# Dimensionality reduction of neuronal degeneracy reveals two interfering physiological mechanisms

arXiv: https://arxiv.org/abs/2405.02038 · HTML: https://mlsanity.com/paper/2405.02038/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 May 2024.

## Built on by (most cited first, 2 of 2)

- [Fast reconstruction of degenerate populations of conductance-based neuron models from spike times](https://mlsanity.com/paper/2509.12783/) (2025)
- [Diffusion learning reveals viable parameter manifolds and compensation geometry in biological dynamical systems](https://mlsanity.com/paper/2607.03671/) (2026)

## Abstract (arXiv)

Neuronal systems maintain stable functions despite large variability in their physiological components. Ion channel expression, in particular, is highly variable in neurons exhibiting similar electrophysiological phenotypes, which poses questions regarding how specific ion channel subsets reliably shape neuron intrinsic properties. Here, we use detailed conductance-based modeling to explore the origin of stable neuronal function from variable channel composition. Using dimensionality reduction, we uncover two principal dimensions in the channel conductance space that capture most of the variance of the observed variability. Those two dimensions correspond to two physiologically relevant sources of variability that can be explained by feedback mechanisms underlying regulation of neuronal activity, providing quantitative insights into how channel composition links to neuronal electrophysiological activity. These insights allowed us to understand and design a model-independent, reliable neuromodulation rule for variable neuronal populations.