Sign in
NeuroscienceeLife
Peer-reviewed journal article

Minimal requirements for a neuron to co-regulate many properties and the implications for ion channel correlations and robustness

Jane YangiD, Husain Shakil, Stéphanie RattéiD, Steven A. PrescottiD

Abstract

Neurons regulate their excitability by adjusting their ion channel levels. Degeneracy - achieving equivalent outcomes (excitability) using different solutions (channel combinations) - facilitates this regulation by enabling a disruptive change in one channel to be offset by compensatory changes in other channels. But neurons must co-regulate many properties. Pleiotropy - the impact of one channel on more than one property - complicates regulation because a compensatory ion channel change that restores one property to its target value often disrupts other properties. How then does a neuron simultaneously regulate multiple properties? Here we demonstrate that of the many channel combinations producing the target value for one property (the single-output solution set), few combinations produce the target value for other properties. Combinations producing the target value for two or more properties (the multi-output solution set) correspond to the intersection between single-output solution sets. Properties can be effectively co-regulated only if the number of adjustable channels (nin) exceeds the number of regulated properties (nout). Ion channel correlations emerge during homeostatic regulation when the dimensionality of solution space (nin - nout) is low. Even if each property can be regulated to its target value when considered in isolation, regulation as a whole fails if single-output solution sets do not intersect. Our results also highlight that ion channels must be co-adjusted with different ratios to regulate different properties, which suggests that each error signal drives modulatory changes independently, despite those changes ultimately affecting the same ion channels.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers
Citations
41
FWCI
2.94
Field percentile
top 7%

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISGorur-Shand '19Mondal '25Schneider '23Tran '19Mondal '26Mishra '21
67% semantic matchNeuroscience
Srinivas Gorur-Shandilya, Eve E. Marder, Timothy O’Leary·bioRxiv·Sep 2, 2019· 1 citations