Observer-independent method for microstructural parcellation of cerebral cortex: a quantitative approach to cytoarchitectonics.
Abstract
We describe a new, observer-independent procedure for identifying boundaries between cortical areas. The method is useful for images obtained from sections which provide microstructural information on the cortical laminar pattern, e.g., Nissl-, myelin-, or immunohistochemically stained sections or receptor autoradiographs. The laminar pattern is represented by profile curves extending from the cortical surface to the white matter boundary. These profiles are constructed from digitized images. Digitization is based on the grey level index (Nissl) or densitometry (myelin, immunohistochemistry, receptor autoradiography). The shapes of neighboring profiles are compared by calculating their distances according to feature vectors extracted from the profiles. Profiles derived from a homogeneous area can be expected to be similar in shape and hence show low distance values between each other. Maximum distances can be found between profiles which lie on opposite sides of a structural boundary. The Mahalanobis distance was found to be more sensitive and to yield greater spatial resolution than other distance measures such as the Euclidean distance. Cell-stained sections of the human neocortex were analyzed. The method not only verified boundaries which had been defined by visual inspection, it also revealed new ones which had not been detected visually. The procedure offers an important supplement to the traditional methods based on visual inspection which, for the first time, is based on quantitative data and therefore offers a new level of reproducibility and observer independence. Anatomical atlases based on this procedure thus provide a new tool for the interpretation of structural data obtained from functional imaging techniques.
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The borders of the new areas were proven by significant changes in the laminar patterns of cyto- and receptorarchitecture using an algorithm-based method for the detection of borders.
“Their borders were proven by significant changes in the laminar patterns of cyto- and receptorarchitecture using an algorithm-based method for the detection of borders [39].”
From Broca's Region: Novel Organizational Principles and Multiple Receptor Mapping (2010) · cites this paper as [39]
Borders between cortical areas were identified in the receptor autoradiographs as well as in the cell body-stained sections using an algorithm-based approach and multivariate statistical analysis.
“Borders between cortical areas were identified in the receptor autoradiographs as well as in the cell body–stained sections using an algorithm-based approach and multivariate statistical analysis [39].”
From Broca's Region: Novel Organizational Principles and Multiple Receptor Mapping (2010) · cites this paper as [39]
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Self-citation
- Authors
- Schleicher, A., Amunts, K., Geyer, S., Morosan, P., & Zilles, K.
- Affiliations
- Heinrich Heine University Düsseldorf (DE)
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 1999-01
- Volume
- 9
- Issue
- 1
- Pages
- 165-177
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W1973000876
- Cited by
- 353
- References
- 48
- Citations by year
- 2026: 3 · 2025: 6 · 2024: 15 · 2023: 12 · 2022: 10 · 2021: 15 · 2020: 10 · 2019: 6 · 2018: 14 · 2017: 7 · 2016: 8 · 2015: 16 · 2014: 8 · 2013: 15 · 2012: 11
- FWCI
- 22.21
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Max Planck Digital Library (submittedVersion)
- JuSER (Forschungszentrum Jülich) (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Cell Image Analysis Techniques
- Keywords
- cortical parcellation, cytoarchitecture, profile curves, Mahalanobis distance, observer independence, Nissl staining, myelin staining, immunohistochemistry, receptor autoradiography, feature vectors, anatomical atlas, human neocortex
- MeSH terms
- Brain Mapping, Cerebral Cortex, Computer Simulation, Histological Techniques, Humans, Image Processing, Computer-Assisted, Neurons, Occipital Lobe, Temporal Lobe, Visual Cortex, Reproducibility of Results, Observer Variation
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