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Dendritic distributions of I h channels in experimentally-derived multi-compartment models of oriens-lacunosum/moleculare (O-LM) hippocampal interneurons.

Sekulić V, Chen TC, Lawrence JJ, Skinner FK - Front Synaptic Neurosci (2015)

Bottom Line: We found that the best O-LM models that included uniformly distributed h-channels in the dendrites could not fully capture the "sag" response.In tuning our models, we found that different kinetics and non-uniform distributions could better reproduce experimental O-LM cell responses.Although the present results were morphology-dependent, our work shows that it should be possible to determine the distributions and characteristics of O-LM cells with recordings and morphologies from the same cell.

View Article: PubMed Central - PubMed

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

ABSTRACT
The O-LM cell type mediates feedback inhibition onto hippocampal pyramidal cells and gates information flow in the CA1. Its functions depend on the presence of voltage-gated channels (VGCs), which affect its integrative properties and response to synaptic input. Given the challenges associated with determining densities and distributions of VGCs on interneuron dendrites, we take advantage of computational modeling to consider different possibilities. In this work, we focus on hyperpolarization-activated channels (h-channels) in O-LM cells. While h-channels are known to be present in O-LM cells, it is unknown whether they are present on their dendrites. In previous work, we used ensemble modeling techniques with experimental data to obtain insights into potentially important conductance balances. We found that the best O-LM models that included uniformly distributed h-channels in the dendrites could not fully capture the "sag" response. This led us to examine activation kinetics and non-uniform distributions of h-channels in the present work. In tuning our models, we found that different kinetics and non-uniform distributions could better reproduce experimental O-LM cell responses. In contrast to CA1 pyramidal cells where higher conductance densities of h-channels occur in more distal dendrites, decreasing conductance densities of h-channels away from the soma were observed in O-LM models. Via an illustrative scenario, we showed that having dendritic h-channels clearly speeds up back-propagating action potentials in O-LM cells, unlike when h-channels are present only in the soma. Although the present results were morphology-dependent, our work shows that it should be possible to determine the distributions and characteristics of O-LM cells with recordings and morphologies from the same cell. We hypothesize that h-channels are distributed in O-LM cell dendrites and endow them with particular synaptic integration properties that shape information flow in hippocampus.

No MeSH data available.


Plots of the activation time constant curves of Ih for the models after optimization. Curves showing the time constant of activation for Ih, or τ±vs. voltage on a semi-log plot, for models with both morphologies and Rm, Cm, t1, t2, …, t8, and dendritic scaling factor kd for dendritic distribution for Gh parameters optimized against both experimental traces. Models optimized against experimental trace 4525#4 with morphology 1 (A) and 2 (C); models optimized against experimental trace 4610#2 with morphology 1 (B) and 2 (D).
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Figure 8: Plots of the activation time constant curves of Ih for the models after optimization. Curves showing the time constant of activation for Ih, or τ±vs. voltage on a semi-log plot, for models with both morphologies and Rm, Cm, t1, t2, …, t8, and dendritic scaling factor kd for dendritic distribution for Gh parameters optimized against both experimental traces. Models optimized against experimental trace 4525#4 with morphology 1 (A) and 2 (C); models optimized against experimental trace 4610#2 with morphology 1 (B) and 2 (D).

Mentions: The activation time constants from the resulting fits are shown in Figure 8 on a semi-log plot. The original activation time constant used in Saraga et al. (2003) is also plotted for comparison purposes. We see that the activation time constant is similar to the original Saraga model for most of the portion of the membrane potential corresponding to when Ih is maximally active. This is from about −150 to −90 mV, as determined from r∞, the equation for the steady-state activation of Ih (see Models and Methods, also Figure 8A). Since the optimizations were done in these hyperpolarized ranges (Figure 3), this is somewhat expected. Otherwise, however, there is considerable variation. Taking into account the contributions of the various t1, t2, …, t8 parameters to the time constant (τ), it is also clear that the left hand side of the time constant curve is more constrained. That is, from Table 4, we note that t3, t4, and t8 had small variances relative to their mean values, whereas the other parameters had large variances. However, since only t3 and t8 can be considered as independent, we can mainly point to the (left hand side) horizontal scaling that seems to be a constrained aspect of the time constant curve. See Supplementary Material for more details. t8 represents the minimum τ-value, and is quite constrained. This suggests that the minimum time constant is relatively robust at about 100 ms.


