Directional selectivity (DS) is known to increase significantly in ferrets during two weeks after eye opening and it has been shown to strongly depend on visual experience (Li et al. 2008, Nature). Such selectivity to features of the input is traditionally assumed to indicate the functional maturity of the visual system, however, this assumption has not been confirmed directly. Recently, a measurement for assessing functional maturity has been put forth by Berkes et al. (2011, Science) based on the idea that a mature visual system is optimized for probabilistically encoding natural stimuli. They use Kulback-Leibler divergence (KL) to quantify dissimilarities in the statistical structure of multi-neuron firing patterns in V1 of awake ferrets acquired under different stimulus conditions. The distribution of firing patterns acquired in complete darkness (spontaneous activity) reflects the prior probability distribution over visual features that is unconstrained by visual input. According to the probabilistic approach, the more the distribution of spontaneous activity is similar to the distribution of average activity evoked by naturalistic stimuli, the more the visual system is adapted to the statistics of the visual environment. Berkes et al. (2011) have shown that the dissimilarity of these two distributions monotonically decreases with animal age, supporting the notion of gradual maturation of the system. However, due to constraints of the experimental design it was not possible to determine the role that visual experience plays in this optimization process. In the present study, we explored both the role of experience in this maturation, and the relationship between KL and the more commonly used measure of functional maturity based on direction selectivity. Specifically, we acquired measurements of spontaneous and visually evoked activity in awake, and directional selectivity tuning in anesthetized visually naïve ferrets (mean age p30) using extracellular 16 channel microwire array electrodes chronically implanted into V1. Immediately after acquiring these measurements, the animals were randomly assigned to one of three experimental conditions: (1) visual training with drifting gratings while anesthetized, (2) visual training with naturalistic movies while anesthetized or (3) no visual training while awake. After 12 hours of training in the assigned experimental condition, both measurements were acquired again. This experimental design allowed us to correlate the two measurements of visual maturity, and explore the role of visual experience in the process of optimizing an immature visual system to the statistics of the visual environment.