Diego

    Google Scholar 

  5. Amunts K, Lepage C, Borgeat L et al (2013) BigBrain: an ultrahigh-resolution 3D human brain model. Science 340:1472–1475. https://doi.org/10.1126/science.1235381

    CAS  Article  PubMed  Google Scholar 

  6. Andrew J, Watkins ES (1969) A stereotaxic atlas of the human thalamus and adjacent structures: a variability study. Williams and Wilkins, Baltimore

    Google Scholar 

  7. Aoki S, Okada Y, Nishimura K et al (1989) Normal deposition of brain iron in childhood and adolescence: MR imaging at 1.5 T. Radiology 172:381–385. https://doi.org/10.1148/radiology.172.2.2748819

    CAS  Article  PubMed  Google Scholar 

  8. Avants BB, Epstein CL, Grossman M, Gee JC (2008) Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain. Med Image Anal 12:26–41. https://doi.org/10.1016/j.media.2007.06.004

    CAS  Article  PubMed  Google Scholar 

  9. Bauchot R (1967) Modifications of brain weight in the course of fixation. J Für Hirnforsch 9:253–283

    CAS  Google Scholar 

  10. Butler T, Zaborszky L, Pirraglia E et al (2014) Comparison of human septal nuclei MRI measurements using automated segmentation and a new manual protocol based on histology. NeuroImage 97:245–251. https://doi.org/10.1016/j.neuroimage.2014.04.026

    Article  PubMed  PubMed Central  Google Scholar 

  11. Carballo-Barreda M, RodríGuez-Rojas R, Torres-Montoya A, LóPez-Flores G (2007) Computerized atlas for image-guided stereotactic functional neurosurgery. Neurocir Astur Spain 18:478–484

    CAS  Article  Google Scholar 

  12. Casanova MF, Kreczmanski P, Trippe J 2nd et al (2008) Neuronal distribution in the neocortex of schizophrenic patients. Psychiatry Res 158:267–277. https://doi.org/10.1016/j.psychres.2006.12.009

    Article  PubMed  Google Scholar 

  13. Chakravarty MM, Bertrand G, Hodge CP et al (2006) The creation of a brain atlas for image guided neurosurgery using serial histological data. NeuroImage 30:359–376. https://doi.org/10.1016/j.neuroimage.2005.09.041

    Article  PubMed  Google Scholar 

  14. Crum WR, Camara O, Hill DLG (2006) Generalized overlap measures for evaluation and validation in medical image analysis. IEEE Trans Med Imaging 25:1451–1461. https://doi.org/10.1109/TMI.2006.880587

    Article  PubMed  Google Scholar 

  15. Dandy WE (1918) Ventriculography following the injection of air into the cerebral ventricles. Ann Surg 68:5–11

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  16. Dice LR (1945) Measures of the amount of ecologic association between species. Ecology 26:297–302. https://doi.org/10.2307/1932409

    Article  Google Scholar 

  17. Drayer B, Burger P, Darwin R et al (1986) MRI of brain iron. AJR Am J Roentgenol 147:103–110. https://doi.org/10.2214/ajr.147.1.103

    CAS  Article  PubMed  Google Scholar 

  18. Duyn JH (2012) The future of ultra-high field MRI and fMRI for study of the human brain. Neuroimage 62:1241–1248. https://doi.org/10.1016/j.neuroimage.2011.10.065

    Article  PubMed  Google Scholar 

  19. Emmers R, Tasker R (1975) The human somesthetic thalamus: with maps for physiological target localization during stereotactic neurosurgery. Raven Press, New York

    Google Scholar 

  20. Ewers M, Frisoni GB, Teipel SJ et al (2011) Staging Alzheimer’s disease progression with multimodality neuroimaging. Prog Neurobiol 95:535–546. https://doi.org/10.1016/j.pneurobio.2011.06.004

    Article  PubMed  PubMed Central  Google Scholar 

  21. Ewert S, Plettig P, Li N et al (2017) Toward defining deep brain stimulation targets in MNI space: a subcortical atlas based on multimodal MRI, histology and structural connectivity. NeuroImage. https://doi.org/10.1016/j.neuroimage.2017.05.015

    PubMed Central  Google Scholar 

  22. Fonoff ET, Campos WK, Mandel M et al (2012) Bilateral subthalamic nucleus stimulation for generalized dystonia after bilateral pallidotomy. Mov Disord Off J Mov Disord Soc 27:1559–1563. https://doi.org/10.1002/mds.25127

