2024/05/03 by Arthur Fyon, Alessio Franci, Fyon, Arthur +5 · 1 citation
Computer Science · Medicine · #Adipose Tissue and Metabolism #Cell Behavior (q-bio.CB) #Computational Drug Discovery Methods #FOS: Biological sciences #FOS: Physical sciences #Mathematical Physics (math-ph) #Neurons and Cognition (q-bio.NC)
paper · pdf · doi:10.48550/arxiv.2405.02038
openalex publication_date 2024/05/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.