## 4 Discussion  
In this paper, we explored the application of functional connectivity calculations and analysis in investigating human responses to different styles of art. Our results indicate that functional connectivity provides a more sensitive method that can potentially uncover the temporal and spatial details of brain activity that remain hidden in traditional ERP or time-frequency analysis. Several M/EEG-ERP studies have focused on the time course and temporal order of processing activities during art perception and identified several key stages [43; 44]. The initial stage starts at around 100 ms post-stimulus with early visual processing involving visual areas, such as V1, V2 and V4. Perceptual grouping, symmetry analysis, etc. provide input to the initial impression formation stage occuring at around 300 ms. From around 300 to 600 ms, the recognition and memory networks related to memory retrieval and processing familiarity engage with the artworks. The final stage, beyond approximately 600 ms, is assumed to be the classification stage, which involves the recognition of the content and style of the artworks. This is known as the early--automatic--aesthetic evaluation, which involves extensive right hemispheric activations. Activities after the first second fall into the deliberate, contemplative aesthetic processing phase that is believed to evoke aesthetic emotions. Our functional connectivity study focused on the first 1 s of aesthetic processing and the time course of activities manifested in the connectivity networks. Our exploratory analysis on network node strengths revealed more activation details than traditional ERP analysis. The extracted node strength map series (see Figures 4 and 5) demonstrated that for both the abstract and figurative conditions, this method could detect more detailed activation patterns in the frontal regions than would be inferred from the ERP topoplots alone and showed that occipital activation is neither constant nor symmetric over time (Figure 3). For the connectivity network analysis, we selected three key time points (100, 300 and 500 ms), aligning with past studies [43; 45; 46; 47] and with the main peaks found in our ERP waveform (Figure 2). The analysis based on the edge weights of the functional connectivity networks found significant differences between the abstract and figurative conditions across all the time points and frequency bands. A significant difference in connectivity  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{3}{c}{**Mean \(p\)-Values of the Significant Edge Weight Differences**} \\  & \(-\)**300 ms (Baseline)** & **100 ms** & **300 ms** & **500 ms** \\ \hline \multicolumn{3}{c}{**Figure \(>\) Abstract**} \\ \hline Delta & 0.0248 & 0.0259 & 0.0273 & 0.0247 \\ \hline Theta & 0.0275 & 0.0292 & 0.0288 & 0.0234 \\ \hline Alpha & 0.0299 & 0.0264 & 0.0267 & 0.0268 \\ \hline Beta & 0.0263 & 0.0232 & 0.0232 & 0.0260 \\ \hline Gamma & 0.0266 & 0.0245 & 0.0254 & 0.0248 \\ \hline \multicolumn{3}{c}{**Abstract \(>\) Figurative**} \\ \hline Delta & 0.0258 & 0.0239 & 0.0233 & 0.0204 \\ \hline Theta & 0.0250 & 0.0223 & 0.0270 & 0.0306 \\ \hline Alpha & 0.0273 & 0.0259 & 0.0243 & 0.0269 \\ \hline Beta & 0.0256 & 0.0252 & 0.0275 & 0.0256 \\ \hline Gamma & 0.0246 & 0.0251 & 0.0253 &represents an increase in network edge weight that in turn represents an increase in phase synchronization (stronger communication) between brain regions. The increased connectivity in our first condition (figurative > abstract) showed a sustained and focused network, initially involving the occipital and parietal regions then progressing to the frontal and other areas as processing continues. This temporal progression aligns with previous literature suggesting that art processing begins with perceptual analyses before advancing to higher-order semantic processing and context integration [43; 48; 49].