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Network models provide insights into how oriens-lacunosum-moleculare and bistratified cell interactions influence the power of local hippocampal CA1 theta oscillations.

Ferguson KA, Huh CY, Amilhon B, Manseau F, Williams S, Skinner FK - Front Syst Neurosci (2015)

Bottom Line: We found that our models operate in regimes that could be distinguished by whether OLM cells minimally or strongly affected the power of network theta oscillations due to balances that, respectively, allow compensatory effects or not.Inactivation of OLM cells could result in no change or even an increase in theta power.We predict that the dis-inhibitory effect of OLM cells to BiCs to pyramidal cell interactions plays a critical role in the resulting power of network theta oscillations.

View Article: PubMed Central - PubMed

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

ABSTRACT
Hippocampal theta is a 4-12 Hz rhythm associated with episodic memory, and although it has been studied extensively, the cellular mechanisms underlying its generation are unclear. The complex interactions between different interneuron types, such as those between oriens-lacunosum-moleculare (OLM) interneurons and bistratified cells (BiCs), make their contribution to network rhythms difficult to determine experimentally. We created network models that are tied to experimental work at both cellular and network levels to explore how these interneuron interactions affect the power of local oscillations. Our cellular models were constrained with properties from patch clamp recordings in the CA1 region of an intact hippocampus preparation in vitro. Our network models are composed of three different types of interneurons: parvalbumin-positive (PV+) basket and axo-axonic cells (BC/AACs), PV+ BiCs, and somatostatin-positive OLM cells. Also included is a spatially extended pyramidal cell model to allow for a simplified local field potential representation, as well as experimentally-constrained, theta frequency synaptic inputs to the interneurons. The network size, connectivity, and synaptic properties were constrained with experimental data. To determine how the interactions between OLM cells and BiCs could affect local theta power, we explored how the number of OLM-BiC connections and connection strength affected local theta power. We found that our models operate in regimes that could be distinguished by whether OLM cells minimally or strongly affected the power of network theta oscillations due to balances that, respectively, allow compensatory effects or not. Inactivation of OLM cells could result in no change or even an increase in theta power. We predict that the dis-inhibitory effect of OLM cells to BiCs to pyramidal cell interactions plays a critical role in the resulting power of network theta oscillations. Overall, our network models reveal a dynamic interplay between different classes of interneurons in influencing local theta power.

No MeSH data available.


Firing rates and spike characteristics of SOM+ interneuron model closely matches experiment An example intracellular recording of a SOM+ cell during current clamp with applied current of 61 pA (top) is compared with the firing of our SOM+ cell model with an applied current of 61 pA (bottom). The spike characteristics and firing rates of the model closely match those of the experiment.
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Figure 2: Firing rates and spike characteristics of SOM+ interneuron model closely matches experiment An example intracellular recording of a SOM+ cell during current clamp with applied current of 61 pA (top) is compared with the firing of our SOM+ cell model with an applied current of 61 pA (bottom). The spike characteristics and firing rates of the model closely match those of the experiment.

Mentions: The model parameters were set by our experimentally determined intrinsic properties (as summarized in Table 1), and are given in Table 2. Thus, we set vr = −62.2 mV, vt = −53.3 mV, c = −69.9 mV, vpeak = 6.4 mV, and khigh = 10 nS/mV in our models. The remaining model parameters were chosen such that the rheobase and initial and final f-I curves of the SOM+ cell model is similar to those of our recordings. Thus, we had to set our membrane capacitance to Cm = 180 pF. We determined the rheobase current and the slope of the initial and final f-I curve over 40 Hz (using a least squares approach) for each model in order to settle upon a final model in which our initial and final f-I slopes and rheobase approximated that which we determined biologically. We determined that a = 0.0001 ms −1, b = 1 nS, klow = 2, nS/mV and d = 2.6 pA. This gave us a model f-I initial slope of 0.2422, a final slope of 0.1511, and a rheobase of ~0 pA (see Figure 1). As shown in Figure 2, the model firing characteristics are similar to the experimental recordings.


