## 5 Discussion, Conclusions and Future Work  
We performed the presented preparatory experiments to get insights into the human brain perception of synthetic color fractal and natural textures and the freely reasoning over the images complexity, all by using a less informative EEG setup, in order to form the ground basis for a more in-depth study and investigate if a less channels EEG system is able to provide any reliable information on visual perception and reasoning of image complexity. We equested to find and quantify any differences between the preliminary perception of synthetic color fractal and natural textures with EEG in short intervals up to 1 s.  
Firstly, the analysis showed that the fractal images may constitute stimuli for more throughout studies, while due to their capturing properties we could investigate their capacity to induce brain oscillations, and even further they presented interest for the participants. In more detail, the observed neurophysiological facts in the ERPs suggests that the primary visual processing of the stimuli (P200) is differentiated for the three types of images (Uni, Nat, Frac), while the perception, interpretation and reasoning over the complexity of textures (P300), shows higher discriminability involving different thought processes. The gradual increased amplitude ERP responses currently observed tend to be related to more complex processes and stronger attentional demand, as reported in the scientific literature [29]. Even though the texture complexity does not vary according to the CFD measure between Nat and Frac images, but only the amount of colors as indicated by color entropy (CE), perceiving the complexity of fractal images by the human brain seem to require more thought processes. These could relate to the higher number of colors for fractal images, or the irregular synthetic structure unrelated to any known forms, which probably makes it harder for the brain to create rules for complexity differentiation. Increased brain parietal ERP activity suggests increased difficulty as with higher information load [77], which differ depending on the content and structure of the textural image. This effect is further highlighted by the decreased ERDs at parietal sites (more complex processing) and slightly higher at temporal sites (due to the recognizable distinction between Nat and Frac), which gradually decreases as with increased image complexity perception from Uni to Nat and Frac. The natural images generate desynchronizations even in higher frequencies such as \(\gamma\) band, which tends to imply, a more intense process, as compared to fractal images. This may be to the fact that natural images contain more detailed structures which generates a profound thought process for establishing logical connections and criteria for complexity levels differentiation, while for the synthetic abstract fractal structures, the differentiation is either done automatically by subconscious processes or is ambiguous. This is supported by participants opinion, where 5 participants stated a more complex decision for natural images. After an overview of the neural responses, it seems that, generally, the thought process of evaluating natural images complexity is more complex than in the case of fractal images, requiring more processes, while the fractal images complexity perception probably induces a more intense reasoning process, causing more neurons to fire, adding up to the ERP potential, by probably accessing a deeper reasoning with respect to a detection of imaginary forms for differentiation. While on natural textures, the complexity decision might easily relate to known structure and form types, for synthetic fractal textures it is harder to relate to known structures, even though the complexity evaluation has been shown in the experiment to be easier.