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Quantitative architectural analysis: a new approach to cortical mapping

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Abstract

Recent progress in anatomical and functional MRI has revived the demand for a reliable, topographic map of the human cerebral cortex. Till date, interpretations of specific activations found in functional imaging studies and their topographical analysis in a spatial reference system are, often, still based on classical architectonic maps. The most commonly used reference atlas is that of Brodmann and his successors, despite its severe inherent drawbacks. One obvious weakness in traditional, architectural mapping is the subjective nature of localising borders between cortical areas, by means of a purely visual, microscopical examination of histological specimens. To overcome this limitation, more objective, quantitative mapping procedures have been established in the past years. The quantification of the neocortical, laminar pattern by defining intensity line profiles across the cortical layers, has a long tradition. During the last years, this method has been extended to enable a reliable, reproducible mapping of the cortex based on image analysis and multivariate statistics. Methodological approaches to such algorithm-based, cortical mapping were published for various architectural modalities. In our contribution, principles of algorithm-based mapping are described for cyto- and receptorarchitecture. In a cytoarchitectural parcellation of the human auditory cortex, using a sliding window procedure, the classical areal pattern of the human superior temporal gyrus was modified by a replacing of Brodmann’s areas 41, 42, 22 and parts of area 21, with a novel, more detailed map. An extension and optimisation of the sliding window procedure to the specific requirements of receptorarchitectonic mapping, is also described using the macaque central sulcus and adjacent superior parietal lobule as a second, biologically independent example. Algorithm-based mapping procedures, however, are not limited to these two architectural modalities, but can be applied to all images in which a laminar cortical pattern can be detected and quantified, e.g. myeloarchitectonic and in vivo high resolution MR imaging. Defining cortical borders, based on changes in cortical lamination in high resolution, in vivo structural MR images will result in a rapid increase of our knowledge on the structural parcellation of the human cerebral cortex.

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Abbreviations

2D:

two-dimensional

3D:

three-dimensional

AChE:

acetylcholinesterase

BA:

Brodmann’s area

CL:

cluster analysis

Cs:

central sulcus

d :

cortical depth

GLI:

Grey level index

HG:

Heschl’s gyrus

HS:

Heschl’s sulcus

ips:

intraparietal sulcus

l :

length of feature vector

MD:

Mahalanobis distance

MRI:

magnet resonance imaging

MTG:

middle temporal gyrus

n :

number of profiles in a cortical sector

P :

level of significance

ROI:

region of interest

STG:

superior temporal gyrus

STS:

superior temporal sulcus

SW:

sliding window

TP:

temporal plane

w :

width of a cortical layer

References

  • Amunts K, Zilles K (2001) Advances in cytoarchitectonic mapping of the human cerebral cortex. Anat Basis Funct Magn Reson Imaging 11:151–169

    CAS  Google Scholar 

  • Amunts K, Schleicher A, Bürgel U, Mohlberg H, Uylings HBM, Zilles K (1999) Broca’s region revisited: cytoarchitecture and intersubject variability. J Comp Neurol 412:319–341

    Article  PubMed  CAS  Google Scholar 

  • Amunts K, Malicovic A, Mohlberg H, Schormann T, Zilles K (2000) Brodmann’s areas 17 and 18 brought into stereotactic space—where and how variable? Neuroimage 11:66–84

    Article  PubMed  CAS  Google Scholar 

  • Amunts K, Schleicher A, Zilles K (2002) Architectonic mapping of the human cerebral cortex. In: Schüz A, Miller R (eds) Cortical areas: unity and diversity. Taylor & Francis, New York, NY, pp 29–52

    Google Scholar 

  • Annese J, Pitiota A, Dinova ID, Toga AW (2004) A myelo-architectonic method for the structural classification of cortical areas. Neuroimage 21:15–26

    Article  PubMed  CAS  Google Scholar 

  • Artacho-Perula E, Arbizu J, Arroyo-Jimenez M del M, Marcos P, Martinez-Marcos A, Blaizot X, Insausti R (2004) Quantitative estimation of the primary auditory cortex in human brains. Brain Res 1008:20–28

    Article  PubMed  CAS  Google Scholar 

  • Bok ST, van Kip MJE (1939) The size of the body and the size and the number of the nerve cells in the cerebral cortex. Acta Ned Morphol 3:1–22

