Homogeneous and narrow bandwidth of spike initiation in rat L1 cortical interneurons Christophe Verbist Stefano Borda Bossana Michele Giugliano 10.6084/m9.figshare.12091047.v1 https://figshare.com/articles/dataset/Homogeneous_and_narrow_bandwidth_of_spike_initiation_in_rat_L1_cortical_interneurons/12091047 Cortical layer 1 contains a population of GABAergic interneurons, considered a key component of information integration, processing, and relaying in neocortical networks. In fact, L1 interneurons combine top-down information with feed-forward sensory inputs in layer 2/3 and 5 pyramidal cells, while filtering their incoming signals. Despite L1 importance for network emerging phenomena, little is known on the dynamics of the spike initiation and encoding properties of its neurons. Using acute brain tissue slices from the rat neocortex, combined with the analysis of an existing database of model neurons, we investigated the dynamical transfer properties of these cells, sampling the entire population of known “electrical classes”, and comparing experiments and model predictions. We found the bandwidth of spike initiation to be significantly narrower than in L2/3 and 5 pyramidal cells, with values below , but without significant heterogeneity in the cell response properties, across distinct electrical types. The upper limit of the neuronal bandwidth was significantly correlated to the mean firing rate, as anticipated from theoretical studies but not reported for pyramidal cells. Finally, at high spectral frequencies, the magnitude of the neuronal response attenuated as a power-law, with an exponent significantly smaller than what reported for pyramidal neurons and reminiscent of the dynamics of a “leaky” integrate-and-fire model of spike initiation. Finally, most of our <i>in vitro</i> results matched quantitatively the numerical simulations of the models, as a further contribution to independently validate the models against novel experimental data. 2020-04-22 08:25:32 noise interneuron spike-triggered average dynamics transfer function Neuroscience