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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/22817

Title: Image Informatics Strategies for Deciphering Neuronal Network Connectivity
Authors: Detrez, Jan R.
Verstraelen, Peter
Gebuis, Titia
Verschuuren, Marlies
Kuijlaars, Jacobine
Langlois, Xavier
Nuydens, Rony
Timmermans, Jean-Pierre
De Vos, Winnok H.
Issue Date: 2016
Citation: Advances in Anatomy Embryology and Cell Biology, 219, p. 123-148
Abstract: Brain function relies on an intricate network of highly dynamic neuronal connections that rewires dramatically under the impulse of various external cues and pathological conditions. Amongst the neuronal structures that show morphological plasticity are neurites, synapses, dendritic spines and even nuclei. This structural remodelling is directly connected with functional changes such as intercellular communication and the associated calcium bursting behaviour. In vitro cultured neuronal networks are valuable models for studying these morpho-functional changes. Owing to the automation and standardization of both image acquisition and image analysis, it has become possible to extract statistically relevant readouts from such networks. Here, we focus on the current state-of-the-art in image informatics that enables quantitative microscopic interrogation of neuronal networks. We describe the major correlates of neuronal connectivity and present workflows for analysing them. Finally, we provide an outlook on the challenges that remain to be addressed, and discuss how imaging algorithms can be extended beyond in vitro imaging studies.
URI: http://hdl.handle.net/1942/22817
DOI: 10.1007/978-3-319-28549-8_5
ISI #: 000385738300006
ISSN: 0301-5556
Category: A1
Type: Journal Contribution
Validation: ecoom, 2017
Appears in Collections: Research publications

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