    Google Scholar 

  • Bortz J (1999) Statistik für Sozialwissenschaftler. Springer, Berlin Heidelberg New York

    Google Scholar 

  • Brodmann K (1909) Vergleichende Lokalisationslehre der Großhirnrinde in ihren Prinzipien dargestellt auf Grund des Zellenbaues. J.A. Barth, Leipzig

    Google Scholar 

  • Burwell RD (2001) Borders and cytoarchitecture of the perirhinal and postrhinal cortices in the rat. J Comp Neurol 437:17–41

    Article  PubMed  CAS  Google Scholar 

  • Crum WR, Griffin LD, Hill DL, Hawkes DJ (2003) Zen and the art of medical image registration: correspondence, homology, and quality. Neuroimage 20:1425–1437

    Article  PubMed  CAS  Google Scholar 

  • de Vos K, Pool CW, Sanz-Arigita EJ, Uylings HBM (2004) Curvature effects in observer independent cytoarchitectonic mapping of the human cerebral cortex. Proceedings of the Second Vogt–Brodmann Symposium, Research Center Jülich, Germany, p 44

  • Dixon WJ, Brown MB, Engelman L, Hill MA, Jennrich RI (1988) BMDP Statistical Software Manual. University of California Press, Berkley, CA

    Google Scholar 

  • Eickhoff S, Geyer S, Amunts K, Mohlberg H, Zilles K (2002) Cytoarchitectonic analysis and stereotaxic map of the human secondary somatosensory cortex region. Neuroimage 16(S1):1780

    Google Scholar 

  • Eickhoff S, Schleicher A, Zilles K, Amunts K (2003) Automated exploratory delineation and analysis of cortical areas. Program No. 863.4. Society for Neuroscience, Washington, DC (Online)

  • Eickhoff S, Walters N, Schleicher A, Egan G, Watson J, Zilles K, Amunts K (2004) High resolution MR imaging reveals microstructural features of the cerebral cortex. Hum Brain Mapp 24:206–215

    Article  Google Scholar 

  • Fatterpekar GM, Naidich TP, Delman BN, Aguinaldo JG, Gultekin H, Sherwood CC, Hof R, Drayer BP, Fayad ZA (2002) Cytoarchitecture of the human cerebral cortex: MR microscopy of excised specimens at 9.4 Tesla. AJNR Am J Neuroradiol 23:1313–1321

    PubMed  Google Scholar 

  • Geyer S, Ledberg A, Schleicher A, Kinomura S, Schormann T, Bürgel U, Larsson J, Zilles K, Roland PE (1996) Two different areas within the primary motor cortex of man. Nature 382:805–807

    Article  PubMed  CAS  Google Scholar 

  • Geyer S, Schleicher A, Zilles K (1999) Areas 3a, 3b, and 1 of human primary somatosensory cortex. 1. Microstructural organization and interindividual variability. Neuroimage 10:63–83

    Article  PubMed  CAS  Google Scholar 

  • Gower JC (1985) Measures of similarity, dissimilarity, and distance. In: Kotz S, Johnson NL (eds) Encyclopaedia of statistical sciences, vol 5. Wiley, New York

  • Grefkes C, Geyer S, Schormann T, Roland P, Zilles K (2001) Human somatosensory area 2: observer-independent cytoarchitectonic mapping, interindividual variability, and population map. Neuroimage 14:617–631

    Article  PubMed  CAS  Google Scholar 

  • Hackett TA, Preuss TM, Kaas JH (2001) Architectonic identification of the core region in auditory cortex of macaques, chimpanzees, and humans. J Comp Neurol 441:197–222

    Article  PubMed  CAS  Google Scholar 

  • Hopf A (1966) Über eine Methode zur objektiven Registrierung der Myeloarchitektonik der Hirnrinde. J Hirnforsch 8:302–313

    Google Scholar 

  • Hopf A (1968a) Registration of the myeloarchitecture of the human frontal lobe with an extinction method. J Hirnforsch 10:259–269

    CAS  Google Scholar 

  • Hopf A (1968b) Photometric studies on the myeloarchitecture of the human temporal lobe. J Hirnforsch 10:285–297

    CAS  Google Scholar 

  • Hudspeth AJ, Ruark JE, Kelly JP (1976) Cytoarchitectonic mapping by microdensitometry. Proc Natl Acad Sci USA 73:2928–2931

