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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

Across different model neurons, switch in afferent activity between θ oscillations and SWRs triggered variable changes in ionic conductances during cell-autonomous self-regulation of calcium homeostasis. A, Schematic showing the temporal sequence of the experiment, along with notations for the temporal locations at which steady-state values of the sodium conductance (gNa) were measured in the course of their calcium-dependent evolution. Note that this schematic represents a theta–SWR–theta temporal sequence in afferent activity, and the notations here hold for B–E. All histograms depict statistics across the 78 valid models obtained after GSA. B, Histogram of gNa values at the steady state of the evolution with θ-frequency oscillations as afferent inputs. Inset, Histogram of base values of gNa obtained from GSA. C, Histogram of percentage changes in gNa measured at steady state of evolution with SWR inputs (after θ1–SWR), computed with reference to the steady state value after evolution with θ-frequency oscillations (θ1). D, Histogram of percentage changes in gNa measured at steady state of evolution with θ-frequency oscillations (after θ1–SWR–θ2), computed with reference to the steady state value after evolution with SWR inputs (after θ1–SWR). E, Histogram of percentage changes in gNa measured at steady state of evolution with θ-frequency oscillations (after θ1–SWR–θ2), computed with reference to gNa measured at steady state of evolution after θ1. F–J, Same as A–E, but for a SWR–theta–SWR temporal sequence in afferent activity, with notations for conductance values shown in F.
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Figure 8: Across different model neurons, switch in afferent activity between θ oscillations and SWRs triggered variable changes in ionic conductances during cell-autonomous self-regulation of calcium homeostasis. A, Schematic showing the temporal sequence of the experiment, along with notations for the temporal locations at which steady-state values of the sodium conductance (gNa) were measured in the course of their calcium-dependent evolution. Note that this schematic represents a theta–SWR–theta temporal sequence in afferent activity, and the notations here hold for B–E. All histograms depict statistics across the 78 valid models obtained after GSA. B, Histogram of gNa values at the steady state of the evolution with θ-frequency oscillations as afferent inputs. Inset, Histogram of base values of gNa obtained from GSA. C, Histogram of percentage changes in gNa measured at steady state of evolution with SWR inputs (after θ1–SWR), computed with reference to the steady state value after evolution with θ-frequency oscillations (θ1). D, Histogram of percentage changes in gNa measured at steady state of evolution with θ-frequency oscillations (after θ1–SWR–θ2), computed with reference to the steady state value after evolution with SWR inputs (after θ1–SWR). E, Histogram of percentage changes in gNa measured at steady state of evolution with θ-frequency oscillations (after θ1–SWR–θ2), computed with reference to gNa measured at steady state of evolution after θ1. F–J, Same as A–E, but for a SWR–theta–SWR temporal sequence in afferent activity, with notations for conductance values shown in F.

Mentions: We assessed the percentage changes in sodium conductance after each switch in both sequences (across all 78 model neurons), and found that the changes in conductances introduced by the switches were significantly variable (Fig. 8B–E for the theta–SWR–theta sequence and G–J for the SWR–theta–SWR sequence). We plotted the histogram solely for the sodium conductance, but not for all 12 conductances because the changes in all conductances are correlated given that a single transcription factor regulated all conductances. However, upon reverting back to the same type of afferent activity, a significant percentage of neurons were robust (with reference to conductance values, firing patterns and intrinsic properties) to the intervening switch to another type of afferent activity (Fig. 8E,J). The robustness of the neuron to an intermediate activity switch, however, was dependent on the specific temporal sequence of activity switch. Specifically, the percentage of neurons robust to an intervening period of activity switch was lower for the theta–SWR–theta (∼20%; Fig. 8E) compared with the percentage for SWR–theta–SWR sequence (∼90%; Fig. 8J). These results also reveal that the maintenance of calcium homeostasis does not necessarily require or translate to maintenance of individual conductances at specific values (O'Leary et al., 2014), and that significant plasticity in ionic conductances need not necessarily translate to significant changes in afferent-driven firing activity (Fig. 7F), thereby revealing a significant dissociation between individual channelostasis, activity/functional homeostasis and calcium homeostasis.


