Simple, biologically-constrained CA1 pyramidal cell models using an intact, whole hippocampus context.
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Thus, simple models are preferable, but at the same time they need to have a clear, experimental basis so as to allow physiologically based understandings to emerge.In this article, we describe the development of simple models of CA1 pyramidal cells, as derived in a well-defined experimental context of an intact, whole hippocampus preparation expressing population oscillations.These models are based on the intrinsic properties and frequency-current profiles of CA1 pyramidal cells, and can be used to build, fully examine, and analyze large networks.
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Affiliation: Toronto Western Research Institute, University Health Network, Toronto, Ontario, M5T 2S8, Canada ; Department of Physiology, University of Toronto, Toronto, Ontario, M5S 1A1, Canada.
ABSTRACT
The hippocampus is a heavily studied brain structure due to its involvement in learning and memory. Detailed models of excitatory, pyramidal cells in hippocampus have been developed using a range of experimental data. These models have been used to help us understand, for example, the effects of synaptic integration and voltage gated channel densities and distributions on cellular responses. However, these cellular outputs need to be considered from the perspective of the networks in which they are embedded. Using modeling approaches, if cellular representations are too detailed, it quickly becomes computationally unwieldy to explore large network simulations. Thus, simple models are preferable, but at the same time they need to have a clear, experimental basis so as to allow physiologically based understandings to emerge. In this article, we describe the development of simple models of CA1 pyramidal cells, as derived in a well-defined experimental context of an intact, whole hippocampus preparation expressing population oscillations. These models are based on the intrinsic properties and frequency-current profiles of CA1 pyramidal cells, and can be used to build, fully examine, and analyze large networks. No MeSH data available. |
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Mentions: We found that for the two weakly adapting pyramidal cells, the slope of the linear least squares approximation of the f-I curves were 0.119 and 0.138 for the initial curves, and 0.013 and 0.044 for the final curves (values relating to experimental, data green and black inFigure 1 andFigure 4). A series of depolarizing (10 pA) steps were used to precisely determine the rheobase currents, which were 62.0 pA and -12.1 pA for the two weakly adapting cells. We kept our previously determined parameters constant (i.e.vr = -61.8 mV,vt = -57.0 mV,c = -65.8 mV,vpeak = 22.6 mV, andkhigh = 3.3 nS/mV), and set our membrane capacitance toCm = 300pA, which allowed us to obtain the gradual f-I slope. We then varied the parametersa, b, d, andklow to produce multiple models, and again determined the rheobase current and the slope of the initial and final f-I curve over 10 Hz (using a least squares approach) for each model. In addition, to obtain an appropriate rheobase current, we included a shift in the applied current (Iapplied →Iapplied +IShift). For our first model, we determined thata = 0.001ms-1, b = 3nS, klow = 0.5nS/mV,d = 5pA, andIshift = –45pA. This gave us a model f-I initial slope of 0.136, a final slope of 0.089, and a rheobase of 5 pA (see purple solid and dashed lines inFigure 4). The second weakly adapting model is identical to the first, except that we explored smallera parameter values in order to capture the gradual slope of the final f-I curve. For this model,a = 0.00008ms-1, which gave an initial f-I slope of 0.136, a final slope of 0.048, and a rheobase of 5 pA (see purple solid and magenta dashed lines inFigure 4). An example of the weak adaptation in this case is shown inFigure 5A, and rebound firing for model 1 is shown inFigure 5B. |
View Article: PubMed Central - PubMed
Affiliation: Toronto Western Research Institute, University Health Network, Toronto, Ontario, M5T 2S8, Canada ; Department of Physiology, University of Toronto, Toronto, Ontario, M5S 1A1, Canada.
No MeSH data available.