Table 3.
Backward stepwise regressions to predict working-memory performance using different types of fMRI measures in healthy individuals
| Task performance measure (dependent variable) | Type of imaging measure | Independent variables entered | Statistics for best model |
|||||
|---|---|---|---|---|---|---|---|---|
| Predictors retained, standardized β values | R2 | Adj. R2 | AICc | AICca (n = 15) | F (df) | |||
| 2-back AHR | Load-dependent connectivity (n = 39) | 6 network pairs | lFPN-rFPN, β = 0.55*** | 0.30 | 0.28 | −133 | −61.3 | 15.7*** (1, 38) |
| Load-independent connectivity (n = 39) | 6 network pairs | CON-rFPN β = −0.22 | 0.05 | 0.02 | −121 | −44.5 | 1.8 (1, 38) | |
| Load-dependent activation (n = 39) | 4 networks | CON, β = −0.47* lFPN, β = 0.52** | 0.22 | 0.18 | −125 | −43.0 | 5.1* (2, 38) | |
| PET dopamine (n = 15) | DLPFC BPND, DLPFC ΔBPND | ΔBPND, β = −0.34 | 0.11 | 0.05 | — | −46.2 | 1.7 (1, 14) | |
| Differential accuracy (2-back − 1-back) | Load-dependent connectivity (n = 39) | 6 network pairs | lFPN-rFPN, β = 0.39* | 0.15 | 0.13 | −128 | −40.9 | 6.7* (1, 38) |
| Load-independent connectivity (n = 39) | 6 network pairs | CON-lFPN β = 0.22 | 0.05 | 0.02 | −124 | −42.6 | 1.8 (1, 38) | |
| Load-dependent activation (n = 39) | 4 networks | lFPN, β = 0.47* rFPN, β = −0.45 | 0.12 | 0.07 | −123 | −35.0 | 2.5 (2, 38) | |
| PET dopamine (n = 15) | DLPFC BPND, DLPFC ΔBPND | BPND, β = 0.29 | 0.08 | 0.01 | — | −38.8 | 1.14 (1, 14) | |
aAICc, Corrected AIC calculated to compare models on the subsample with PET dopamine measures (n = 15).
***p < 0.001,
**p < 0.01,
*p < 0.05.