## 4 Discussion  
The objective of this study was to investigate neural responses to both IET and SPV tests using EEG and to determine whether individuals can regulate their effort based solely on perceived exertion, as indicated by the RPE scale. The results yield substantial insights into the neural mechanisms governing exercise regulation and the effectiveness of the RPE scale for guiding exercise intensity. Our results showed that during the SPV test, the beta PSD initially increased but then stabilized at around 80% of the test duration. This suggests that participants reached a point where their perceived exertion allowed them to maintain their effort without requiring further increases in neural engagement. In contrast, the IET exhibited a continuous increase in beta activity throughout the test, reflecting a gradual rise in neural demand as participants neared exhaustion. Our findings diverge from those reported by [PERSON] et al. (2019). He observed sustained elevations in both alpha and beta wave activity during the SPV test and during the IET, and beta activity peaked before declining, indicating an earlier onset of fatigue [31]. The possible explanations for these discrepancies are several. [PERSON] focused on the dorsolateral prefrontal cortex, which is associated with executive function and inhibitory control [43; 44], whereas our study examined the central area of the brain [45; 46], particularly motor-related cortical regions. These central regions may show different activation patterns due to their direct involvement in motor control and sensory feedback integration during intense physical exertion [47; 48; 46]. Finally, another possible explanation for the divergence in results is the methodological difference between the studies. Unlike [PERSON]'s study, which imposed specific RPE levels, our study allowed participants to self-regulate their exertion based on subjective feedback at each step of the exercise. This individualized approach likely provides a more accurate reflection of how individuals naturally regulate exertion, leading to more sustained neural engagement. However, it is worth noting that the advantages of self-paced protocols may be less pronounced in populations that are not as aware of their physiological cues or in those with less exercise experience [10; 48], which could explain variations across different studies. The stabilization of beta activity in the SPV test in our study could be interpreted in line with the Central Governor Model, as proposed by [PERSON] [18]. This model suggests that the brain regulates effort to prevent overexertion and maintain homeostasis, potentially explaining why beta activity plateaus during self-paced exercise [49]. In contrast, the \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline  & & & \multicolumn{3}{c}{**Condition**} & \multicolumn{3}{c}{**Time (\%)**} & \multicolumn{3}{c}{**Condition \(\times\) Time (\%)**} \\ \hline  & **R\({}^{2}\)** & **F** & **Pr \textgreater F** & **F** & **Pr \textgreater F** & **F** & **Pr \textgreater F** & **F** & **Pr \textgreater F** \\ \hline Central Beta/\(\mathrm{\dot{V}O_{2}}\) & 0.466 & 6.810 & \textless{}0.001 & 2.415 & 0.124 & 13.439 & \textless{}0.001 & 1.250 & 0.293 \\ \hline Frontal Beta/\(\mathrm{\dot{V}O_{2}}\) & 0.389 & 4.969 & \textless{}0.001 & 0.052 & 0.819 & 10.867 & \textless{}0.001 & 0.054 & 0.998 \\ \hline \multicolumn{1}{c}{} & & & & & & & & & \\ \hline \multicolumn{1}{c}{} & & & & & & & & & \\ \hline \multicolumn{1}{c}{} & & & & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Multi-factor ANOVA outcomes for the EEG Beta/\(\mathrm{\dot{V}O_{2}}\) ratio analyzed across various brain scalp zones (central, frontal, parietal) and total power (TP) during the incremental exercise test and the self-paced \(\mathrm{\dot{V}O_{2}}\)max test. continuous rise in beta activity during the IET reflects the higher neural strain imposed by the lack of self-regulation, which may have contributed to earlier fatigue onset [12; 21; 25].