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Variability in State-Dependent Plasticity of Intrinsic Properties during Cell-Autonomous Self-Regulation of Calcium Homeostasis in Hippocampal Model Neurons(1,2,3).

Srikanth S, Narayanan R - eNeuro (2015)

Bottom Line: Although calcium homeostasis emerged efficaciously across all models in the population, disparate changes in ionic conductances that mediated this emergence resulted in variable plasticity to several intrinsic properties, also manifesting as significant differences in firing responses across models.We found that the conductance values, intrinsic properties, and firing response of neurons exhibited differential robustness to an intervening switch in the type of afferent activity.These results unveil critical dissociations between different forms of homeostasis, and call for a systematic evaluation of the impact of state-dependent switches in afferent activity on neuronal intrinsic properties during neural coding and homeostasis.

View Article: PubMed Central - HTML - PubMed

Affiliation: Cellular Neurophysiology Laboratory, Molecular Biophysics Unit, Indian Institute of Science , Bangalore 560 012, India ; Undergraduate program, Indian Institute of Science , Bangalore 560 012, India.

ABSTRACT
How do neurons reconcile the maintenance of calcium homeostasis with perpetual switches in patterns of afferent activity? Here, we assessed state-dependent evolution of calcium homeostasis in a population of hippocampal pyramidal neuron models, through an adaptation of a recent study on stomatogastric ganglion neurons. Calcium homeostasis was set to emerge through cell-autonomous updates to 12 ionic conductances, responding to different types of synaptically driven afferent activity. We first assessed the impact of theta-frequency inputs on the evolution of ionic conductances toward maintenance of calcium homeostasis. Although calcium homeostasis emerged efficaciously across all models in the population, disparate changes in ionic conductances that mediated this emergence resulted in variable plasticity to several intrinsic properties, also manifesting as significant differences in firing responses across models. Assessing the sensitivity of this form of plasticity, we noted that intrinsic neuronal properties and the firing response were sensitive to the target calcium concentration and to the strength and frequency of afferent activity. Next, we studied the evolution of calcium homeostasis when afferent activity was switched, in different temporal sequences, between two behaviorally distinct types of activity: theta-frequency inputs and sharp-wave ripples riding on largely silent periods. We found that the conductance values, intrinsic properties, and firing response of neurons exhibited differential robustness to an intervening switch in the type of afferent activity. These results unveil critical dissociations between different forms of homeostasis, and call for a systematic evaluation of the impact of state-dependent switches in afferent activity on neuronal intrinsic properties during neural coding and homeostasis.

No MeSH data available.


Related in: MedlinePlus

Measurements of intrinsic response dynamics in the base neuronal model. A, The cylindrical model used in this study showing the 11 ion channels inserted. The red arrows denote inward currents and the green arrows denote outward currents. B, Voltage responses (top) of the base neuronal model to current pulses (bottom) ranging from –50 to 50 pA in steps of 10 pA. C, The steady state voltages from (B) are plotted against the corresponding current injected. The slope of the resulting V–I plot was defined as the input resistance, Rin. D, The voltage response of the base neuronal model to a current injection of 250 pA. The amplitude of the last action potential was defined as the action potential (AP) amplitude, VAP. E, The AP firing frequency (f) versus injected current plot showing the frequency of firing with current injections from 0 to 250 pA in steps of 50 pA. The number of APs elicited by the model in response to a 250 pA, 500 ms current pulse was used to compute the firing rate at 250 pA, f250. F, The model’s voltage response (top) to a chirp current stimulus of peak-to-peak amplitude of 100 pA, with frequency linearly increasing from 0 to 25 Hz in 25 s (bottom). G, The impedance amplitude profile /Z(f)/ derived from traces in F. The frequency at which the impedance amplitude is maximum (/Z/max) was defined as the resonance frequency, fR. The strength of resonance, Q, was taken as the ratio of /Z(fR)/ to /Z(0.5)/. H, The impedance phase profile (ϕ(f)) with the area under the inductive part of the curve defined as the total inductive phase (ΦL).
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Figure 1: Measurements of intrinsic response dynamics in the base neuronal model. A, The cylindrical model used in this study showing the 11 ion channels inserted. The red arrows denote inward currents and the green arrows denote outward currents. B, Voltage responses (top) of the base neuronal model to current pulses (bottom) ranging from –50 to 50 pA in steps of 10 pA. C, The steady state voltages from (B) are plotted against the corresponding current injected. The slope of the resulting V–I plot was defined as the input resistance, Rin. D, The voltage response of the base neuronal model to a current injection of 250 pA. The amplitude of the last action potential was defined as the action potential (AP) amplitude, VAP. E, The AP firing frequency (f) versus injected current plot showing the frequency of firing with current injections from 0 to 250 pA in steps of 50 pA. The number of APs elicited by the model in response to a 250 pA, 500 ms current pulse was used to compute the firing rate at 250 pA, f250. F, The model’s voltage response (top) to a chirp current stimulus of peak-to-peak amplitude of 100 pA, with frequency linearly increasing from 0 to 25 Hz in 25 s (bottom). G, The impedance amplitude profile /Z(f)/ derived from traces in F. The frequency at which the impedance amplitude is maximum (/Z/max) was defined as the resonance frequency, fR. The strength of resonance, Q, was taken as the ratio of /Z(fR)/ to /Z(0.5)/. H, The impedance phase profile (ϕ(f)) with the area under the inductive part of the curve defined as the total inductive phase (ΦL).

