We report a noise induced delay of bifurcation in a simple pulse-coupled neural circuit. We study the behavior of two neural oscillators, each individually governed by saddle-node dynamics, with reciprocal excitatory synaptic connections. In the deterministic circuit, the synaptic current amplitude acts as a control parameter to move the circuit from a mono-stable regime through a bifurcation into a bistable regime. In this regime stable sustained anti-phase oscillations in both neurons coexist with a stable rest state. We introduce a small amount of random current into both neurons to model possible randomly arriving synaptic inputs. We find that such random noise delays the onset of bistability, even though in decoupled neurons noise tend...
<div><p>In order to study the ability of coupled neural oscillators to synchronize in the presence o...
Rhythmic neural activity plays a central role in neural computation. Oscillatory activity has been a...
The present thesis is concerned with the stochastic phase dynamics of neuron models and spike time r...
We study a model for a network of synaptically coupled, excitable neurons to identify the role of co...
Spike time-dependent plasticity is a fundamental adaptation mechanism of the nervous system. It indu...
We present here some studies on noise-induced order and synchronous firing in a system of bidirectio...
We study the nonlinear FitzHugh-Nagumo model witch describes the dynamics of excitable neural elemen...
Spike timing-dependent plasticity is a fundamental adaptation mechanism of the nervous system. It in...
GABAergic interneurons play a major role in the emergence of various types of synchronous oscillator...
Intuitively one might expect independent noise to be a powerful tool for desynchronizing a populatio...
The response of neurons is highly sensitive to the stimulus. The stimulus can be associated with a d...
Intuitively one might expect independent noise to be a powerful tool for desynchronizing a populatio...
A stochastic-delay differential equation (SDDE) model of a small neural network with recurrent inhib...
We study an excitatory all-to-all coupled network of N spiking neurons with synaptically filtered ba...
Stochastic resonance in a coupled FitzHugh–Nagumo equation with a propagational time delay is invest...
<div><p>In order to study the ability of coupled neural oscillators to synchronize in the presence o...
Rhythmic neural activity plays a central role in neural computation. Oscillatory activity has been a...
The present thesis is concerned with the stochastic phase dynamics of neuron models and spike time r...
We study a model for a network of synaptically coupled, excitable neurons to identify the role of co...
Spike time-dependent plasticity is a fundamental adaptation mechanism of the nervous system. It indu...
We present here some studies on noise-induced order and synchronous firing in a system of bidirectio...
We study the nonlinear FitzHugh-Nagumo model witch describes the dynamics of excitable neural elemen...
Spike timing-dependent plasticity is a fundamental adaptation mechanism of the nervous system. It in...
GABAergic interneurons play a major role in the emergence of various types of synchronous oscillator...
Intuitively one might expect independent noise to be a powerful tool for desynchronizing a populatio...
The response of neurons is highly sensitive to the stimulus. The stimulus can be associated with a d...
Intuitively one might expect independent noise to be a powerful tool for desynchronizing a populatio...
A stochastic-delay differential equation (SDDE) model of a small neural network with recurrent inhib...
We study an excitatory all-to-all coupled network of N spiking neurons with synaptically filtered ba...
Stochastic resonance in a coupled FitzHugh–Nagumo equation with a propagational time delay is invest...
<div><p>In order to study the ability of coupled neural oscillators to synchronize in the presence o...
Rhythmic neural activity plays a central role in neural computation. Oscillatory activity has been a...
The present thesis is concerned with the stochastic phase dynamics of neuron models and spike time r...