Chapter title |
Image Informatics Strategies for Deciphering Neuronal Network Connectivity
|
---|---|
Chapter number | 5 |
Book title |
Focus on Bio-Image Informatics
|
Published in |
Advances in anatomy embryology and cell biology, May 2016
|
DOI | 10.1007/978-3-319-28549-8_5 |
Pubmed ID | |
Book ISBNs |
978-3-31-928547-4, 978-3-31-928549-8
|
Authors |
Detrez, Jan R., Verstraelen, Peter, Gebuis, Titia, Verschuuren, Marlies, Kuijlaars, Jacobine, Langlois, Xavier, Nuydens, Rony, Timmermans, Jean-Pierre, De Vos, Winnok H., Jan R. Detrez, Peter Verstraelen, Titia Gebuis, Marlies Verschuuren, Jacobine Kuijlaars, Xavier Langlois, Rony Nuydens, Jean-Pierre Timmermans, Winnok H. De Vos, Detrez, Jan R, De Vos, Winnok |
Editors |
Winnok H. De Vos, Sebastian Munck, Jean-Pierre Timmermans |
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. |
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Belgium | 1 | 50% |
Unknown | 1 | 50% |
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Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
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Unknown | 18 | 100% |
Demographic breakdown
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Researcher | 4 | 22% |
Student > Postgraduate | 2 | 11% |
Professor | 2 | 11% |
Student > Bachelor | 1 | 6% |
Student > Doctoral Student | 1 | 6% |
Other | 5 | 28% |
Unknown | 3 | 17% |
Readers by discipline | Count | As % |
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Neuroscience | 4 | 22% |
Agricultural and Biological Sciences | 3 | 17% |
Medicine and Dentistry | 3 | 17% |
Biochemistry, Genetics and Molecular Biology | 1 | 6% |
Pharmacology, Toxicology and Pharmaceutical Science | 1 | 6% |
Other | 0 | 0% |
Unknown | 6 | 33% |