    Article  Google Scholar 

  23. Fonov V, Evans AC, Botteron K et al (2011) Unbiased average age-appropriate atlases for pediatric studies. NeuroImage 54:313–327. https://doi.org/10.1016/j.neuroimage.2010.07.033

    Article  PubMed  Google Scholar 

  24. François C, Yelnik J, Percheron G (1996) A stereotaxic atlas of the basal ganglia in macaques. Brain Res Bull 41:151–158

    Article  PubMed  Google Scholar 

  25. Franklin K, Paxinos G (2008) The mouse brain in stereotaxic coordinates. Academic Press, New York

    Google Scholar 

  26. Ganser KA, Dickhaus H, Metzner R, Wirtz CR (2004) A deformable digital brain atlas system according to Talairach and Tournoux. Med Image Anal 8:3–22

    Article  PubMed  Google Scholar 

  27. Grinberg L, Heinsen H (2007) Computer-assisted 3D reconstruction of the human basal forebrain complex. Dement Neuropsychol 1:140–146

    Article  PubMed  PubMed Central  Google Scholar 

  28. Grinberg LT, Amaro E Jr, Teipel S et al (2008) Assessment of factors that confound MRI and neuropathological correlation of human postmortem brain tissue. Cell Tissue Bank 9:195–203. https://doi.org/10.1007/s10561-008-9080-5

    Article  PubMed  Google Scholar 

  29. Grinberg LT, Amaro Junior E, da Silva AV et al (2009) Improved detection of incipient vascular changes by a biotechnological platform combining post mortem MRI in situ with neuropathology. J Neurol Sci 283:2–8. https://doi.org/10.1016/j.jns.2009.02.327

    Article  PubMed  Google Scholar 

  30. Haakma W, Pedersen M, Froeling M et al (2016) Diffusion tensor imaging of peripheral nerves in non-fixed post-mortem subjects. Forensic Sci Int 263:139–146. https://doi.org/10.1016/j.forsciint.2016.04.001

    Article  PubMed  Google Scholar 

  31. Hallgren B, Sourander P (1958) The effect of age on the non-haemin iron in the human brain. J Neurochem 3:41–51

    CAS  Article  PubMed  Google Scholar 

  32. Hassler R, Schaltenbrand G, Walker E (1982) Architectonic organization of the thalamic nuclei. In: Schaltenbrand G, Walker E (eds) Stereotaxy of the human brain: anatomical, physiological and clinical applications, 2nd edn. George Thieme Verlag, Stuttgart

    Google Scholar 

  33. Heckers S, Heinsen H, Heinsen Y, Beckmann H (1991) Cortex, white matter, and basal ganglia in schizophrenia: a volumetric postmortem study. Biol Psychiatry 29:556–566

    CAS  Article  PubMed  Google Scholar 

  34. Heinsen H, Heinsen YL (1991) Serial thick, frozen, gallocyanin stained sections of human central nervous system. J Histotechnol 14:167–173

    Article  Google Scholar 

  35. Heinsen H, Henn R, Eisenmenger W et al (1994a) Quantitative investigations on the human entorhinal area: left–right asymmetry and age-related changes. Anat Embryol (Berl) 190:181–194

    CAS  Article  Google Scholar 

  36. Heinsen H, Strik M, Bauer M et al (1994b) Cortical and striatal neurone number in Huntington’s disease. Acta Neuropathol (Berl) 88:320–333

    CAS  Article  Google Scholar 

  37. Heinsen H, Rüb U, Gangnus D et al (1996) Nerve cell loss in the thalamic centromedian–parafascicular complex in patients with Huntington’s disease. Acta Neuropathol (Berl) 91:161–168

    CAS  Article  Google Scholar 

  38. Heinsen H, Arzberger T, Schmitz C (2000) Celloidin mounting (embedding without infiltration)—a new, simple and reliable method for producing serial sections of high thickness through complete human brains and its application to stereological and immunohistochemical investigations. J Chem Neuroanat 20:49–59

    CAS  Article  PubMed  Google Scholar 

  39. Hirai T, Jones EG (1989) A new parcellation of the human thalamus on the basis of histochemical staining. Brain Res Brain Res Rev 14:1–34

    CAS  Article  PubMed  Google Scholar 

  40. Horn A, Kühn AA (2015) Lead-DBS: a toolbox for deep brain stimulation electrode localizations and visualizations. NeuroImage 107:127–135. https://doi.org/10.1016/j.neuroimage.2014.12.002

