Nonlinear Maps for Design of Discrete-Time Models of Neuronal Network Dynamics
Abstract
A new promising way to significantly improve computational efficiency of neurobiological network simulations is to design a neuronal model in the form of difference equations that generates neuronal states in discrete moments of time. In this approach, time step can be made comparable with the duration of action potential (a spike) and capture correctly dynamics of the intrinsic and input-responsive tiring patterns. We propose to use modern DSP ideas to develop new efficient approaches to the design of such discrete-time models for studies of large-scale neuronal network activity.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 31, 2016
- Accession Number
- AD1007639
Entities
People
- Nikolai Rulkov
Organizations
- University of California, San Diego