Modeling Synapses of CA1 Pyramidal Neurons


  • František Michal Sebestyén Comenius University in Bratislava


CA1 Pyramidal Neurons

There are multiple theories regarding the role of the hippocampus - the part of the brain renowned for its high levels of plasticity. Biologically realistic modeling provides another method of investigating its behavior. CA1 pyramidal cells are the principal cells in the CA1 region of the hippocampus. They are characterized by the pyramidal soma, single axon, large apical dendrite, and multiple small basal dendrites. This paper is concerned with simulating the distribution of the synapses on the CA1 pyramidal neuron.

Modeling of Synaptic Plasticity

Neuronal computation consists of the integration of multiple synaptic inputs. Synapses are distributed over the whole dendritic tree, and due to the electrical properties of dendrites, synaptic potentials are dramatically attenuated as they propagate along the dendrites toward the soma. One of the compensatory mechanisms is distance-dependent synaptic scaling [1], which we implemented in our model.

We used the reduced-morphology model of the CA1 pyramidal cell [2]. The model was previously successfully validated and is biophysically realistic. In the model, we distributed excitatory synapses while maintaining synaptic scaling.

Synapses changed their weights according to the Event Timing-Dependent Plasticity (ETDP) rule, in which the presynaptic event is a presynaptic spike, and the postsynaptic event happens, when the local postsynaptic potential (PSP) exceeds a certain voltage threshold. In addition, we used the BCM-like metaplasticity as a global homeostatic mechanism [3].

Results & Implications

We performed a series of experiments in neuronal simulation software NEURON. Using the meta-ETDP synaptic plasticity rule and realistic distribution of synapses, the model was dynamically stable during ongoing in vivo like spontaneous activity. This finding is important from the point of view of the stability-plasticity dilemma because synapses should change their weights only when a significant input (pattern) is presented.


[1] D. Nicholson, R. Trana, Y. Katz, W. Kath, N. Spruston and Y. Geinisman, "Distance-Dependent Differences in Synapse Number and AMPA Receptor Expression in Hippocampal CA1 Pyramidal Neurons", Neuron, vol. 50, no. 3, pp. 431-442, 2006. Available: 10.1016/j.neuron.2006.03.022 [Accessed 31 May 2022].

[2] M. Tomko, L. Benuskova and P. Jedlicka, "A new reduced-morphology model for CA1 pyramidal cells and its validation and comparison with other models using HippoUnit", Scientific Reports, vol. 11, no. 1, 2021. Available: 10.1038/s41598-021-87002-7 [Accessed 31 May 2022].

[3] P. Jedlicka, L. Benuskova and W. Abraham, "A Voltage-Based STDP Rule Combined with Fast BCM-Like Metaplasticity Accounts for LTP and Concurrent “Heterosynaptic” LTD in the Dentate Gyrus In Vivo", PLOS Computational Biology, vol. 11, no. 11, p. e1004588, 2015. Available: 10.1371/journal.pcbi.1004588 [Accessed 31 May 2022].