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Rossini, P.M., DiLorio, R., Bentivoglio, M., Bertini, G., et al. (2019) Methods for Analysis of Human Brain Connectivity: An IFCN-Sponsored Review. Clinical Neurophysiology, 130, 1833-1858.
https://doi.org/10.1016/j.clinph.2019.06.006

has been cited by the following article:

• TITLE: Adaptation to Fluctuating Neuronal Signal Traffic for Brain Connectivity

  AUTHORS: Gerhard Werner, Bernhard J. Mitterauer

  KEYWORDS: Brain Connectivity, White Matter, Neuronal Groups, Gap Junctions

  JOURNAL NAME: Advances in Bioscience and Biotechnology, Vol.14 No.5, May 12, 2023

  ABSTRACT: Brain connectivity is commonly studied in terms of causal interaction or statistical dependency between brain regions. In this analysis paper, we draw attention to the constraining effect the dynamics of fiber tract connections may impose on neuronal signal traffic. We propose a model developed by Copelli and Kinouchi (l.c.) for a different purpose to safeguard signal transmission for brain connectivity by ensuring dynamic adaptation of signal reception to a wide frequency range of traffic flow over connecting fiber tracts. Gap junction connectivity would confer to neuronal groups the capacity of acting as collectives for dynamical adaptability to impinging neural traffic thereby forestalling traffic congestion and overload. It is suggested that applying this model to signal reception in brain connectivity would deliver the required functionality as a collective achievement of the interrelations between neurons and gap junctions, the latter regulated by glia.