Branching morphology determines signal propagation dynamics in neurons.

ABSTRACT: Computational modeling of signal propagation in neurons is critical to our understanding of basic principles underlying brain organization and activity. Exploring these models is used to address basic neuroscience questions as well as to gain insights for clinical applications. The seminal Hodgkin Huxley model is a common theoretical framework to study brain activity. It was mainly used to investigate the electrochemical and physical properties of neurons. The influence of neuronal structure on activity patterns was explored, however, the rich dynamics observed in neurons with different morphologies is not yet fully understood. Here, we study signal propagation in fundamental building blocks of neuronal branching trees, unbranched and branched axons. We show how these simple axonal element

SUBMITTER: Ofer N 

PROVIDER: S-EPMC5567046 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature