Susanna Narkilahti
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Articles (8)
Year:
2024
Year:
2022
Year:
2022
To obtain commensurate numerical data of neuronal network morphology in vitro, network analysis needs to follow consistent guidelines. Important factors in successful analysis are sample uniformity, suitability of the analysis method for extracting relevant data and the use of established metrics. However, for the analysis of 3D neuronal cultures, there is little coherence in the analysis methods and metrics used in different studies. Here, we present a framework for the analysis of neuronal networks in 3D. First, we selected a hydrogel that supported the growth of human pluripotent stem cell-derived cortical neurons. Second, we tested and compared two software programs for tracing multi-neuron images in three dimensions and optimized a workflow for neuronal analysis using software that was considered highly suitable for this purpose. Third, as a proof of concept, we exposed 3D neuronal networks to oxygen-glucose deprivation- and ionomycin-induced damage and showed morphological differences between the damaged networks and control samples utilizing the proposed analysis workflow. With the optimized workflow, we present a protocol for preparing, challenging, imaging and analysing 3D human neuronal cultures.
Year:
2022
Year:
2022
Year:
2021
Year:
2021
Year:
2020
Collaborators (6)
Pasi Kallio
University of Tampere
Andrey Vinogradov
Tampere University
emre kapucu
University of Tampere
Lassi Sukki
University of Tampere
L. Ylä-Outinen
University of Jyväskylä
Tanja Hyvärinen
University of Tampere
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