Dendritic distributions of I h channels in experimentally-derived multi-compartment models of oriens-lacunosum/moleculare (O-LM) hippocampal interneurons.

Sekulić V, Chen TC, Lawrence JJ, Skinner FK - Front Synaptic Neurosci (2015)

Plots of the activation time constant curves of Ih for the models after optimization. Curves showing the time constant of activation for Ih, or τ±vs. voltage on a semi-log plot, for models with both morphologies and Rm, Cm, t1, t2, …, t8, and dendritic scaling factor kd for dendritic distribution for Gh parameters optimized against both experimental traces. Models optimized against experimental trace 4525#4 with morphology 1 (A) and 2 (C); models optimized against experimental trace 4610#2 with morphology 1 (B) and 2 (D).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4343010&req=5

Figure 8: Plots of the activation time constant curves of Ih for the models after optimization. Curves showing the time constant of activation for Ih, or τ±vs. voltage on a semi-log plot, for models with both morphologies and Rm, Cm, t1, t2, …, t8, and dendritic scaling factor kd for dendritic distribution for Gh parameters optimized against both experimental traces. Models optimized against experimental trace 4525#4 with morphology 1 (A) and 2 (C); models optimized against experimental trace 4610#2 with morphology 1 (B) and 2 (D).
Mentions: The activation time constants from the resulting fits are shown in Figure 8 on a semi-log plot. The original activation time constant used in Saraga et al. (2003) is also plotted for comparison purposes. We see that the activation time constant is similar to the original Saraga model for most of the portion of the membrane potential corresponding to when Ih is maximally active. This is from about −150 to −90 mV, as determined from r∞, the equation for the steady-state activation of Ih (see Models and Methods, also Figure 8A). Since the optimizations were done in these hyperpolarized ranges (Figure 3), this is somewhat expected. Otherwise, however, there is considerable variation. Taking into account the contributions of the various t1, t2, …, t8 parameters to the time constant (τ), it is also clear that the left hand side of the time constant curve is more constrained. That is, from Table 4, we note that t3, t4, and t8 had small variances relative to their mean values, whereas the other parameters had large variances. However, since only t3 and t8 can be considered as independent, we can mainly point to the (left hand side) horizontal scaling that seems to be a constrained aspect of the time constant curve. See Supplementary Material for more details. t8 represents the minimum τ-value, and is quite constrained. This suggests that the minimum time constant is relatively robust at about 100 ms.

Bottom Line: We found that the best O-LM models that included uniformly distributed h-channels in the dendrites could not fully capture the "sag" response.In tuning our models, we found that different kinetics and non-uniform distributions could better reproduce experimental O-LM cell responses.Although the present results were morphology-dependent, our work shows that it should be possible to determine the distributions and characteristics of O-LM cells with recordings and morphologies from the same cell.

View Article: PubMed Central - PubMed

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

ABSTRACT
The O-LM cell type mediates feedback inhibition onto hippocampal pyramidal cells and gates information flow in the CA1. Its functions depend on the presence of voltage-gated channels (VGCs), which affect its integrative properties and response to synaptic input. Given the challenges associated with determining densities and distributions of VGCs on interneuron dendrites, we take advantage of computational modeling to consider different possibilities. In this work, we focus on hyperpolarization-activated channels (h-channels) in O-LM cells. While h-channels are known to be present in O-LM cells, it is unknown whether they are present on their dendrites. In previous work, we used ensemble modeling techniques with experimental data to obtain insights into potentially important conductance balances. We found that the best O-LM models that included uniformly distributed h-channels in the dendrites could not fully capture the "sag" response. This led us to examine activation kinetics and non-uniform distributions of h-channels in the present work. In tuning our models, we found that different kinetics and non-uniform distributions could better reproduce experimental O-LM cell responses. In contrast to CA1 pyramidal cells where higher conductance densities of h-channels occur in more distal dendrites, decreasing conductance densities of h-channels away from the soma were observed in O-LM models. Via an illustrative scenario, we showed that having dendritic h-channels clearly speeds up back-propagating action potentials in O-LM cells, unlike when h-channels are present only in the soma. Although the present results were morphology-dependent, our work shows that it should be possible to determine the distributions and characteristics of O-LM cells with recordings and morphologies from the same cell. We hypothesize that h-channels are distributed in O-LM cell dendrites and endow them with particular synaptic integration properties that shape information flow in hippocampus.

No MeSH data available.