Economo-Koskinas cytoarchitectonics¶
This page contains descriptions and examples to stratify and visualize surface-based findings according to cyatoarchitectural variation.
Economo-Koskinas stratification¶
As part of the ENIGMA TOOLBOX, we included a digitized parcellation of von Economo and Koskina’s cytoarchitectonic mapping of the human cerebral cortex, from which five different structural types of cerebral cortex can be described: i) agranular (purple; thick with large cells but sparse layers II and IV), ii) frontal (blue; thick but not rich in cellular substance, visible layers II and IV), iii) parietal (green; thick and rich in cells with dense layers II and IV but small and slender pyramidal cells), iv) polar (orange; thin but rich in cells, particularly in granular layers), and v) granular or koniocortex (yellow; thin but rich in smalls cells, even in layer IV, and a rarified layer V).
In the following example, we contextualized disease-related cortical atrophy patterns with respect to the well-established von Economo and Koskinas cytoarchitectonic atlas by summarizing cortex-wide effects across each of the five structural types of isocortex. To ease interpretation, stratification of findings based on the von Economo and Koskinas atlas are also visualized in a spider plot. Here, negative values (towards the center) represent greater atrophy in disease cases relative to healthy controls.
Prerequisites ↪ Load summary statistics or example data ↪ Z-score data (mega only)
>>> from enigmatoolbox.histology import economo_koskinas_spider
>>> # Stratify cortical atrophy based on Economo-Koskinas classes
>>> class_mean = economo_koskinas_spider(CT_d, axis_range=(-0.4, 0))
% Stratify cortical atrophy based on Economo-Koskinas classes
class_mean = economo_koskinas_spider(CT_d, 'axis_range', [-0.4 0])
>>> from enigmatoolbox.histology import economo_koskinas_spider
>>> # Stratify cortical atrophy based on Economo-Koskinas classes
>>> class_mean = economo_koskinas_spider(CT_z_mean, axis_range=(-1, 0))
% Stratify cortical atrophy based on Economo-Koskinas classes
class_mean = economo_koskinas_spider(CT_z_mean{:, :}, 'axis_range', [-1 0])
