Neuronal growth via hybrid system of self-growing and diffusion based grammar rules: I
Bulletin of Mathematical Biology, ISSN: 1522-9602, Vol: 57, Issue: 2, Page: 205-227
1995
- 4Citations
- 3Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
The formation of neuronal networks requires axonal growth towards target neutons. A simple set of grammar rules is introduced to describe axonal growth towards target cells situated both at short and long distances from the growing neuron. Growth for short distances is descrbed by growth following the highest gradient of a chemical compound (which is spread by diffusion from the targets). This approach fails to describe long-distance growth, which is addressed by adopting a graph grammar theory for growing trees. With these rules a flexible tool to draw network of neurons by computer can be developed. © 1995 Society for Mathematical Biology.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=0029257514&origin=inward; http://dx.doi.org/10.1007/bf02460616; http://www.ncbi.nlm.nih.gov/pubmed/7703918; http://link.springer.com/10.1007/BF02460616; http://www.springerlink.com/index/pdf/10.1007/BF02460616; http://www.springerlink.com/index/10.1007/BF02460616; https://dx.doi.org/10.1007/bf02460616; https://link.springer.com/article/10.1007/BF02460616
Springer Nature
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