Table 3.
Relationship between AP and PA SICF circuitry and its modulation in the presence of SAI
| A. Correlation between SICF (AP) and SICF (PA) | |||
|---|---|---|---|
| SICF (AP) vs. | Pearson correlation coefficient (R) | P-value | Regression line equation |
| PA SICF1 | 0.90 | 0.006 | y = 0.90x + 0.29 |
| PA SICF2 | 0.93 | 0.003 | y = 0.98x + 0.08 |
| PA SICF3 | 0.90 | 0.006 | y = 0.70x + 0.80 |
| PA SICF T1 | 0.55 | 0.204 | y = 0.88x + 0.66 |
| B. Correlation between SICFSAI (AP) and SICFSAI (PA) | |||
|---|---|---|---|
| SICFSAI (AP) vs. | Pearson correlation coefficient (R) | P-value | Regression line equation |
| PA SICF1SAI | 0.89 | 0.008 | y = 0.71x + 0.72 |
| PA SICF2SAI | 0.83 | 0.022 | y = 0.71x + 0.70 |
| PA SICF3SAI | 0.86 | 0.013 | y = 0.72x + 0.80 |
| PA SICF T1SAI | 0.58 | 0.175 | y = 0.66x + 1.18 |
A, there is a high degree of correlation between AP SICF1 and all PA SICF peaks. B, this relationship remains strong in the presence of SAI. SICF1, SICF2 and SICF3, SICF peaks 1, 2, 3; T1, trough 1. P < 0.05 indicates a significant correlation without correction for multiple comparisons; P < 0.0125 indicates a significant correlation with correction for multiple (4) comparisons in each condition.