@article {DrionENEURO.0031-14.2015, author = {Guillaume Drion and Alessio Franci and Julie Dethier and Rodolphe Sepulchre}, title = {Dynamic Input Conductances Shape Neuronal Spiking}, elocation-id = {ENEURO.0031-14.2015}, year = {2015}, doi = {10.1523/ENEURO.0031-14.2015}, publisher = {Society for Neuroscience}, abstract = {Assessing the role of biophysical parameter variations in neuronal activity is critical to the understanding of modulation, robustness and homeostasis of neuronal signaling. The paper proposes that this question can be addressed through the analysis of dynamic input conductances. Those voltage-dependent curves aggregate the concomitant activity of all ion channels in distinct timescales. They are shown to shape the current-voltage dynamical relationships that determine neuronal spiking. We propose an experimental protocol to measure dynamic input conductances in neurons. In addition, we provide a computational method to extract dynamic input conductances from arbitrary conductance-based models and to analyze their sensitivity to arbitrary parameters. We illustrate the relevance of the proposed approach for modulation, compensation and robustness studies in a published neuron model based on data of the stomatogastric ganglion of the crab Cancer borealis. Significance statement: Reliable neuron activity is ensured by a tight regulation of the ion channels that resides in the neuron{\textquoteright}s membrane. Understanding the causal mechanisms that relate this regulation to physiological and pathological neuronal activity is a necessary step for developing efficient therapies for neurological diseases associated with abnormal nervous system activity. Our paper provides a novel methodological framework to quantify the sensitivity of neuronal activity to changes in ion channel densities. This framework, which is general and can be applied to any neuron type, has the potential to improve our understanding of the regulation of brain functions and to help in the design of new pharmacological treatments.}, URL = {https://www.eneuro.org/content/early/2015/01/30/ENEURO.0031-14.2015}, eprint = {https://www.eneuro.org/content/early/2015/01/30/ENEURO.0031-14.2015.full.pdf}, journal = {eNeuro} }