以语法通顺句子流畅形式优雅、格式专业为翻译标准改写以下一段英文。不要前后颠倒句子不要分段The data analysis were restricted to the delta theta and alpha bands due to considerable electromyographic artifacts observed in high frequencies during dat

Data analysis was restricted to the delta, theta, and alpha bands due to the presence of significant electromyographic artifacts in high frequencies during data cleaning. All measures were conducted within three frequency bands: delta (1-4) Hz, theta (4-8) Hz, and alpha (8-13) Hz. The 10-second epochs underwent Fast Fourier Transformation (FFT) analysis with a frequency resolution of 0.5 Hz. Relative power was computed using the Pwelch method. This involved applying a hamming window with a length of 1000 sampling points and 50% overlap. Relative power was chosen because it is more robust than absolute power across different subjects and less affected by artifacts. To ensure comparability, the relative power of the alpha band was normalized to the total power of the entire band and expressed as a percentage contribution. Additionally, regional power was calculated to illustrate the difference in relative power between the left and right hemispheres. Specifically, regional power was computed for each patient in the following areas: left frontal (FP1, AF3, F1, F3, F5, F7), right frontal (FP2, AF4, F2, F4, F6, F8), left parietal (CP1, CP3, CP5, P1, P3, P5, P7), and right parietal (CP2, CP4, CP6, P2, P4, P6, P8), as shown in Figure 1A.

The FC metric was calculated using the weighted phase lag index (wPLI), where the observed phase leads and phase lags were weighted by the magnitude of the imaginary part of the cross-spectrum. Larger values of the FC metric indicate a higher coupling of neural oscillatory activity. To better account for functional differences between the left and right hemispheres, electrodes in the midline position were excluded from the analysis. To calculate the FC of the left and right hemispheres and different brain regions, FC matrices were constructed for each patient in the frequency bands of interest in the respective left and right hemispheres/brain regions. Finally, the FC values were averaged across patients and pairs of electrodes.

Asymmetry analysis can provide insights into abnormal brain activation. The asymmetry index was calculated by subtracting the natural log-transformed EEG alpha power of the right hemisphere from that of the corresponding locus in the left hemisphere. Logarithmic transformation was employed to better align with the normal distribution of the data. Higher alpha power is associated with lower cortical activation, as it is inversely correlated with cortical activity. We computed the frontal and parietal asymmetry index in the electrode sites F3, F4, and P3, P4, respectively. Similarly, synchronous asymmetry was utilized to depict the differences in FC between left and right brain regions