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Unveiling the functional connectivity of astrocytic networks with AstroNet, a graph reconstruction algorithm coupled to image processing

2025/01/24 by Lou Zonca, Félix Bellier, Giampaolo Milior +5 · 1 voice · 1 citation
Neuroscience · #Neural dynamics and brain function #Neuroinflammation and Neurodegeneration Mechanisms #Neuroscience and Neuropharmacology Research

paper · pdf · doi:10.1038/s42003-024-07390-0

openalex publication_date 2025/01/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/31

Abstract

Astrocytes form extensive networks with diverse calcium activity, yet the organization and connectivity of these networks across brain regions remain largely unknown. To address this, we developed AstroNet, a data-driven algorithm that uses two-photon calcium imaging to map temporal correlations in astrocyte activation. By organizing individual astrocyte activation events chronologically, our method reconstructs functional networks and extracts local astrocyte correlations. We create a graph of the astrocyte network by tallying direct co-activations between pairs of cells along these activation pathways. Applied to the CA1 hippocampus and motor cortex, AstroNet reveals notable differences: astrocytes in the hippocampus display stronger connectivity, while cortical astrocytes form sparser networks. In both regions, smaller, tightly connected sub-networks are embedded within a larger, loosely connected structure. This method not only identifies astrocyte activation paths and connectivity but also reveals distinct, region-specific network patterns, providing new insights into the functional organization of astrocytic networks in the brain. AstroNet, a novel data-driven algorithm, maps astrocytic network connectivity through calcium imaging, revealing distinct connectivity patterns in the hippocampus and motor cortex, and providing insights into astrocyte network organization across brain regions.

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