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JOURNALS // Computer Research and Modeling // Archive

Computer Research and Modeling, 2025 Volume 17, Issue 3, Pages 465–481 (Mi crm1280)

This article is cited in 1 paper

ANALYSIS AND MODELING OF COMPLEX LIVING SYSTEMS

Modelling of astrocyte morphology with space colonization algorithm

A. N. Kriuchechnikovaa, T. G. Levdika, A. R. Brazheba

a Department of Molecular Neurobiology, Shemyakin – Ovchinnikov Institute of Bioorganic Chemistry of the Russian Academy of Sciences, 16/10 Miklukho-Maklaya st., GSP-7, Moscow, Russia
b Department of Biophysics, Biological Faculty, Lomonosov Moscow State University, 1/24 Leninskie Gory, Moscow, 119234, Russia

Abstract: We examine a phenomenological algorithm for generating morphology of astrocytes, a major class of glial brain cells, based on morphometric data of rat brain protoplasmic astrocytes and observations of general cell development trends in vivo, based on current literature. We adapted the Space Colonization Algorithm (SCA) for procedural generation of astrocytic morphology from scratch. Attractor points used in generation were spatially distributed in the model volume according to the synapse distribution density in the rat hippocampus tissue during the first week of postnatal brain development. We analyzed and compared astrocytic morphology reconstructions at different brain development stages using morphometry estimation techniques such as Sholl analysis, number of bifurcations, number of terminals, total tree length, and maximum branching order. Using morphometric data from protoplasmic astrocytes of rats at different ages, we selected the necessary generation parameters to obtain the most realistic three-dimensional cell morphology models. We demonstrate that our proposed algorithm allows not only to obtain individual cell geometry but also recreate the phenomenon of tiling domain organization in the cell populations. In our algorithm tiling emerges due to the cell competition for territory and the assignment of unique attractor points to their processes, which then become unavailable to other cells and their processes. We further extend the original algorithm by splitting morphology generation in two phases, thereby simulating astrocyte tree structure development during the first and third-fourth weeks of rat postnatal brain development: rapid space exploration at the first stage and extensive branching at the second stage. To this end, we introduce two attractor types to separate two different growth strategies in time. We hypothesize that the extended algorithm with dynamic attractor generation can explain the formation process of fine astrocyte cell structures and maturation of astrocytic arborizations.

Keywords: glia, astrocyte, computational modeling, morphology

UDC: 519.8

Received: 23.11.2024
Accepted: 03.12.2024

DOI: 10.20537/2076-7633-2025-17-3-465-481



© Steklov Math. Inst. of RAS, 2026