Network models provide insights into how oriens-lacunosum-moleculare and bistratified cell interactions influence the power of local hippocampal CA1 theta oscillations.

Ferguson KA, Huh CY, Amilhon B, Manseau F, Williams S, Skinner FK - Front Syst Neurosci (2015)

Firing rates and spike characteristics of SOM+ interneuron model closely matches experiment An example intracellular recording of a SOM+ cell during current clamp with applied current of 61 pA (top) is compared with the firing of our SOM+ cell model with an applied current of 61 pA (bottom). The spike characteristics and firing rates of the model closely match those of the experiment.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4528165&req=5

Figure 2: Firing rates and spike characteristics of SOM+ interneuron model closely matches experiment An example intracellular recording of a SOM+ cell during current clamp with applied current of 61 pA (top) is compared with the firing of our SOM+ cell model with an applied current of 61 pA (bottom). The spike characteristics and firing rates of the model closely match those of the experiment.
Mentions: The model parameters were set by our experimentally determined intrinsic properties (as summarized in Table 1), and are given in Table 2. Thus, we set vr = −62.2 mV, vt = −53.3 mV, c = −69.9 mV, vpeak = 6.4 mV, and khigh = 10 nS/mV in our models. The remaining model parameters were chosen such that the rheobase and initial and final f-I curves of the SOM+ cell model is similar to those of our recordings. Thus, we had to set our membrane capacitance to Cm = 180 pF. We determined the rheobase current and the slope of the initial and final f-I curve over 40 Hz (using a least squares approach) for each model in order to settle upon a final model in which our initial and final f-I slopes and rheobase approximated that which we determined biologically. We determined that a = 0.0001 ms −1, b = 1 nS, klow = 2, nS/mV and d = 2.6 pA. This gave us a model f-I initial slope of 0.2422, a final slope of 0.1511, and a rheobase of ~0 pA (see Figure 1). As shown in Figure 2, the model firing characteristics are similar to the experimental recordings.

Bottom Line: We found that our models operate in regimes that could be distinguished by whether OLM cells minimally or strongly affected the power of network theta oscillations due to balances that, respectively, allow compensatory effects or not.Inactivation of OLM cells could result in no change or even an increase in theta power.We predict that the dis-inhibitory effect of OLM cells to BiCs to pyramidal cell interactions plays a critical role in the resulting power of network theta oscillations.

View Article: PubMed Central - PubMed

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

ABSTRACT
Hippocampal theta is a 4-12 Hz rhythm associated with episodic memory, and although it has been studied extensively, the cellular mechanisms underlying its generation are unclear. The complex interactions between different interneuron types, such as those between oriens-lacunosum-moleculare (OLM) interneurons and bistratified cells (BiCs), make their contribution to network rhythms difficult to determine experimentally. We created network models that are tied to experimental work at both cellular and network levels to explore how these interneuron interactions affect the power of local oscillations. Our cellular models were constrained with properties from patch clamp recordings in the CA1 region of an intact hippocampus preparation in vitro. Our network models are composed of three different types of interneurons: parvalbumin-positive (PV+) basket and axo-axonic cells (BC/AACs), PV+ BiCs, and somatostatin-positive OLM cells. Also included is a spatially extended pyramidal cell model to allow for a simplified local field potential representation, as well as experimentally-constrained, theta frequency synaptic inputs to the interneurons. The network size, connectivity, and synaptic properties were constrained with experimental data. To determine how the interactions between OLM cells and BiCs could affect local theta power, we explored how the number of OLM-BiC connections and connection strength affected local theta power. We found that our models operate in regimes that could be distinguished by whether OLM cells minimally or strongly affected the power of network theta oscillations due to balances that, respectively, allow compensatory effects or not. Inactivation of OLM cells could result in no change or even an increase in theta power. We predict that the dis-inhibitory effect of OLM cells to BiCs to pyramidal cell interactions plays a critical role in the resulting power of network theta oscillations. Overall, our network models reveal a dynamic interplay between different classes of interneurons in influencing local theta power.

No MeSH data available.