    Article  PubMed  Google Scholar 

  41. Ilinsky IA, Kultas-Ilinsky K, Knosp B (2002) Stereotactic atlas of the Macaca mulatta thalamus and adjacent basal ganglia nuclei. Springer, Boston

    Book  Google Scholar 

  42. Jenkinson M, Beckmann CF, Behrens TEJ et al (2012) FSL. NeuroImage 62:782–790. https://doi.org/10.1016/j.neuroimage.2011.09.015

    Article  PubMed  Google Scholar 

  43. Kilimann I, Grothe M, Heinsen H et al (2014) Subregional basal forebrain atrophy in Alzheimer’s disease: a multicenter study. J Alzheimers Dis JAD 40:687–700. https://doi.org/10.3233/JAD-132345

    PubMed  Google Scholar 

  44. König JFR, Klippel RA (1963) The rat brain: a stereotaxic atlas of the forebrain and lower parts of the brain stem. Williams and Wilkins, Baltimore

    Google Scholar 

  45. Konukoglu E, Glocker B, Ye DH et al (2012) Discriminative segmentation-based evaluation through shape dissimilarity. IEEE Trans Med Imaging 31:2278–2289

    Article  PubMed  PubMed Central  Google Scholar 

  46. Konukoglu E, Glocker B, Criminisi A, Pohl KM (2013) WESD—weighted spectral distance for measuring shape dissimilarity. IEEE Trans Pattern Anal Mach Intell 35:2284–2297

    Article  PubMed  PubMed Central  Google Scholar 

  47. Krauth A, Blanc R, Poveda A et al (2010) A mean three-dimensional atlas of the human thalamus: generation from multiple histological data. NeuroImage 49:2053–2062. https://doi.org/10.1016/j.neuroimage.2009.10.042

    Article  PubMed  Google Scholar 

  48. Kretschmann HJ, Tafesse U, Herrmann A (1982) Different volume changes of cerebral cortex and white matter during histological preparation. Microsc Acta 86:13–24

    CAS  PubMed  Google Scholar 

  49. Kroon JP, Riley AL (1986) A microcomputer-based system for stereotaxic coordinates in the rat brain. Physiol Behav 38:593–596

    CAS  Article  PubMed  Google Scholar 

  50. Kumazawa-Manita N, Katayama M, Hashikawa T, Iriki A (2013) Three-dimensional reconstruction of brain structures of the rodent Octodon degus: a brain atlas constructed by combining histological and magnetic resonance images. Exp Brain Res 231:65–74. https://doi.org/10.1007/s00221-013-3667-1

    Article  PubMed  PubMed Central  Google Scholar 

  51. Lanciego JL, Vázquez A (2012) The basal ganglia and thalamus of the long-tailed macaque in stereotaxic coordinates. A template atlas based on coronal, sagittal and horizontal brain sections. Brain Struct Funct 217:613–666. https://doi.org/10.1007/s00429-011-0370-5

    Article  PubMed  Google Scholar 

  52. Mai JK, Paxinos G, Voss T (2008) Atlas of the human brain. Academic Press, New York

    Google Scholar 

  53. Martin RF, Bowden DM (1996) A stereotaxic template atlas of the macaque brain for digital imaging and quantitative neuroanatomy. NeuroImage 4:119–150. https://doi.org/10.1006/nimg.1996.0036

    CAS  Article  PubMed  Google Scholar 

  54. Martinez RCR, Hamani C, de Carvalho MC et al (2013) Intraoperative dopamine release during globus pallidus internus stimulation in Parkinson’s disease. Mov Disord Off J Mov Disord Soc. https://doi.org/10.1002/mds.25691

    Google Scholar 

  55. Mesulam MM, Mufson EJ, Wainer BH, Levey AI (1983) Central cholinergic pathways in the rat: an overview based on an alternative nomenclature (Ch1–Ch6). Neuroscience 10:1185–1201

    CAS  Article  PubMed  Google Scholar 

  56. Morel A (2007) Stereotactic atlas of the human thalamus and basal ganglia. Informa Healthcare, New York

    Book  Google Scholar 

  57. Morel A, Magnin M, Jeanmonod D (1997) Multiarchitectonic and stereotactic atlas of the human thalamus. J Comp Neurol 387:588–630

    CAS  Article  PubMed  Google Scholar 

  58. Niemann K, van Nieuwenhofen I (1999) One Atlas–Three Anatomies: relationships of the Schaltenbrand and Wahren Microscopic Data. Acta Neurochir (Wien) 141:1025–1038

