Limits...
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 neuron with h-conductance database frequencies. This series of panels show the oscillation frequencies of the individual neurons in the database with intrinsic ionic conductances corresponding to the titles and axes. Neuron potassium conductance increases from the top left to bottom right panels. Maximal calcium conductance is on the y-axis and maximal h-conductance is on the x-axis. The color bar in the bottom right corner conveys the frequency color coding that applies for all plots in this figure. White spaces indicate neurons that are silent, non-oscillatory, or do not cross threshold. All neurons have a ḡleak of 0.1 nS.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4596081&req=5

Figure 2: Morris–Lecar neuron with h-conductance database frequencies. This series of panels show the oscillation frequencies of the individual neurons in the database with intrinsic ionic conductances corresponding to the titles and axes. Neuron potassium conductance increases from the top left to bottom right panels. Maximal calcium conductance is on the y-axis and maximal h-conductance is on the x-axis. The color bar in the bottom right corner conveys the frequency color coding that applies for all plots in this figure. White spaces indicate neurons that are silent, non-oscillatory, or do not cross threshold. All neurons have a ḡleak of 0.1 nS.

Mentions: A database of Morris–Lecar neurons modified by a hyperpolarization-activated current was created (Fig. 2). A coarse sampling of the three-dimensional conductance space formed by the potassium, calcium, and h-conductances yielded many intrinsically oscillating neurons. In Figure 2, we show two-dimensional plots of the effects of altering ḡCa and ḡh on oscillation frequency for each of 15 values of ḡK. The regions of white space indicate sets of parameters at which the neuron is not oscillatory. As ḡK is increased, oscillatory behavior becomes increasingly predominant. Note that at each value of ḡK and ḡCa, increasing ḡh increases the oscillation frequency. In contrast, increasing ḡCa produces a rotated “U” in oscillator frequency, with the highest frequencies seen at the middle range of ḡCa. Consequently, at each value of ḡh and ḡK, it is likely that there are two or more models (with different ḡCa values) that produce similar frequency oscillations.


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

Gutierrez GJ, Marder E - eNeuro (2014)

Morris–Lecar neuron with h-conductance database frequencies. This series of panels show the oscillation frequencies of the individual neurons in the database with intrinsic ionic conductances corresponding to the titles and axes. Neuron potassium conductance increases from the top left to bottom right panels. Maximal calcium conductance is on the y-axis and maximal h-conductance is on the x-axis. The color bar in the bottom right corner conveys the frequency color coding that applies for all plots in this figure. White spaces indicate neurons that are silent, non-oscillatory, or do not cross threshold. All neurons have a ḡleak of 0.1 nS.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 2: Morris–Lecar neuron with h-conductance database frequencies. This series of panels show the oscillation frequencies of the individual neurons in the database with intrinsic ionic conductances corresponding to the titles and axes. Neuron potassium conductance increases from the top left to bottom right panels. Maximal calcium conductance is on the y-axis and maximal h-conductance is on the x-axis. The color bar in the bottom right corner conveys the frequency color coding that applies for all plots in this figure. White spaces indicate neurons that are silent, non-oscillatory, or do not cross threshold. All neurons have a ḡleak of 0.1 nS.
Mentions: A database of Morris–Lecar neurons modified by a hyperpolarization-activated current was created (Fig. 2). A coarse sampling of the three-dimensional conductance space formed by the potassium, calcium, and h-conductances yielded many intrinsically oscillating neurons. In Figure 2, we show two-dimensional plots of the effects of altering ḡCa and ḡh on oscillation frequency for each of 15 values of ḡK. The regions of white space indicate sets of parameters at which the neuron is not oscillatory. As ḡK is increased, oscillatory behavior becomes increasingly predominant. Note that at each value of ḡK and ḡCa, increasing ḡh increases the oscillation frequency. In contrast, increasing ḡCa produces a rotated “U” in oscillator frequency, with the highest frequencies seen at the middle range of ḡCa. Consequently, at each value of ḡh and ḡK, it is likely that there are two or more models (with different ḡCa values) that produce similar frequency oscillations.

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.