## 4 Discussion  
Various electrophysiological findings have been described in PD, from changes of EEG-background activity to complex disturbances in functional connectivity on the cortico-subcortical and cortico-cortical levels [9; 29; 30; 31]. However, there are no reports in our knowledge using time series analysis to document an unexpected increase in network assortativity during motor tasks in PD. In our study, the correlation coefficient of spectral entropy calculated for pairs of electrodes does not show significant differences between PD subjects compared to healthy controls, evidencing that the interdependence level is very similar in resting-state. This value, used as a connectivity estimator in our work, increases markedly when the motor cortex is activated in PD subjects, indicating a possible over correlation during motor execution. Actions emerge from temporally coordinated local brain activities at multiple sites in involved neuronal networks, and thus changes in connectivity are expected from a motor or cognitive activation compared with resting-state as seen in our results. Increases in connectivity in PD have been reported previously as an increased resting-state cortico-cortical functional connectivity in the alpha frequency band [9] or elevated phase amplitude coupling [11]. Both have been interpreted as a sign of PD or dopaminergic status. Increased resting-state cortico-cortical functional connectivity in the 8-10 Hz alpha range is a feature of PD from the earliest clinical stages onward. With disease progression, neighboring frequency bands become increasingly involved. These findings suggest that changes in functional coupling throughout [PERSON]'s disease evolution may be linked to the topographical progression of pathology over the brain [29]. In this sense, we have also explored how assortativity depends on the frequency range using the coherence analysis of EEG signals. Similar to SpEn correlation, in our sample, coherence seems to be pretty similar in resting-state, but in response to motor activation, there are opposite changes in the values of PD compared to controls. These changes are not influenced by the motor activation side and seem to confirm an increase in connectivity in all frequencies in response to motor activation in PD. It has been previously published that high values of EEG correlation coefficient or coherence may be caused by anatomical connections or functional coupling between the brain regions generating the recorded EEG signals [32; 33]. Figure 5: Comparison of the effect of levodopa over: Spectral Entropy Correlation Coefficient (left panel), Kullback–Leibler Divergence (central panel), and Median and SD of signal coherence (right panel). Results are shown for the resting-state, right and left finger tapping in each panel. * \(p\) < 0.05, *** \(p\) < 0.001. Our results suggest that increased connectivity and a more extended network activation may be necessary to accomplish the demands of a motor task in PD brains, thus probably reducing its efficiency that results in cognitive and motor performance impairments [34]. In our cohort, it is evident that both sides of the brain seem to work independently to a certain extent. This independence, measured as the Kullback-Leibler Divergence, seems to be higher in controls compared to PD but it is not statistically significant (\(p\) = 0.15). However, there is a significant difference between both groups' interhemispheric independence changes with motor activation on either side. Parallel to what was seen in coherence and entropy correlation, there is an increase in independence in controls but a decrease in PD, indicating that the coupling between both hemispheres may be increased during motor tasks in PD by requiring global participation of networks that may explain a reduced motor performance. No differences were seen between both hands' activation.