Susanna Narkilahti

University of Tampere
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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

FINLAND
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Andrey Vinogradov

Tampere University

FINLAND
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emre kapucu

University of Tampere

FINLAND
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Lassi Sukki

University of Tampere

FINLAND
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L. Ylä-Outinen

University of Jyväskylä

FINLAND
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Tanja Hyvärinen

University of Tampere

FINLAND
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