    Article  PubMed  CAS  Google Scholar 

  • Jones SE, Buchbinder BR, Aharon I (2000) Three-dimensional mapping of cortical thickness using Laplace’s equation. Hum Brain Mapp 11:12–32

    Article  PubMed  CAS  Google Scholar 

  • Kruggel F, Bruckner MK, Arendt T, Wiggins CJ, von Cramon DY (2003) Analyzing the neocortical fine-structure. Med Image Anal 7:251–264

    Article  PubMed  CAS  Google Scholar 

  • Lidow MS, Goldman-Rakic PS, Rakic P, Gallager DW (1988) Differential quenching and limits of resolution in autoradiograms of brain tissue labelled with 3H-, 125I- and 14C-compounds. Brain Res 459:105–119

    Article  PubMed  CAS  Google Scholar 

  • Merker B (1983) Silver staining of cell bodies by means of physical development. J Neurosci Methods 9:235–241

    Article  PubMed  CAS  Google Scholar 

  • Morecraft RJ, Cipolloni PB, Stilwell-Morecraft KS, Gedney MT, Pandya DN (2004) Cytoarchitecture and cortical connections of the posterior cingulate and adjacent somatosensory fields in the rhesus monkey. J Comp Neurol 469:37–69

    Article  PubMed  CAS  Google Scholar 

  • Morosan P, Rademacher J, Schleicher A, Amunts K, Schormann T, Zilles K (2001) Human primary auditory cortex: cytoarchitectonic subdivisions and mapping into a spatial reference system. Neuroimage 13:684–701

    Article  PubMed  CAS  Google Scholar 

  • Morosan P, Palomero-Gallagher N, Rademacher J, Schleicher A, Mohlberg H, Amunts K, Zilles K (2004a) Cyto- and receptor architecture of human auditory cortex. Proceedings of the Second Vogt–Brodmann Symposium, the converge of structure and function, Jülich, p 31

  • Morosan P, Schleicher A, Amunts K, Zilles K (2004b) Multimodal architectonic mapping of human superior temporal gyrus. Anat Embryol (this issue)

  • Mountcastle VB (1978) An organizing principle for cerebral function: the unit module and the distributed system. In: Edelmann GM, Mountcastle VB (eds) The mindful brain: cortical organization and the group-selective theory of higher brain function. MIT Press, Cambridge, pp 7–51

    Google Scholar 

  • Ramm P, Kulick JH, Stryker MP, Frost BJ (1984) Video and scanning microdensitometer-based imaging systems in autoradiographic video densitometry. J Neurosci Methods 11:89–100

    Article  PubMed  CAS  Google Scholar 

  • Roland PE, Zilles K (1994) Brain atlases—a new research tool. TINS 17:458–467

    PubMed  CAS  Google Scholar 

  • Sanz-Arigita EJ, de Vos K, Pool CW, Uylings HBM (2002) Multivariate quantitative cytoarchitectonics. Laminar characterization of cortical microstructure by cell-type selection. Neuroimage 16(2 Suppl 1)

  • Sanz-Arigita EJ, de Vos K, Pool CW, Uylings HBM (2004) Multivariate quantitative analysis of the microstructure of the cingulate cortex—areas 24 of Brodmann. Abstracts of the Second Vogt–Brodmann Symposium, the converge of structure and function, Jülich, p 44

  • Schleicher A, Zilles K (1990) A quantitative approach to cytoarchitectonics: analysis of structural inhomogeneities in nervous tissue using an image analyser. J Microsc 157:367–381

    PubMed  CAS  Google Scholar 

  • Schleicher A, Ritzdorf H, Zilles K (1987) Erster Ansatz zur objektiven Lokalisation von Arealgrenzen im Cortex cerebri. Verh Anat Ges 81:867–868

    Google Scholar 

  • Schleicher A, Amunts K, Geyer S, Morosan P, Zilles K (1999) Observer-independent method for microstructural parcellation of cerebral cortex: a quantitative approach to cytoarchitectonics. Neuroimage 9:165–177

    Article  PubMed  CAS  Google Scholar 

  • Schleicher A, Amunts K, Geyer S, Kowalski T, Schormann T, Palomero-Gallagher N, Zilles K (2000) A stereological approach to human cortical architecture: identification and delineation of cortical areas. J Chem Neuroanat 20:31–47

