Table 3.
Regression coefficients from linear mixed models
| Behavioural measure | Intercept | βConnectivity |
|---|---|---|
| Connectivityfunc | ||
| Identityinva | 5319.06 (±254.10)** | −1556.87 (±706.49)* |
| Affectinva | 4397.54 (±179.92)** | −795.15 (±459.85) |
| 3Facesinva | 6055.73 (±236.78)** | −162.41 (±655.95) |
| Connectivitystruc–func | ||
| Identityinv | 5287.58 (±307.83)** | −1093.79 (±777.91) |
| Affectinv | 4514.71 (±215.40)** | −908.91 (±537.74) |
| 3Facesinv | 5403.58 (±417.53)** | −84.77 (±931.25) |
| Males | ||
| Females | 6705.77 (±622.66)* | −2787.03 (±1374.25) * |
Notes: Values give the estimates of inverted efficiency (expressed in milliseconds) emerging from the models used to investigate the relationship between functional connectivity and face-processing performance. Each measure of face processing performance was regressed with age and mean functional connectivity, the latter measured as the mean correlation among ROIs comprising the ‘obligatory-optional sub-network’ identified by either PLSfunc or PLSstruc–func (‘Connectivityfunc’ or ‘Connectivitystruc–func’, respectively; see text). Where a significant Sex*Connectivity effect emerged, the table gives the coefficients for males (n = 21) and females (n = 17) separately. Intercepts give values of the behavioural measure corresponding to the minimum value of functional connectivity (r = −0.13 and −0.22, respectively; see text). *P < 0.05; **P < 0.001.
aThe corresponding measure of functional connectivity was entered as both a fixed and random effect.