    CAS  Article  Google Scholar 

  59. Niemann K, Naujokat C, Pohl G et al (1994) Verification of the Schaltenbrand and Wahren stereotactic atlas. Acta Neurochir (Wien) 129:72–81

    CAS  Article  Google Scholar 

  60. Nowinski WL, Belov D (2003) The Cerefy Neuroradiology Atlas: a Talairach–Tournoux atlas-based tool for analysis of neuroimages available over the internet. NeuroImage 20:50–57

    Article  PubMed  Google Scholar 

  61. Nowinski WL, Fang A, Nguyen BT et al (1997) Multiple brain atlas database and atlas-based neuroimaging system. Comput Aided Surg Off J Int Soc Comput Aided Surg 2:42–66. https://doi.org/10.1002/(SICI)1097-0150(1997)2:1<42:AID-IGS7>3.0.CO;2-N

    CAS  Article  Google Scholar 

  62. Nowinski WL, Belov D, Thirunavuukarasuu A, Benabid AL (2005) A probabilistic functional atlas of the VIM nucleus constructed from pre-, intra- and postoperative electrophysiological and neuroimaging data acquired during the surgical treatment of Parkinson’s disease patients. Stereotact Funct Neurosurg 83:190–196. https://doi.org/10.1159/000091082

    Article  PubMed  Google Scholar 

  63. Nowinski WL, Liu J, Thirunavuukarasuu A (2006) Quantification and visualization of the three-dimensional inconsistency of the subthalamic nucleus in the Schaltenbrand–Wahren brain atlas. Stereotact Funct Neurosurg 84:46–55. https://doi.org/10.1159/000093722

    Article  PubMed  Google Scholar 

  64. Ono M, Kubik S, Abernathey CD (1990) Atlas of the cerebral sulci. G. Thieme Verlag/Thieme Medical Publishers, Stuttgart/New York

    Google Scholar 

  65. Paxinos G, Watson C (1986) The rat brain in stereotaxic coordinates. Academic Press, New York

    Google Scholar 

  66. Quester R, Schröder R (1997) The shrinkage of the human brain stem during formalin fixation and embedding in paraffin. J Neurosci Methods 75:81–89

    CAS  Article  PubMed  Google Scholar 

  67. Reese R, Pinsker MO, Herzog J et al (2012) The atypical subthalamic nucleus—an anatomical variant relevant for stereotactic targeting. Mov Disord Off J Mov Disord Soc 27:544–548. https://doi.org/10.1002/mds.24902

    Article  Google Scholar 

  68. Reuter M, Rosas HD, Fischl B (2010) Highly accurate inverse consistent registration: a robust approach. NeuroImage 53:1181–1196. https://doi.org/10.1016/j.neuroimage.2010.07.020

    Article  PubMed  PubMed Central  Google Scholar 

  69. Saleem KS, Logothetis NK (2012) A combined MRI and histology atlas of the rhesus monkey brain in stereotaxic coordinates. Academic Press, New York

    Google Scholar 

  70. Schaltenbrand G, Bailey P (1959) Introduction to stereotaxis with an atlas of the human brain, vol I: Text, vol II: Plate 1–57, vol III: Plate 58–76. Georg Thieme, Grune & Stratton:Stuttgart, New York

  71. Schaltenbrand G, Hassler R, Wahren W (1977) Atlas for stereotaxy of the human brain: with an accompanying guide. Thieme, Stuttgart

    Google Scholar 

  72. Schulz G, Crooijmans HJA, Germann M et al (2011) Three-dimensional strain fields in human brain resulting from formalin fixation. J Neurosci Methods 202:17–27. https://doi.org/10.1016/j.jneumeth.2011.08.031

    Article  PubMed  Google Scholar 

  73. Schwarz AJ, Danckaert A, Reese T 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 32:538–550. https://doi.org/10.1016/j.neuroimage.2006.04.214

    Article  PubMed  Google Scholar 

  74. Shanta TR, Manocha SL, Bourne GH (1968) A stereotaxic atlas of the java monkey brain (Macaca irus). Basel, Karger, doi:10.1159/000390681

  75. Simmons DM, Swanson LW (2009) Comparing histological data from different brains: sources of error and strategies for minimizing them. Brain Res Rev 60:349–367. 10.1016/j.brainresrev.2009.02.002

    Article  PubMed  PubMed Central  Google Scholar 

  76. Small CS, Peterson DI (1982) The reliability of dimensions of formalin-fixed brains. Neurology 32:413–415

    CAS  Article  PubMed  Google Scholar 

  77. Spiegel EA, Wycis HT, Freed H (1952) Stereoencephalotomy: thalamotomy and related procedures. J Am Med Assoc 148:446–451. https://doi.org/10.1001/jama.1952.02930060028009

