Higher-Order Interactions in Neuronal Function: From Genes to Ionic Currents in Biophysical Models
Neuronal firing patterns are the consequence of precise varia- tions in neuronal membrane potential, which are themselves shaped by multiple ionic currents. In this study, we use bio- physical models, statistical methods, and information theory to explore the interaction between these ionic currents and neuron electrophysiological phenotype. We created numerous electrical models with diverse firing patterns using Monte Carlo Markov Chain methods. By analyzing these models, we identified intricate relationships between model parameters and electrical features. Our findings show that neuronal features are often influenced by multiple ionic currents sharing synergistic relationships. We also applied our methods to single-cell RNAseq data, discovering gene expression modules specific to certain interneuron types. This research sheds light on the complex links between biophysical parameters and neuronal phenotypes.