Mentions: To study state-dependent and cell-autonomous calcium homeostasis in hippocampal CA1 pyramidal neurons, we used a single compartmental cylindrical model of diameter (d) = 100 μm and length (L) = 100 μm. Passive properties were set as specific membrane resistance (Rm) = 35 kΩ.cm2 and specific membrane capacitance (Cm) = 1 μF/cm2. These settings ensured that the passive input resistance (Rin) was ∼111 MΩ and the passive membrane time constant was 35 ms (Narayanan and Johnston, 2007, 2008). The neuronal compartment consisted of 11 conductance-based models for ion channels (Fig. 1A) namely, fast sodium (NaF), delayed-rectifier potassium (KDR), A-type potassium (KA), M-type potassium (KM), T-type calcium (CaT), R-type calcium (CaR), N-type calcium (CaN), L-type calcium (CaL), hyperpolarization-activated cyclic nucleotide gated channel (HCN or h), small conductance (SK) and big conductance calcium-activated potassium (BK) channels. The channel kinetics for NaF, KDR, and KA were obtained from Hoffman et al. (1997) and Migliore et al. (1999), for CaT from Shah et al. (2011), for KM from Migliore et al. (2006), for CaR and CaL from Magee and Johnston (1995) and Poirazi et al. (2003), CaN and SK from Migliore et al. (1995), for HCN from Magee (1998) and Poolos et al. (2002), and for BK from Moczydlowski and Latorre (1983). The reversal potentials for K+ and Na+ ions were set as –90 and +55 mV, respectively, and for the HCN channel as –30 mV. Accounting for the leak conductance (gleak=1/Rm), this configuration meant the presence of 12 ion channels in our model.


Variability in State-Dependent Plasticity of Intrinsic Properties during Cell-Autonomous Self-Regulation of Calcium Homeostasis in Hippocampal Model Neurons(1,2,3).

Srikanth S, Narayanan R - eNeuro (2015)

Measurements of intrinsic response dynamics in the base neuronal model. A, The cylindrical model used in this study showing the 11 ion channels inserted. The red arrows denote inward currents and the green arrows denote outward currents. B, Voltage responses (top) of the base neuronal model to current pulses (bottom) ranging from –50 to 50 pA in steps of 10 pA. C, The steady state voltages from (B) are plotted against the corresponding current injected. The slope of the resulting V–I plot was defined as the input resistance, Rin. D, The voltage response of the base neuronal model to a current injection of 250 pA. The amplitude of the last action potential was defined as the action potential (AP) amplitude, VAP. E, The AP firing frequency (f) versus injected current plot showing the frequency of firing with current injections from 0 to 250 pA in steps of 50 pA. The number of APs elicited by the model in response to a 250 pA, 500 ms current pulse was used to compute the firing rate at 250 pA, f250. F, The model’s voltage response (top) to a chirp current stimulus of peak-to-peak amplitude of 100 pA, with frequency linearly increasing from 0 to 25 Hz in 25 s (bottom). G, The impedance amplitude profile /Z(f)/ derived from traces in F. The frequency at which the impedance amplitude is maximum (/Z/max) was defined as the resonance frequency, fR. The strength of resonance, Q, was taken as the ratio of /Z(fR)/ to /Z(0.5)/. H, The impedance phase profile (ϕ(f)) with the area under the inductive part of the curve defined as the total inductive phase (ΦL).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4596012&req=5

