Nonlinear Maps for Design of Discrete-Time Models of Neuronal Network Dynamics
Abstract
To bring the design of map-based models of neuronal networks to a qualitatively new level of efficiency in modeling of neurobiological networks dynamics we propose to study discrete-time implementation for these elements and develop methods of nonlinear analysis and models design focusing on the following goals: 1. Improvement of discrete-time dynamical systems design for capturing important features of both intrinsic and response nonlinear behavior of specific. This includes: - Development of modeling techniques to form a complete set of nonlinear dynamical features of modeled neuron by coupling nonlinear difference equations capturing effects of various depolarizing and hyperpolarizing effects ionic currents. - Development of methods for nonlinear analysis of neuronal behavior that ensure robustness of the modeled features and comparative analysis of model behavior with the HH type of models or real data. 2. Demonstrate an improved design of efficient discrete-time models for dynamics of synaptic connections in a form enabling very efficient simulations of large-scale networks. We will develop computationally efficient algorithms for modeling various types of synaptic plasticity and demonstrate their performance in discrete-time network models. We will also design the computationally efficient methods for modeling effects of time-delay associated with spike propagation times. 3. Demonstration of feasibility and efficiency of the map-based approach in modeling important elements of dynamical behavior of in specific examples of neurobiological networks behavior. These examples will include modeling of network oscillations and dynamics synaptic plasticity (i.e. depression, facilitation, STDP, etc.) in multilayer cortical network and dynamics of controlled switching in Central Pattern Generators (CPGs) containing large populations of neurons.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jun 10, 2016
- Source ID
- N000141612252
Entities
People
- Nikolai Rulkov
Organizations
- Office of Naval Research
- United States Navy
- University of California, San Diego