Theory of spike initiation, sensory systems, autonomous behavior, epistemology
Editor Romain Brette
Ionic current correlations are ubiquitous across phyla (2017)
Trinh Tran, Cagri T. Unal, Laszlo Zaborszky, Horacio G. Rotstein, Alfredo Kirkwood, Jorge P. Golowasch
This is a short paper showing that in mice, a number of ionic conductances vary across cells in a correlated way. This is shown in particular in hippocampal granule cells, which are very compact (important to interpret the results because of space clamp issues). This phenomenon had been previously demonstrated in invertebrates; other work had shown that the voltage-dependence of different channels is also correlated (McAnelly & Zakon, 2000). Another interesting finding is that conductances vary with the circadian rhythm.
The co-variation of conductances has important consequences in terms of modeling. It means in particular that conductances are not genetically set, they are plastic as virtually everything in the cell. The fact that they co-vary, rather than vary independently, suggest that this may not be a random variation, or more precisely that there is some regulation that ensures that the parameters “make sense”, that is, produce a functional cell. For example, in an isopotential cell, the electrophysiological properties vary moderately if all conductances are scaled by the same number (ie you get similar spikes, but possibly a different excitability threshold). This kind of scaling could result from global homeostatic regulation, for example (see e.g. O’Leary et al. (2014) and other work from Marder’s lab). The data in this paper, however, suggest that the regulation of conductances is more complex than a global scaling. Some conductance pairs are not correlated. In other cases, the linear regression has a positive intercept – so the relation is not linear but affine. Generally, there is also a fair amount of variability around the linear regression, which might be noise of various sources, but which might also be simply the signature of a more complex multidimensional dependence (linear or nonlinear).
(By the way, in case the authors read this comment, the caption of Fig. 2 is incomplete on this version.)