Distinct current modules shape cellular dynamics in model neurons

Abstract

Numerous intrinsic currents are known to collectively shape neuronal membrane potential dynamics, or neuronal signatures. Although how sets of currents shape specific signatures such as spiking characteristics or oscillations has been studied individually, it is less clear how a neuron’s suite of currents jointly shape its entire set of signatures. Biophysical conductance based models of neurons represent a viable tool to address this important question. We hypothesized that currents are grouped into distinct modules that shape specific neuronal characteristics or signatures, such as resting potential, sub-threshold oscillations, and spiking waveforms, for several classes of neurons. For such a grouping to occur, the currents within one module should have minimal functional interference with currents belonging to other modules. This condition is satisfied if the gating functions of currents in the same module are grouped together on the voltage axis; in contrast, such functions are segregated along the voltage axis for currents belonging to different modules. We tested this hypothesis using four published example case models and found it to be valid for these classes of neurons. This insight into the neurobiological organization of currents also suggests an intuitive, systematic, and robust methodology to develop biophysical single cell models with multiple biological characteristics applicable for both hand- and automated- tuning approaches. We illustrate the methodology using two example case rodent pyramidal neurons, from the lateral amygdala and the hippocampus. The methodology also helped reveal that a single core compartment model could capture multiple neuronal properties. Such biophysical single compartment models have potential to improve the fidelity of large network models.

Gamma Oscillations in the Basolateral Amygdala: Biophysical Mechanisms and Computational Consequences

“…We set a cutoff of 1.5 to classify PNs adapting. Our previous PN models (Li et al, 2009; Kim et al, 2013; Feng et al, 2016) were revised to incorporate the low-threshold and high-threshold oscillations (LTOs and HTOs, respectively) reported in BLA PNs (Pape et al, 1998) and modeled recently by our group (Alturki et al, 2016). The model PNs had three compartments representing a soma (diameter, 24.75 µm; length, 25 µm), where GABAergic synapses were placed, an apical dendrite (a-dend; diameter, 3 µm and length, 270 µm) where glutamatergic synapses were located, and another dendrite (p-dend; diameter, 5 µm and length, 555 µm) to match passive properties.…”

“…All compartments had the following currents: leak ( I L ), voltage-gated persistent muscarinic ( I M ), high-voltage activated Ca 2+ ( I Ca ), spike-generating sodium ( I Na ), potassium delayed rectifier ( I DR ), A-type potassium ( I A ; Li et al, 2009; Power et al, 2011) and hyperpolarization-activated nonspecific cation ( I h ) current. In addition, the soma had a slow apamin-insensitive, voltage-independent AHP current ( I sAHP ; Power et al, 2011; Alturki et al, 2016). See Tables 1, 2 for current equations and densities.…”

Gamma Oscillations in the Basolateral Amygdala: Localization, Microcircuitry, and Behavioral Correlates

“…Single-cell models. Single-cell models were developed using the Hodgkin-Huxley formulation and a segregation technique (Alturki et al, 2016). The PN model has three compartments and 16 segments in total (soma with 1 segment: diameter, 15 mm; length, 15 mm; apical dendrite with 8 segments: diameter, 3 mm; length, 270 mm; proximal dendrites with 7 segments: diameter, 5 mm; length, 555 mm).…”

Comparison of low-power, high-frequency and temporally precise optogenetic inhibition of spiking in NpHR, eNpHR3.0 and Jaws-expressing neurons

“…where, C m is the membrane capacitance, and I DC is the external constant DC bias current that controls the excitability of the neuron, and I ionic is the sum of the membrane ion-channel currents (I , Na I , Kdr I , H I , CaL I KD and I L ) [40][41][42].…”

“…The voltage-dependent functions and values of parameters are given in tables 2 and 3, respectively [40,41]. A time-step of 0.01 ms has been used for all simulations in MATLAB R2015a.…”