Intrinsic membrane properties and dynamics of medial vestibular neurons: a simulation.

The vestibulo-ocular and vestibulo-spinal network provides the ability to hold gaze fixed on an object during passive head movement. Within that network, most of the second-order neurons of the medial vestibular nucleus (MVNn) compute internal representations of head movement velocity in the horizontal plane. Our previous in vitro studies of the MVNn membrane properties indicated that they may play a major role in determining the dynamic properties of these neurons independently of their connectivity. The present study investigated that hypothesis at a theoretical level. Biophysical models of type A and B MVNn were developed. Two factors were found to be important in modeling tonic and phasic firing activity: the activation of the delayed potassium current and the rate of calcium flux. In addition, the model showed that the strength of the delayed potassium current may determine the different forms of action potentials observed experimentally. These two models (type A and B cells) were examined using depolarizing stimulation, random noise, step, ramp and sinusoidal inputs. For random noise, type A cells showed stable (regular) firing frequencies, while type B cells exhibited irregular activity. With step stimulation, the models exhibited tonic and phasic firing responses, respectively. Using ramp stimulations, frequency versus current curves showed a linear response for the type B neuron model. Finally, with sinusoidal stimulation of increasing frequencies, the type A model demonstrated a decrease in sensitivity, while the type B model exhibited an increase in sensitivity. These theoretical results support the hypothesis that MVNn intrinsic membrane properties specify various types of dynamic properties amongst these cells and therefore contribute to the wide range of dynamic responses which characterize the vestibulo-ocular and vestibulo-spinal network.

XNBC: a simulation tool. Application to the study of neural coding using hybrid networks.

XNBC is a software package for simulating biological neural networks. Two neuron models are available, a leaky integrator model and an ion-conductance model. Inputs to the simulated neurons can be provided by experimental data stored in files, allowing the creation of 'hybrid' networks. Graphic tools are used to describe the modeled neurons as well as the network. Neuron and network parameters can be modified during the simulation, to mimic electrical stimulations and drugs action. The temporal evolution of the network and of selected neurons can be visualized. A point process, frequency or dynamic analysis of the simulator output can be performed. The successive stages of the creation of a hybrid network are explained.

A model for temporal and intensity coding in insect olfaction by a network of inhibitory neurons.

Female insects release sex-pheromones which attract their conspecific males. These pheromones are detected through a distinct male-specific olfactory subsystem which resides at the first stage of olfactory processing, and consists of receptor, local and projection (relay) neurons. When male insects were stimulated by female sexpheromones, some projection neurons could distinguish between different pheromones, following input and code stimulus intensity. Presented here, is a simple biophysical model that described characteristic bursting responses observed for projection neurons. The bursting behavior of the model resulted from a particular cellular mechanism and specific network architecture. At the neuron level, a rapidly activating and slowly inactivating low-threshold calcium channel provided depolarizing current for bursting, while at the network level, inhibitory neurons implementing dis-inhibition which triggered this calcium channel. Also, the network architecture provided a mechanism by which certain projection neurons coded temporal input and stimulus intensity.

Modeling insect olfactory neuron signaling by a network utilizing disinhibition.

A male moth locates a conspecific female by detecting her sexual-pheromone blend. This detection is carried out in the antennal lobe, the first stage of olfactory information processing, where local inhibitory neurons and projection (relay) neurons interact. Antennal-lobe neurons exhibit low-frequency (< 10 Hz) background activity and bursting (> 100 Hz) activity in response to pheromone stimulation. We describe this behavior by a realistic biophysical neuron model. The bursting behavior of the model is the result of both intrinsic cellular properties and network interaction. A slowly activating and inactivating calcium channel provides a depolarizing current for bursting and disinhibition is shown to be a feasible network mechanism for triggering this calcium channel. Small neural networks utilizing disinhibition are presented with local neurons intercalated between receptor and projection neurons. The firing behaviors of projection neurons in response to stimulation by the pheromone blend or its components are in accordance with experimental results. This network architecture offers an alternative view of olfactory processing from the classical architecture derived from vertebrate studies.

The role of a transient potassium current in a bursting neuron model.

Presented here is a biophysical cell model which can exhibit low-frequency repetitive activity and bursting behavior. The model is developed from previous models (Av-Ron et al. 1991, 1993) for excitability, oscillations and bursting. A stepwise development of the present model shows the contribution of a transient potassium current (IA) to the overall dynamics. By changing a limited set of model parameters one can describe different firing patterns; oscillations with frequencies ranging from 2-200 Hz and a wide range of bursting behaviors in terms of the durations of bursting and quiescence, peak firing frequency and rate of change of the firing frequency.

A basic biophysical model for bursting neurons.

Presented here is a basic biophysical cell model for bursting, an extension of our previous model (Av-Ron et al. 1991) for excitability and oscillations. By changing a limited set of model parameters, one can describe different patterns of bursting behavior in terms of the burst cycle, the durations of oscillation and quiescence, and firing frequency.

A minimal biophysical model for an excitable and oscillatory neuron.

Presented here is a minimal biophysical cell model, based on work by Hodgkin and Huxley and by Rinzel, that can exhibit both excitable and oscillatory behavior. Two versions of the model are studied, which conform to data for squid and lobster giant axons.