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Using multi-compartment ensemble modeling as an investigative tool of spatially distributed biophysical balances: application to hippocampal oriens-lacunosum/moleculare (O-LM) cells.

Sekulić V, Lawrence JJ, Skinner FK - PLoS ONE (2014)

Bottom Line: Models were quantified and ranked based on minimal error compared to a dataset of O-LM cell electrophysiological properties.Co-regulatory balances between conductances were revealed, two of which were dependent on the presence of dendritic Ih.These findings inform future experiments that differentiate between somatic and dendritic Ih, thereby continuing a cycle between model and experiment.

View Article: PubMed Central - PubMed

Affiliation: Toronto Western Research Institute, University Health Network, Toronto, Ontario, Canada; Department of Physiology, University of Toronto, Toronto, Ontario, Canada.

ABSTRACT
Multi-compartmental models of neurons provide insight into the complex, integrative properties of dendrites. Because it is not feasible to experimentally determine the exact density and kinetics of each channel type in every neuronal compartment, an essential goal in developing models is to help characterize these properties. To address biological variability inherent in a given neuronal type, there has been a shift away from using hand-tuned models towards using ensembles or populations of models. In collectively capturing a neuron's output, ensemble modeling approaches uncover important conductance balances that control neuronal dynamics. However, conductances are never entirely known for a given neuron class in terms of its types, densities, kinetics and distributions. Thus, any multi-compartment model will always be incomplete. In this work, our main goal is to use ensemble modeling as an investigative tool of a neuron's biophysical balances, where the cycling between experiment and model is a design criterion from the start. We consider oriens-lacunosum/moleculare (O-LM) interneurons, a prominent interneuron subtype that plays an essential gating role of information flow in hippocampus. O-LM cells express the hyperpolarization-activated current (Ih). Although dendritic Ih could have a major influence on the integrative properties of O-LM cells, the compartmental distribution of Ih on O-LM dendrites is not known. Using a high-performance computing cluster, we generated a database of models that included those with or without dendritic Ih. A range of conductance values for nine different conductance types were used, and different morphologies explored. Models were quantified and ranked based on minimal error compared to a dataset of O-LM cell electrophysiological properties. Co-regulatory balances between conductances were revealed, two of which were dependent on the presence of dendritic Ih. These findings inform future experiments that differentiate between somatic and dendritic Ih, thereby continuing a cycle between model and experiment.

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Hyperpolarization-induced sag response varies as a function of Ih maximum conductance density and somatodendritic distribution in models.Plots of the average sag response (mV) of model outputs as recorded in the soma as a function of different Ih maximum conductance density values across different model subsets. The general and restricted subsets of highly-ranked models with Ih in soma and dendrites are shown in red and green, respectively (“General S+D” and “Restricted S+D”, respectively, in the figure legend). The general and restricted subsets of highly-ranked models with Ih in soma only are shown in blue and black, respectively (“General S” and “Restricted S”, respectively, in the figure legend). Error bars denote standard deviations of the sag response in the respective model database subsets.
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pone-0106567-g007: Hyperpolarization-induced sag response varies as a function of Ih maximum conductance density and somatodendritic distribution in models.Plots of the average sag response (mV) of model outputs as recorded in the soma as a function of different Ih maximum conductance density values across different model subsets. The general and restricted subsets of highly-ranked models with Ih in soma and dendrites are shown in red and green, respectively (“General S+D” and “Restricted S+D”, respectively, in the figure legend). The general and restricted subsets of highly-ranked models with Ih in soma only are shown in blue and black, respectively (“General S” and “Restricted S”, respectively, in the figure legend). Error bars denote standard deviations of the sag response in the respective model database subsets.

Mentions: Close examination of our highly-ranked models revealed that they did not adequately capture the hyperpolarization-induced “sag” response typically observed in O-LM cell experimental data. This can be seen in Fig. 2, where the biological cells (Fig. 2D,E) show larger sag as compared with the highly-ranked models (e.g., Fig. 2A). Specifically, this measure, PulsePotSag, has a mean of 14.2 mV and a standard deviation of 3.1 mV in the experimental dataset (see Table S1), whereas its value maximally approaches 8 mV in any of the models. This is shown in Fig. 7 where this measure is plotted for general and restricted sets, and for models with or without dendritic Ih. Considering the models without dendritic Ih, we see that as the Ih conductance density increases, the sag amplitude also increases. One might think that if we simply increased this value more, the sag amplitudes in the models could better represent those seen in experiment. However, this is not the case, as an earlier version of our model database, with larger Ih conductances, exhibited unacceptable models (not shown) when the Ih maximal conductance densities were larger than 0.5 pS/µm2, which is the upper range of values in the current database. In other words, this increase in sag amplitude with increasing Ih conductance is due to a balanced increase of Ih conductance, as other conductances in the variety of models are not the same. Now, considering the models with dendritic Ih, a larger sag amplitude can be obtained, but with the restricted set, models do not possess Ih maximum conductance densites greater than 0.1 pS/µm2 (Fig. 7, green line). Again, this increase in sag amplitude with larger Ih conductances is a balanced response. We note that these observations are a result of our database analyses, and would not have been feasible to uncover using hand-tuned modeling. We further note that our database design of models with and without dendritic Ih allowed us to easily examine what differences might exist between the two cases and to clearly show that dendritic Ih models are better at capturing the sag amplitude feature. However, as noted above, the sag amplitude feature is a clear limitation of the models (Fig. 1, Step 4(ii)).


