This is the readme for models associated with the paper Kondgen H, Geisler C, Fusi S, Wang XJ, Luscher HR, Giugliano M (2008) The dynamical response properties of neocortical neurons to temporally modulated noisy inputs in vitro. Cereb Cortex 18:2086-9 Neocortical neurons are classified by their current-frequency relationships. This is a static description and it may be inadequate to interpret neuronal responses to time-varying stimuli. Theoretical studies (Brunel et al., 2001; Fourcaud-Trocme et al. 2003; Fourcaud-Trocme and Brunel 2005; Naundorf et al. 2005) suggested that single-cell dynamical response properties are necessary to interpret ensemble responses to fast input transients. Further, it was shown that input-noise linearizes and boosts the response bandwidth, and that the interplay between the barrage of noisy synaptic currents and the spike-initiation mechanisms determine the dynamical properties of the firing rate. In order to allow a reader to explore such simulations, we prepared a simple NEURON implementation of the experiments performed in Kondgen et al., 2008 (see also Fourcaud-Trocme al. 2003; Fourcaud-Trocme and Brunel 2005). In addition, we provide sample MATLAB routines for exploring the sandwich model proposed in Kondgen et al., 2008, employing a simple frequdency-domain filtering. The simulations and the MATLAB routines are based on the linear response properties of layer 5 pyramidal cells estimated by injecting a superposition of a small-amplitude sinusoidal wave and a background noise, as in Kondgen et al., 2008. Similarly to the experiments performed there, the simulations quantify the evoked firing probability across many stimulation trials and a wide range of oscillation frequencies (1-1000 Hz). The (dynamical) response is quantified in terms of amplitude and phase-shift, while changing noise statistics. Neocortical neurons track unexpectedly fast transients, as their response amplitude has no attenuation up to 200 Hz. This cut-off frequency is higher than the limits set by passive membrane properties (~50 Hz) and average firing rate (~20 Hz) and is not affected by the rate of change of the input. These model files were supplied by Michele Giugliano. A short demo has been created by Michele Giugliano & Vincent Delattre Brain Mind Institute, EPFL of Lausanne Demonstrating: 1) noisy stimulation, modulated in time 2) instantaneous firing rate, estimate and quantitative fit The demo uses a single-compartmental, conductance-based model neuron in a current-clamp stimulation. Each spike is counted and has it's time recorded, then the output firing rate is graphically compared with the input. When started (Click the run button) the simulation produces the following graphs of spikes and injected current In black, the instantaneous firing rate [Hz] is indicated (i.e. the PSTH) In red, the best fit sinusoid. In blue the sinusoid is displayed which is subsequently modified by noise to produce the input.