All simulations were performed using NEURON, which is embedded in Python 2.10 (Hines et al.,
2009). The backward Euler method was used for numerical integration with a time step of 0.025 ms. Two full-morphology compartmental models of rat CA1 pyramidal cells (Kim et al.,
2015; Magó et al.,
2020) were used for the simulations of the LTP experiments. The simulation files of the Kim et al. (
2015) CA1 model were downloaded from ModelDB (
https://modeldb.science/), accession number 184054. We added 150 excitatory synapses, randomly distributed on the apical tuft dendrites of the model (Fig.
2a). While spines were not explicitly modelled, the associated surface area was accounted for by adjusting the specific membrane resistivity (R
m) and specific membrane capacitance (C
m) of compartments located more than 100 μm from the soma, which were multiplied by a factor of two. Each synapse was composed of an AMPA and an NMDA conductance, simulated by the sum of two exponential functions with rise time and decay time constants of 0.2 and 2 ms for AMPA (Katz et al.,
2009) and 1 and 50 ms for NMDA (Spruston et al.,
1995). Initial peak conductances were randomly selected from a lognormal distribution (mean 0.18, sigma 0.35 nS) for both AMPA and NMDA synapses (Rößler et al.,
2023). The voltage-dependent magnesium block of the NMDAR was simulated using the equation:
\({g}_{Mg}={\left[1+0.2801\times {Mg}_{ext}^{2+}\times exp\left(-0.062\times \left(V-10\right)\right)\right]}^{-1}\), where
\({Mg}_{ext}^{2+}=1\) mM is the Mg
2+ concentration in the bath and
\(V\) is the local dendritic voltage (Kim et al.,
2015). In addition, we decided to modify the model by turning off the slow inactivation of Na
v channels, which resulted in a better fit to the experimental data. This modification is supported by a review of the literature and published models of CA1 cells (Bloss et al.,
2018; Jarsky et al.,
2005), as the presence or absence of slow inactivation in sodium channels varies across different neuronal models and experimental observations.
The model of Magó et al. (
2020) from the ModelDB (accession number 265511) included synaptic conductances: AMPA had a rise time of 0.1 ms, a decay time of 1 ms, and a maximum conductance of 0.6 nS, while NMDA had a rise time of 2 ms, a decay time of 50 ms, and a maximum conductance of 0.8 nS. The voltage-dependent magnesium block was simulated using the equation
\({g}_{Mg}={g}_{0}{\left(1+{Mg}_{ext}^{2+}/4.3\times exp\left(-0.071\times V\right)\right)}^{-1}\) where
\({Mg}_{ext}^{2+}=1\) mM is the Mg
2+ concentration in the bath and
\(V\) is the local dendritic voltage (Magó et al.,
2020). In this model, synapses were placed on high-impedance dendritic spines consisting of a spine neck (length: 1.58 μm; diameter: 0.077 μm) and a spine head (length: 0.5 μm; diameter: 0.5 μm) with a total neck resistance of ~ 500MΩ (Harnett et al.,
2012). Two, three, four or eight spines were placed on distal dendritic segments of 5 selected perisomatic dendrites (
x = 0.96, Fig.
3a). To account for spines, C
m was increased, and R
m was decreased by a factor of 2 in dendritic compartments beyond 100 μm from the soma (Magó et al.,
2020).