Figure 1: Measurements of intrinsic response dynamics in the base neuronal model. A, The cylindrical model used in this study showing the 11 ion channels inserted. The red arrows denote inward currents and the green arrows denote outward currents. B, Voltage responses (top) of the base neuronal model to current pulses (bottom) ranging from –50 to 50 pA in steps of 10 pA. C, The steady state voltages from (B) are plotted against the corresponding current injected. The slope of the resulting V–I plot was defined as the input resistance, Rin. D, The voltage response of the base neuronal model to a current injection of 250 pA. The amplitude of the last action potential was defined as the action potential (AP) amplitude, VAP. E, The AP firing frequency (f) versus injected current plot showing the frequency of firing with current injections from 0 to 250 pA in steps of 50 pA. The number of APs elicited by the model in response to a 250 pA, 500 ms current pulse was used to compute the firing rate at 250 pA, f250. F, The model’s voltage response (top) to a chirp current stimulus of peak-to-peak amplitude of 100 pA, with frequency linearly increasing from 0 to 25 Hz in 25 s (bottom). G, The impedance amplitude profile /Z(f)/ derived from traces in F. The frequency at which the impedance amplitude is maximum (/Z/max) was defined as the resonance frequency, fR. The strength of resonance, Q, was taken as the ratio of /Z(fR)/ to /Z(0.5)/. H, The impedance phase profile (ϕ(f)) with the area under the inductive part of the curve defined as the total inductive phase (ΦL).
Mentions: To study state-dependent and cell-autonomous calcium homeostasis in hippocampal CA1 pyramidal neurons, we used a single compartmental cylindrical model of diameter (d) = 100 μm and length (L) = 100 μm. Passive properties were set as specific membrane resistance (Rm) = 35 kΩ.cm2 and specific membrane capacitance (Cm) = 1 μF/cm2. These settings ensured that the passive input resistance (Rin) was ∼111 MΩ and the passive membrane time constant was 35 ms (Narayanan and Johnston, 2007, 2008). The neuronal compartment consisted of 11 conductance-based models for ion channels (Fig. 1A) namely, fast sodium (NaF), delayed-rectifier potassium (KDR), A-type potassium (KA), M-type potassium (KM), T-type calcium (CaT), R-type calcium (CaR), N-type calcium (CaN), L-type calcium (CaL), hyperpolarization-activated cyclic nucleotide gated channel (HCN or h), small conductance (SK) and big conductance calcium-activated potassium (BK) channels. The channel kinetics for NaF, KDR, and KA were obtained from Hoffman et al. (1997) and Migliore et al. (1999), for CaT from Shah et al. (2011), for KM from Migliore et al. (2006), for CaR and CaL from Magee and Johnston (1995) and Poirazi et al. (2003), CaN and SK from Migliore et al. (1995), for HCN from Magee (1998) and Poolos et al. (2002), and for BK from Moczydlowski and Latorre (1983). The reversal potentials for K+ and Na+ ions were set as –90 and +55 mV, respectively, and for the HCN channel as –30 mV. Accounting for the leak conductance (gleak=1/Rm), this configuration meant the presence of 12 ion channels in our model.

Bottom Line: Although calcium homeostasis emerged efficaciously across all models in the population, disparate changes in ionic conductances that mediated this emergence resulted in variable plasticity to several intrinsic properties, also manifesting as significant differences in firing responses across models.We found that the conductance values, intrinsic properties, and firing response of neurons exhibited differential robustness to an intervening switch in the type of afferent activity.These results unveil critical dissociations between different forms of homeostasis, and call for a systematic evaluation of the impact of state-dependent switches in afferent activity on neuronal intrinsic properties during neural coding and homeostasis.

View Article: PubMed Central - HTML - PubMed

Affiliation: Cellular Neurophysiology Laboratory, Molecular Biophysics Unit, Indian Institute of Science , Bangalore 560 012, India ; Undergraduate program, Indian Institute of Science , Bangalore 560 012, India.

ABSTRACT
How do neurons reconcile the maintenance of calcium homeostasis with perpetual switches in patterns of afferent activity? Here, we assessed state-dependent evolution of calcium homeostasis in a population of hippocampal pyramidal neuron models, through an adaptation of a recent study on stomatogastric ganglion neurons. Calcium homeostasis was set to emerge through cell-autonomous updates to 12 ionic conductances, responding to different types of synaptically driven afferent activity. We first assessed the impact of theta-frequency inputs on the evolution of ionic conductances toward maintenance of calcium homeostasis. Although calcium homeostasis emerged efficaciously across all models in the population, disparate changes in ionic conductances that mediated this emergence resulted in variable plasticity to several intrinsic properties, also manifesting as significant differences in firing responses across models. Assessing the sensitivity of this form of plasticity, we noted that intrinsic neuronal properties and the firing response were sensitive to the target calcium concentration and to the strength and frequency of afferent activity. Next, we studied the evolution of calcium homeostasis when afferent activity was switched, in different temporal sequences, between two behaviorally distinct types of activity: theta-frequency inputs and sharp-wave ripples riding on largely silent periods. We found that the conductance values, intrinsic properties, and firing response of neurons exhibited differential robustness to an intervening switch in the type of afferent activity. These results unveil critical dissociations between different forms of homeostasis, and call for a systematic evaluation of the impact of state-dependent switches in afferent activity on neuronal intrinsic properties during neural coding and homeostasis.

No MeSH data available.


Related in: MedlinePlus