Using multi-compartment ensemble modeling as an investigative tool of spatially distributed biophysical balances: application to hippocampal oriens-lacunosum/moleculare (O-LM) cells.

Sekulić V, Lawrence JJ, Skinner FK - PLoS ONE (2014)

Hyperpolarization-induced sag response varies as a function of Ih maximum conductance density and somatodendritic distribution in models.Plots of the average sag response (mV) of model outputs as recorded in the soma as a function of different Ih maximum conductance density values across different model subsets. The general and restricted subsets of highly-ranked models with Ih in soma and dendrites are shown in red and green, respectively (“General S+D” and “Restricted S+D”, respectively, in the figure legend). The general and restricted subsets of highly-ranked models with Ih in soma only are shown in blue and black, respectively (“General S” and “Restricted S”, respectively, in the figure legend). Error bars denote standard deviations of the sag response in the respective model database subsets.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4215854&req=5

pone-0106567-g007: Hyperpolarization-induced sag response varies as a function of Ih maximum conductance density and somatodendritic distribution in models.Plots of the average sag response (mV) of model outputs as recorded in the soma as a function of different Ih maximum conductance density values across different model subsets. The general and restricted subsets of highly-ranked models with Ih in soma and dendrites are shown in red and green, respectively (“General S+D” and “Restricted S+D”, respectively, in the figure legend). The general and restricted subsets of highly-ranked models with Ih in soma only are shown in blue and black, respectively (“General S” and “Restricted S”, respectively, in the figure legend). Error bars denote standard deviations of the sag response in the respective model database subsets.
Mentions: Close examination of our highly-ranked models revealed that they did not adequately capture the hyperpolarization-induced “sag” response typically observed in O-LM cell experimental data. This can be seen in Fig. 2, where the biological cells (Fig. 2D,E) show larger sag as compared with the highly-ranked models (e.g., Fig. 2A). Specifically, this measure, PulsePotSag, has a mean of 14.2 mV and a standard deviation of 3.1 mV in the experimental dataset (see Table S1), whereas its value maximally approaches 8 mV in any of the models. This is shown in Fig. 7 where this measure is plotted for general and restricted sets, and for models with or without dendritic Ih. Considering the models without dendritic Ih, we see that as the Ih conductance density increases, the sag amplitude also increases. One might think that if we simply increased this value more, the sag amplitudes in the models could better represent those seen in experiment. However, this is not the case, as an earlier version of our model database, with larger Ih conductances, exhibited unacceptable models (not shown) when the Ih maximal conductance densities were larger than 0.5 pS/µm2, which is the upper range of values in the current database. In other words, this increase in sag amplitude with increasing Ih conductance is due to a balanced increase of Ih conductance, as other conductances in the variety of models are not the same. Now, considering the models with dendritic Ih, a larger sag amplitude can be obtained, but with the restricted set, models do not possess Ih maximum conductance densites greater than 0.1 pS/µm2 (Fig. 7, green line). Again, this increase in sag amplitude with larger Ih conductances is a balanced response. We note that these observations are a result of our database analyses, and would not have been feasible to uncover using hand-tuned modeling. We further note that our database design of models with and without dendritic Ih allowed us to easily examine what differences might exist between the two cases and to clearly show that dendritic Ih models are better at capturing the sag amplitude feature. However, as noted above, the sag amplitude feature is a clear limitation of the models (Fig. 1, Step 4(ii)).

Bottom Line: Models were quantified and ranked based on minimal error compared to a dataset of O-LM cell electrophysiological properties.Co-regulatory balances between conductances were revealed, two of which were dependent on the presence of dendritic Ih.These findings inform future experiments that differentiate between somatic and dendritic Ih, thereby continuing a cycle between model and experiment.

View Article: PubMed Central - PubMed

Affiliation: Toronto Western Research Institute, University Health Network, Toronto, Ontario, Canada; Department of Physiology, University of Toronto, Toronto, Ontario, Canada.

ABSTRACT
Multi-compartmental models of neurons provide insight into the complex, integrative properties of dendrites. Because it is not feasible to experimentally determine the exact density and kinetics of each channel type in every neuronal compartment, an essential goal in developing models is to help characterize these properties. To address biological variability inherent in a given neuronal type, there has been a shift away from using hand-tuned models towards using ensembles or populations of models. In collectively capturing a neuron's output, ensemble modeling approaches uncover important conductance balances that control neuronal dynamics. However, conductances are never entirely known for a given neuron class in terms of its types, densities, kinetics and distributions. Thus, any multi-compartment model will always be incomplete. In this work, our main goal is to use ensemble modeling as an investigative tool of a neuron's biophysical balances, where the cycling between experiment and model is a design criterion from the start. We consider oriens-lacunosum/moleculare (O-LM) interneurons, a prominent interneuron subtype that plays an essential gating role of information flow in hippocampus. O-LM cells express the hyperpolarization-activated current (Ih). Although dendritic Ih could have a major influence on the integrative properties of O-LM cells, the compartmental distribution of Ih on O-LM dendrites is not known. Using a high-performance computing cluster, we generated a database of models that included those with or without dendritic Ih. A range of conductance values for nine different conductance types were used, and different morphologies explored. Models were quantified and ranked based on minimal error compared to a dataset of O-LM cell electrophysiological properties. Co-regulatory balances between conductances were revealed, two of which were dependent on the presence of dendritic Ih. These findings inform future experiments that differentiate between somatic and dendritic Ih, thereby continuing a cycle between model and experiment.

Show MeSH