The passive properties of dendrites modulate the propagation of slowly-varying firing rate in feedforward networks.

The propagation of slowly-varying firing rates has been proved significant for the development of the central nervous system. Recent reports have shown that the membrane passive properties of dendrites play a key role in the computation of the single neuron, which is of great importance to the function of neural networks. However, it is still unclear how dendritic passive properties affect the ability of cortical networks to propagate slowly-varying spiking activity. Here, we use two-compartment biophysical models to construct multilayered feedforward neural networks (FFNs) to investigate how dendritic passive properties affect the propagation of the slow-varying inputs. In the two-compartment biophysical models, one compartment represents apical dendrites, and the other compartment describes the soma plus the axon initial segment. Area proportion occupied by somatic compartment and coupling conductance between dendritic and somatic compartments are abstracted to capture the dendritic passive properties. A time-varying signal is injected into the first layer of the FFNs and the fidelity of the signal during propagation is used to qualify the ability of the FFN to transmit wave-like signals. Numerical results reveal an optimal value of coupling conductance between dendritic and somatic compartments to maximize the fidelity of the initial spiking activity. An increase of the dendritic area enhances the initial firing rate of neurons in the first layer by increasing the response of neurons to slow-varying wave-like input, resulting in a delay of attenuation of the firing rate, thus promoting the transmission of signals in FFN. Using a mean-field approach, we examine that changes in area proportion occupied by somatic compartment and coupling conductance between dendritic and somatic compartment affect the signal propagation ability of the FFN by adjusting the input–output transform of a single neuron. With the participation of external noise, a wide range of initial firing rates maintains a unique representation during propagation, which ensures the reliable transmission of slow-varying signals in FFNs. These findings are helpful to understand how passive properties of dendrites participate in the propagation of slowly varying signals in the cerebellum. [ABSTRACT FROM AUTHOR]