Optimizing criterion for the upper limit of the signal response of brain neurons

Islam M. Elbaz, Mohamed A. Sohaly and Hamdy A. El-Metwally

Mathematical Population Studies, 2024, vol. 31, issue 2, 87-104

Abstract: In a model of signal transmission between brain neurons, the Lyapunov functions associated with the “no signal” solution are positive and have a negative derivative with respect to the response. The solution is stable for a response range. Noise added to signal transmission and response enhances stability by allowing the system to escape tricky equilibria. It amplifies weak signals, improves detection and distinction of significant signals from background noise, and generates appropriate and adaptive responses to detected signals. It causes random fluctuations, allowing more parameter values to be tried out and thus optimizing the behavior of the system, enabling it to transmit and respond effectively to signals in the presence of the variability inherent in biological networks. The deterministic model is thus enhanced by its stochastic extension.

Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/08898480.2023.2264662 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:mpopst:v:31:y:2024:i:2:p:87-104

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/GMPS20

DOI: 10.1080/08898480.2023.2264662

Access Statistics for this article

Mathematical Population Studies is currently edited by Prof. Noel Bonneuil, Annick Lesne, Tomasz Zadlo, Malay Ghosh and Ezio Venturino

More articles in Mathematical Population Studies from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().