NEMar 23, 2015
Study of all the periods of a Neuronal Recurrence Equation
arXiv:1503.06866v42.1
Originality Synthesis-oriented
AI Analysis
This work addresses theoretical properties of neuronal recurrence equations, which is incremental for mathematical neuroscience.
The authors characterized the periods of a neuronal recurrence equation by analyzing k-chains in 0-1 periodic sequences and cycles, and explained how these results imply the existence of a generalized period-halving bifurcation.
We characterize the structure of the periods of a neuronal recurrence equation. Firstly, we give a characterization of k-chains in 0-1 periodic sequences. Secondly, we characterize the periods of all cycles of some neuronal recurrence equation. Thirdly, we explain how these results can be used to deduce the existence of the generalized period-halving bifurcation.