Spike-response properties of neocortical cells:an in silico study

The input-output (I-O) properties of cortical excitatory neurons have been intensively studied in the past. Recently, theoretical work has demonstrated that the I-O properties in the high-frequency (HF) domain are not universally determined solely by neuronal properties, but also depend on the interplay between these neuronal properties and input statistics. This study aims to validate the aforementioned theoretical work using an extensive set of numerical simulations on state-of-the-art multi-compartmental cortical neuron models from the Blue Brain Project (BBP). The simulations are conducted using NEURON software with Python and Julia on high-performance computers (HPC). The results reveal variations in the strength of the hypothesized effect among different neurons, with some neuronal models not exhibiting this effect at all. Additionally, a notable anti-correlation has been identified between total dendritic length (TDL) and sensitivity to input statistics. This suggests that more extensive neurons are less sensitive, or even insensitive, to the theorized effect. Instead, they tend to exhibit the previously established universality behavior in the HF domain.