# Color Texture Image Complexity--EEG-Sensed Human Brain Perception vs. Computed Measures
## 7 Experimental Results
### EEG Experiment Analysis  
In the following, we complement the texture complexity evaluation with deep dive into the neural responses (ERP and power spectrum) and analyze the correlations with the image complexity measures and subjective evaluation. For the ERP trials, we consider the complexity levels as labels, as expressed by CE, CFD (Table 2), or participants' answers and group the trials separately based on the them.  
When considering ERPs, as also observed in our previous work [48], the visual perception and cognitive reasoning on complexity influenced by the ERP paradigm generates two discriminative groups of peaks (see e.g., Figure 6). One group is observed from 300 ms after the stimuli is presented (0 ms) comprising of a P200 potential (appearing at 300-400 ms), which varies in amplitude according to the level of complexity perception, relating to the visual perception of the texture and preparation for the cognitive task of complexity level decision, and it is followed by a P300 potential (400-600 ms) representing reasoning processes, which also varies in amplitude and extends differently in time on a trial base, depending on the respective texture complexity reasoning. The second group of peaks (800-1300 ms) appears at 300 ms after the presentation of the relaxation screen (single grey image), and it is comprised by a P200 potential that is equal in amplitude for all levels of textural complexity processing, followed by a P300, which varies in amplitude and it has a prolongued duration that is influenced by the ongoing neural processes relating to an extended thought process for complexity decision.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline  & **P1** & **P2** & **P3** & **P4** & **P5** & **P6** & **P7** & **P8** \\ \hline CE & **0.6** & & 0.35 & 0.38 & \(-\)0.4 & 0.34 & & 0.38 \\ \hline CFD & **0.8** & & 0.4 & **0.65** & \(-\)0.23 & 0.46 & & 0.27 \\ \hline P1 & & **0.51** & **0.53** & \(-\)0.39 & 0.41 & & 0.26 \\ \hline P2 & & & & & & & \\ \hline P3 & & & & & & & \\ \hline P4 & & & & & & & \\ \hline P5 & & & & & & & \\ \hline P6 & & & & & & & \\ \hline P7 & & & & & & & \\ \hline P8 & & & & & & & \\ \hline \end{tabular}
\end{table}
Table 4: CE, CFD levels versus Participants answers—correlation matrix for _Frac_ images. Highest values are highlighted in bold.  
For the correlation analysis, we investigate whether the amplitude of the N3/N300 (min value from 350-450 ms), P3/P300 (max from 400-500 ms) and second P300b/P3b (mean from 1250-1350 ms) vary proportionally with the complexity values (CE, CFD) or participants answers [70].  
For power spectrum, we consider the maximum value in the \(\alpha\) frequency band (6-12 Hz) and the mean value within the \(\beta\) band (18-22 Hz). A stronger power of the signal should be related to a higher level of complexity, if correlated.  
We present the significantly correlated cases as a response to _Nat_ and _Frac_ textures in the table below (Table 5) and discuss them further.  
Figure 6: GA ERP for _Nat_ images corresponding to the 3 complexity levels according to CE, at channel P4 and the scalp topographies at 300–400 ms, 400–500 ms, 800–900 ms, 900–1000 ms, and 1200–1300 ms.