    Article  PubMed  CAS  Google Scholar 

  • Schmitt O, Böhme M (2002) A robust transcortical profile scanner for generating 2-d traverses in histological sections of richly curved cortical courses. Neuroimage 16:1103–1119

    Article  PubMed  CAS  Google Scholar 

  • Schmitt O, Hömke L, Dümbgen L (2003) Detection of cortical transition regions utilizing statistical analyses of excess masses. Neuroimage 19:42–63

    PubMed  Google Scholar 

  • Schmitt O, Pakura M, Aach T, Hömke L, Böhme M, Bock S, Preusse S (2004) Analysis of nerve fibres and their distribution in histological sections of the human brain. Microsc Res Tech 63:220–243

    Article  PubMed  CAS  Google Scholar 

  • Sherwood CC, Broadfield DC, Holloway RL, Gannon PJ, Hof PR (2003) Variability of Broca’s area homologue in African great apes: implications for language evolution. Anat Rec 271A:276–285

    Article  Google Scholar 

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

    Google Scholar 

  • Timm NH (2002) Applied multivariate analysis. Springer, Berlin Heidelberg New York

    Google Scholar 

  • Vogt C, Vogt O (1919) Allgemeinere Ergebnisse unserer Hirnforschung. J Psychol Neurol 25:279–461

    Google Scholar 

  • von Economo K, Koscinas G (1925) Die Cytoarchitektonic der Hirnrinde des erwachsenen Menschen. Springer, Wien

    Google Scholar 

  • Walters NB, Egan GF, Kril JJ, Kean M, Waley P, Jenkinson M, Watson JD (2003) In vivo identification of human cortical areas using high-resolution MRI: an approach to cerebral structure–function correlation. Proc Natl Acad Sci USA 100:2981–2986 (Epub 2003 Feb 24)

    Google Scholar 

  • Walters B, Eickhoff S, Schleicher A, Zilles K, Egan GF, Amunts K, Watson JDG (submitted) Observer independent analysis of high-resolution MR images of the human cerebral cortex: in vivo delineation of cortical areas

  • Wree A, Schleicher A, Zilles K (1982) Estimation of volume fractions in nervous tissue with an image analyzer. J Neurosci Methods 6:29–43

    Article  PubMed  CAS  Google Scholar 

  • Zilles K, Palomero-Gallagher N (2001) Cyto-, myelo-, and receptor architectonics of the human parietal cortex. Neuroimage 14:8–20

    Article  Google Scholar 

  • Zilles K, Schlaug G, Matelli M, Luppino G, Schleicher A, Qü M, Dabringhaus A, Seitz R, Roland PE (1995) Mapping of human and macaque sensorimotor areas by integrating architectonic, transmitter receptor, MRI and PET data. J Anat 187:515–537

    PubMed  CAS  Google Scholar 

  • Zilles K, Schleicher A, Palomero-Gallagher N, Amunts K (2002a) Quantitative analysis of cyto- and receptor architecture of the Human brain. In: Toga AW, Maziotta JC (eds) Brain mapping: the methods, 2nd edn. Academic, Amsterdam, pp 573–602

    Google Scholar 

  • Zilles K, Palomero-Gallagher N, Grefkes C, Scheperjans F, Boy C, Amunts K, Schleicher A (2002b) Architectonics of the human cerebral cortex and transmitter receptor fingerprints: reconciling functional neuroanatomy and neurochemistry. Eur Neuropsychopharmacol 12:587–599

    Article  CAS  Google Scholar 

  • Zilles K, Eickhoff S, Palomero-Gallagher N (2003) The human parietal cortex: a novel approach to its architectonic mapping. Adv Neurol 93:1–21

    PubMed  Google Scholar 

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Acknowledgements

The study was supported by the Brain Imaging Center West (BMBF 01GO0204). The Human Brain Project/Neuroinformatics research is funded by the National Institute of Biomedical Imaging and Bioengineering, the National Institute of Neurological Disorders and Stroke, and the National Institute of Mental Health.

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Schleicher, A., Palomero-Gallagher, N., Morosan, P. et al. Quantitative architectural analysis: a new approach to cortical mapping. Anat Embryol 210, 373–386 (2005). https://doi.org/10.1007/s00429-005-0028-2

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