According to recently emerging views on visual cortical processing, activity in the primary visual cortex is governed by dynamically changing internal states of the system modulated by the incoming information rather than being fully determined by the visual stimulus. We analyzed systematically the dynamical nature of these states and the conditions required for their emergence. Multi-electrode recordings in the primary visual cortex of awake behaving ferrets (N=30) were analyzed after normal and visually deprived development at different ages spanning the range between postnatal day (P) 24 and P170. Visual deprivation has been achieved by bilateral lid suture up to the time of the visual tests. Multi-unit recordings were obtained in three different conditions: in the dark, while the animals watched random noise sequences, and while they saw a natural movie. 10-second segments of continuous recordings under these conditions were used to train two alternative state-dependent models, one based on Hidden Markov modeling that assumes internal dynamical dependencies among subsequent internal states and the other based on Independent Component Analysis which does not assume such dependencies. HMM significantly outperformed ICA (p<0.001) for both normal and lid sutured animals. In addition, HMM performance increased with age (p<0.001), more so than ICA did (p<0.001). We also assessed the similarity between different underlying states across different conditions (Movie, Noise and Dark), by computing the Kullback-Leibler distance between the probability distribution of the observed population activity generated by the underlying states. We found that, in general, similarity between underlying states across conditions strongly increased with age for normal animals, but this similarity remained significantly lower than that for lid sutured animals (p<0.0001). In addition, the number of transitions in the oldest age group was higher in normal animals compared to lid sutured ones (p<0.001). The result suggests that positing dynamic underlying states that emerge with age and can capture the behavior of cell assemblies is critical in characterizing the neural activity in the primary visual cortex. However, both the behavior and the emergence of these states depend only partially on proper visual input, and it is determined to a large extent by internal processes.