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Modulation of a Single Neuron Has State-Dependent Actions on Circuit Dynamics(,.)

Gutierrez GJ, Marder E - eNeuro (2014)

Bottom Line: We determined the effects of varying ḡCa , ḡK , and ḡh on the frequency, amplitude, and duty cycle of a single neuron oscillator.For a different set of network parameters, circuit behavior varied with the maximal conductances of the hub neuron.This demonstrates that neuromodulation of a single target neuron may dramatically alter the performance of an entire network when the network is in one state, but have almost no effect when the circuit is in a different state.

View Article: PubMed Central - HTML - PubMed

Affiliation: Volen Center for Complex Systems and Biology Department, Brandeis University, Waltham, Massachusetts 02454.

ABSTRACT

When does neuromodulation of a single neuron influence the output of the entire network? We constructed a five-cell circuit in which a neuron is at the center of the circuit and the remaining neurons form two distinct oscillatory subnetworks. All neurons were modeled as modified Morris-Lecar models with a hyperpolarization-activated conductance (ḡh ) in addition to calcium (ḡCa ), potassium (ḡK ), and leak conductances. We determined the effects of varying ḡCa , ḡK , and ḡh on the frequency, amplitude, and duty cycle of a single neuron oscillator. The frequency of the single neuron was highest when the ḡK and ḡh conductances were high and ḡCa was moderate whereas, in the traditional Morris-Lecar model, the highest frequencies occur when both ḡK and ḡCa are high. We randomly sampled parameter space to find 143 hub oscillators with nearly identical frequencies but with disparate maximal conductance, duty cycles, and burst amplitudes, and then embedded each of these hub neurons into networks with different sets of synaptic parameters. For one set of network parameters, circuit behavior was virtually identical regardless of the underlying conductances of the hub neuron. For a different set of network parameters, circuit behavior varied with the maximal conductances of the hub neuron. This demonstrates that neuromodulation of a single target neuron may dramatically alter the performance of an entire network when the network is in one state, but have almost no effect when the circuit is in a different state.

No MeSH data available.


Morris–Lecar model neuron with h-conductance. Voltage wave form example of an oscillating model neuron is shown. In this study, we quantify oscillation frequency (period illustrated by green lines and arrow), duty cycle (magenta), peak voltage (cyan), and baseline voltage (blue).
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Figure 1: Morris–Lecar model neuron with h-conductance. Voltage wave form example of an oscillating model neuron is shown. In this study, we quantify oscillation frequency (period illustrated by green lines and arrow), duty cycle (magenta), peak voltage (cyan), and baseline voltage (blue).

Mentions: The intrinsic properties of the hub neuron candidates were analyzed using our MATLAB code. Duty cycle is defined as the proportion of cycle time that the neuron is above threshold, i.e., the time the oscillator spends at voltages larger than 0 mV divided by the period (0 mV; Fig. 1A, magenta arrow). Here, this quantity was computed as the mean duty cycle of the complete cycles taking place over the last 300 s of the simulation. The peak and trough voltages are the most positive and most negative voltages in the wave form, respectively (Fig. 1A, cyan and blue lines and arrows). The peak voltage quantity subsequently refers to the mean of the suprathreshold peak voltages over the last 300 s of simulation time. The trough voltage for each neuron is the mean voltage of the subthreshold troughs over the last 300 s of the simulation.


Modulation of a Single Neuron Has State-Dependent Actions on Circuit Dynamics(,.)

Gutierrez GJ, Marder E - eNeuro (2014)

Morris–Lecar model neuron with h-conductance. Voltage wave form example of an oscillating model neuron is shown. In this study, we quantify oscillation frequency (period illustrated by green lines and arrow), duty cycle (magenta), peak voltage (cyan), and baseline voltage (blue).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4596081&req=5

Figure 1: Morris–Lecar model neuron with h-conductance. Voltage wave form example of an oscillating model neuron is shown. In this study, we quantify oscillation frequency (period illustrated by green lines and arrow), duty cycle (magenta), peak voltage (cyan), and baseline voltage (blue).
Mentions: The intrinsic properties of the hub neuron candidates were analyzed using our MATLAB code. Duty cycle is defined as the proportion of cycle time that the neuron is above threshold, i.e., the time the oscillator spends at voltages larger than 0 mV divided by the period (0 mV; Fig. 1A, magenta arrow). Here, this quantity was computed as the mean duty cycle of the complete cycles taking place over the last 300 s of the simulation. The peak and trough voltages are the most positive and most negative voltages in the wave form, respectively (Fig. 1A, cyan and blue lines and arrows). The peak voltage quantity subsequently refers to the mean of the suprathreshold peak voltages over the last 300 s of simulation time. The trough voltage for each neuron is the mean voltage of the subthreshold troughs over the last 300 s of the simulation.

Bottom Line: We determined the effects of varying ḡCa , ḡK , and ḡh on the frequency, amplitude, and duty cycle of a single neuron oscillator.For a different set of network parameters, circuit behavior varied with the maximal conductances of the hub neuron.This demonstrates that neuromodulation of a single target neuron may dramatically alter the performance of an entire network when the network is in one state, but have almost no effect when the circuit is in a different state.

View Article: PubMed Central - HTML - PubMed

Affiliation: Volen Center for Complex Systems and Biology Department, Brandeis University, Waltham, Massachusetts 02454.

ABSTRACT

When does neuromodulation of a single neuron influence the output of the entire network? We constructed a five-cell circuit in which a neuron is at the center of the circuit and the remaining neurons form two distinct oscillatory subnetworks. All neurons were modeled as modified Morris-Lecar models with a hyperpolarization-activated conductance (ḡh ) in addition to calcium (ḡCa ), potassium (ḡK ), and leak conductances. We determined the effects of varying ḡCa , ḡK , and ḡh on the frequency, amplitude, and duty cycle of a single neuron oscillator. The frequency of the single neuron was highest when the ḡK and ḡh conductances were high and ḡCa was moderate whereas, in the traditional Morris-Lecar model, the highest frequencies occur when both ḡK and ḡCa are high. We randomly sampled parameter space to find 143 hub oscillators with nearly identical frequencies but with disparate maximal conductance, duty cycles, and burst amplitudes, and then embedded each of these hub neurons into networks with different sets of synaptic parameters. For one set of network parameters, circuit behavior was virtually identical regardless of the underlying conductances of the hub neuron. For a different set of network parameters, circuit behavior varied with the maximal conductances of the hub neuron. This demonstrates that neuromodulation of a single target neuron may dramatically alter the performance of an entire network when the network is in one state, but have almost no effect when the circuit is in a different state.

No MeSH data available.