Epigenetics and Bruxism: from Hyper-Narrative Neural Networks to Hyper-Function
Biosemiotics, ISSN: 1875-1350, Vol: 13, Issue: 2, Page: 241-259
2020
- 4Captures
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
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.
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.
Metrics Details
- Captures4
- Readers4
Article Description
This article develops a biosemiotic ´hyper-narrative model´ for the purposes of investigating emergent motor behaviors. It proposes to understand such behaviors in terms of the following associations: the organization of information acquired from the environment, focusing on narrative; the organizational dynamics of epigenetic mechanisms that underly the neural processes facilitating the processing of information; and the evolution of emergent motor behaviors that enable the informational acquisition. The article describes and explains these associations as part of a multi-ordered and multi-causal generative principle of biological phenotype emergence that supersedes the theory of the arbitrary coding of life. Preceeding from narrative’s operations in a biological dimension, the article presents scientific research dealing with the associations of action-oriented organization of narrative information and underlying psychological and physiological dynamics and depicts the relations with a distributed multi-directional mapping dynamic. The article presents the explanatory implications of such a hyper-narrative dynamic model on an example of emergent motor behaviors – bruxism. Central to this discussion is the exploration of the possible mechanisms of emergence and etiopathogenesis of bruxism, based on its neurobiology. The article takes the perspective that complex systems dynamics themselves with a tendency to narrative form are found not to be underlain merely by arbitrary coded mechanisms but, rather, biological neural networks (e.g. neuro-epigenetic network) that render context-dependent bio-informational mapping analogous to that of the narrative possible.
Bibliographic Details
Springer Science and Business Media LLC
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know