    CAS  Article  PubMed  Google Scholar 

  78. St-Jean P, Sadikot AF, Collins L et al (1998) Automated atlas integration and interactive three-dimensional visualization tools for planning and guidance in functional neurosurgery. IEEE Trans Med Imaging 17:672–680. https://doi.org/10.1109/42.736017

    CAS  Article  PubMed  Google Scholar 

  79. Talairach J (1957) Atlas d’anatomie stéréotaxique; repérage radiologique indirect des noyaux gris centraux des régions mésencéphalo-sous-optique et hypothalamique de l’homme. Masson, Paris

    Google Scholar 

  80. Talairach J, Tournoux P (1988) Co-planar stereotaxic atlas of the human brain: 3-dimensional proportional system: an approach to medical cerebral imaging. Thieme, Stuttgart

    Google Scholar 

  81. Teipel SJ, Meindl T, Grinberg L et al (2008) Novel MRI techniques in the assessment of dementia. Eur J Nucl Med Mol Imaging 35(Suppl 1):S58–S69. https://doi.org/10.1007/s00259-007-0703-z

    Article  PubMed  Google Scholar 

  82. Teipel SJ, Meindl T, Grinberg L et al (2011) The cholinergic system in mild cognitive impairment and Alzheimer’s disease: an in vivo MRI and DTI study. Hum Brain Mapp 32:1349–1362. https://doi.org/10.1002/hbm.21111

    Article  PubMed  Google Scholar 

  83. Teipel SJ, Flatz W, Ackl N et al (2014) Brain atrophy in primary progressive aphasia involves the cholinergic basal forebrain and Ayala’s nucleus. Psychiatry Res 221:187–194. https://doi.org/10.1016/j.pscychresns.2013.10.003

    Article  PubMed  Google Scholar 

  84. Toga AW, Samaie M, Payne BA (1989) Digital rat brain: a computerized atlas. Brain Res Bull 22:323–333

    CAS  Article  PubMed  Google Scholar 

  85. Van Buren JM, Borke RC (1972) Variations and connections of the human thalamus. Springer, Berlin

    Book  Google Scholar 

  86. Yelnik J, Bardinet E, Dormont D et al (2007) A three-dimensional, histological and deformable atlas of the human basal ganglia. I. Atlas construction based on immunohistochemical and MRI data. NeuroImage 34:618–638. https://doi.org/10.1016/j.neuroimage.2006.09.026

    Article  PubMed  Google Scholar 

  87. Yoshida M (1987) Creation of a three-dimensional atlas by interpolation from Schaltenbrand–Bailey’s atlas. Appl Neurophysiol 50:45–48

    CAS  PubMed  Google Scholar 

  88. Zaborszky L, Hoemke L, Mohlberg H et al (2008) Stereotaxic probabilistic maps of the magnocellular cell groups in human basal forebrain. NeuroImage 42:1127–1141. https://doi.org/10.1016/j.neuroimage.2008.05.055

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

The authors would like to thank the team participating on the São Paulo-Würzburg collaborative project. This includes all members of the Brain Bank of the Brazilian Aging Brain Research Group (BBBABSG) of the University of São Paulo Medical School, Mrs. E. Broschk and Mrs. A. Bahrke from the Morphological Brain Research Unit of the University of Würzburg, Germany.

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Correspondence to Eduardo Joaquim Lopes Alho.

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This study was supported by resources from the University of Sao Paulo School of Medicine, Brazil and University of Würzburg, Germany. The author Eduardo Joaquim Lopes Alho was supported by a scholarship from CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior) agency, Brazil, for doctoral studies at the University of Würzburg, Germany. The authors do not have personal financial or institutional interest in any of the drugs, materials, or devices described in this article.

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The authors disclose any actual or potential conflict of interest including any financial, personal, or other relationships with other people or organizations within 3 years of beginning the submitted work that could inappropriately influence, or be perceived to influence, their work.

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Alho, E.J.L., Alho, A.T.D.L., Grinberg, L. et al. High thickness histological sections as alternative to study the three-dimensional microscopic human sub-cortical neuroanatomy. Brain Struct Funct 223, 1121–1132 (2018). https://doi.org/10.1007/s00429-017-1548-2

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Keywords

  • Cytoarchitecture
  • Thalamus
  • Sub-cortical atlas
  • Magnetic resonance imaging