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)

Across different model neurons, switch in afferent activity between θ oscillations and SWRs triggered variable changes in ionic conductances during cell-autonomous self-regulation of calcium homeostasis. A, Schematic showing the temporal sequence of the experiment, along with notations for the temporal locations at which steady-state values of the sodium conductance (gNa) were measured in the course of their calcium-dependent evolution. Note that this schematic represents a theta–SWR–theta temporal sequence in afferent activity, and the notations here hold for B–E. All histograms depict statistics across the 78 valid models obtained after GSA. B, Histogram of gNa values at the steady state of the evolution with θ-frequency oscillations as afferent inputs. Inset, Histogram of base values of gNa obtained from GSA. C, Histogram of percentage changes in gNa measured at steady state of evolution with SWR inputs (after θ1–SWR), computed with reference to the steady state value after evolution with θ-frequency oscillations (θ1). D, Histogram of percentage changes in gNa measured at steady state of evolution with θ-frequency oscillations (after θ1–SWR–θ2), computed with reference to the steady state value after evolution with SWR inputs (after θ1–SWR). E, Histogram of percentage changes in gNa measured at steady state of evolution with θ-frequency oscillations (after θ1–SWR–θ2), computed with reference to gNa measured at steady state of evolution after θ1. F–J, Same as A–E, but for a SWR–theta–SWR temporal sequence in afferent activity, with notations for conductance values shown in F.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 8: Across different model neurons, switch in afferent activity between θ oscillations and SWRs triggered variable changes in ionic conductances during cell-autonomous self-regulation of calcium homeostasis. A, Schematic showing the temporal sequence of the experiment, along with notations for the temporal locations at which steady-state values of the sodium conductance (gNa) were measured in the course of their calcium-dependent evolution. Note that this schematic represents a theta–SWR–theta temporal sequence in afferent activity, and the notations here hold for B–E. All histograms depict statistics across the 78 valid models obtained after GSA. B, Histogram of gNa values at the steady state of the evolution with θ-frequency oscillations as afferent inputs. Inset, Histogram of base values of gNa obtained from GSA. C, Histogram of percentage changes in gNa measured at steady state of evolution with SWR inputs (after θ1–SWR), computed with reference to the steady state value after evolution with θ-frequency oscillations (θ1). D, Histogram of percentage changes in gNa measured at steady state of evolution with θ-frequency oscillations (after θ1–SWR–θ2), computed with reference to the steady state value after evolution with SWR inputs (after θ1–SWR). E, Histogram of percentage changes in gNa measured at steady state of evolution with θ-frequency oscillations (after θ1–SWR–θ2), computed with reference to gNa measured at steady state of evolution after θ1. F–J, Same as A–E, but for a SWR–theta–SWR temporal sequence in afferent activity, with notations for conductance values shown in F.
Mentions: We assessed the percentage changes in sodium conductance after each switch in both sequences (across all 78 model neurons), and found that the changes in conductances introduced by the switches were significantly variable (Fig. 8B–E for the theta–SWR–theta sequence and G–J for the SWR–theta–SWR sequence). We plotted the histogram solely for the sodium conductance, but not for all 12 conductances because the changes in all conductances are correlated given that a single transcription factor regulated all conductances. However, upon reverting back to the same type of afferent activity, a significant percentage of neurons were robust (with reference to conductance values, firing patterns and intrinsic properties) to the intervening switch to another type of afferent activity (Fig. 8E,J). The robustness of the neuron to an intermediate activity switch, however, was dependent on the specific temporal sequence of activity switch. Specifically, the percentage of neurons robust to an intervening period of activity switch was lower for the theta–SWR–theta (∼20%; Fig. 8E) compared with the percentage for SWR–theta–SWR sequence (∼90%; Fig. 8J). These results also reveal that the maintenance of calcium homeostasis does not necessarily require or translate to maintenance of individual conductances at specific values (O'Leary et al., 2014), and that significant plasticity in ionic conductances need not necessarily translate to significant changes in afferent-driven firing activity (Fig. 7F), thereby revealing a significant dissociation between individual channelostasis, activity/functional homeostasis and calcium homeostasis.

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