Štajduhar, Andrija; Lipić, Tomislav; Lončarić, Sven; Judaš, Miloš; Sedmak, Goran (2023) Interpretable machine learning approach for neuron-centric analysis of human cortical cytoarchitecture. Scientific Reports, 13 . ISSN 2045-2322
|
PDF
- Published Version
- article
Available under License Creative Commons Attribution. Download (2MB) |
Abstract
The complexity of the cerebral cortex underlies its function and distinguishes us as humans. Here, we present a principled veridical data science methodology for quantitative histology that shifts focus from image-level investigations towards neuron-level representations of cortical regions, with the neurons in the image as a subject of study, rather than pixel-wise image content. Our methodology relies on the automatic segmentation of neurons across whole histological sections and an extensive set of engineered features, which reflect the neuronal phenotype of individual neurons and the properties of neurons’ neighborhoods. The neuron-level representations are used in an interpretable machine learning pipeline for mapping the phenotype to cortical layers. To validate our approach, we created a unique dataset of cortical layers manually annotated by three experts in neuroanatomy and histology. The presented methodology offers high interpretability of the results, providing a deeper understanding of human cortex organization, which may help formulate new scientific hypotheses, as well as to cope with systematic uncertainty in data and model predictions.
| Item Type: | Article | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Uncontrolled Keywords: | Cerebral-cortex; human brain; search; images | ||||||||||||
| Subjects: | TECHNICAL SCIENCES > Computing BIOMEDICINE AND HEALTHCARE BIOMEDICINE AND HEALTHCARE > Public Health and Health Care |
||||||||||||
| Divisions: | Division of Electronics | ||||||||||||
| Projects: |
|
||||||||||||
| Depositing User: | Josipa Karadžole | ||||||||||||
| Date Deposited: | 14 Apr 2026 12:26 | ||||||||||||
| URI: | https://fulir.irb.hr:/id/eprint/11702 | ||||||||||||
| DOI: | 10.1038/s41598-023-32154-x |
Actions (login required)
![]() |
View Item |




Altmetric
Altmetric



