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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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Inverse relationship between Ih maximum conductance densities and Ih distribution.Histograms for highly-ranked models in the general (A) and restricted (B) database subsets as a function of Ih distribution and Ih maximum conductance densities shows that highly-ranked models with somatic Ih only preferentially exhibited higher maximum conductance densities, whereas models with somatodendritic Ih preferentially exhibited lower maximum conductance densities.
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pone-0106567-g006: Inverse relationship between Ih maximum conductance densities and Ih distribution.Histograms for highly-ranked models in the general (A) and restricted (B) database subsets as a function of Ih distribution and Ih maximum conductance densities shows that highly-ranked models with somatic Ih only preferentially exhibited higher maximum conductance densities, whereas models with somatodendritic Ih preferentially exhibited lower maximum conductance densities.

Mentions: Our database was designed to address the specific question of whether Ih is present on O-LM cell dendrites, which is unknown at present (Fig. 1, Step 4(i)). As a result, of particular interest to us was the finding that two co-regulations between conductances in the models depended on the presence of dendritic Ih as described in the previous section. We found that in both the general (Fig. 6A) and restricted (Fig. 6B) subsets of appropriate O-LM cell representations, somatic Ih only models preferentially expressed higher levels of maximum conductance densities of Ih relative to those with Ih conductances uniformly distributed in both soma and dendrites. This makes sense since one would expect that a wider distribution would not need as high a density to maintain overall balances. Furthermore, there were similar amounts of highly-ranked models in both subsets of appropriate O-LM models, regardless of model morphology, that had somatic Ih only (77,806 models in the general subset) as well as somatodendritic Ih (76,194 models in the general subset). The equal likelihood of models with either distribution of Ih channels being ranked highly in the ensemble of O-LM models, given that their Ih conductance densities were appropriately balanced, therefore did not allow for a clear prediction of dendritic Ih conductances in biological O-LM cells.


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)

Inverse relationship between Ih maximum conductance densities and Ih distribution.Histograms for highly-ranked models in the general (A) and restricted (B) database subsets as a function of Ih distribution and Ih maximum conductance densities shows that highly-ranked models with somatic Ih only preferentially exhibited higher maximum conductance densities, whereas models with somatodendritic Ih preferentially exhibited lower maximum conductance densities.
© Copyright Policy
Related In: Results  -  Collection

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

pone-0106567-g006: Inverse relationship between Ih maximum conductance densities and Ih distribution.Histograms for highly-ranked models in the general (A) and restricted (B) database subsets as a function of Ih distribution and Ih maximum conductance densities shows that highly-ranked models with somatic Ih only preferentially exhibited higher maximum conductance densities, whereas models with somatodendritic Ih preferentially exhibited lower maximum conductance densities.
Mentions: Our database was designed to address the specific question of whether Ih is present on O-LM cell dendrites, which is unknown at present (Fig. 1, Step 4(i)). As a result, of particular interest to us was the finding that two co-regulations between conductances in the models depended on the presence of dendritic Ih as described in the previous section. We found that in both the general (Fig. 6A) and restricted (Fig. 6B) subsets of appropriate O-LM cell representations, somatic Ih only models preferentially expressed higher levels of maximum conductance densities of Ih relative to those with Ih conductances uniformly distributed in both soma and dendrites. This makes sense since one would expect that a wider distribution would not need as high a density to maintain overall balances. Furthermore, there were similar amounts of highly-ranked models in both subsets of appropriate O-LM models, regardless of model morphology, that had somatic Ih only (77,806 models in the general subset) as well as somatodendritic Ih (76,194 models in the general subset). The equal likelihood of models with either distribution of Ih channels being ranked highly in the ensemble of O-LM models, given that their Ih conductance densities were appropriately balanced, therefore did not allow for a clear prediction of dendritic Ih conductances in biological O-LM cells.

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