Skip to main content
Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

< Back to Article

Table 1.

Feature distributions of the HCP subjects.

More »

Table 1 Expand

Fig 1.

Gender-specific age distribution of the HCP and ADNI subjects.

More »

Fig 1 Expand

Table 2.

Age distribution of the ADNI subjects.

More »

Table 2 Expand

Fig 2.

Prediction results for the HCP dataset (age) for NICARA and the 1015 ROI dataset from braingraph.org.

The x-axis shows the actual age in years and the y-axis the predicted age in years during the cross-validation.

More »

Fig 2 Expand

Table 3.

Prediction outcome using the correlation-based regression method for age.

More »

Table 3 Expand

Fig 3.

Prediction results for the ADNI dataset (age) for the total dataset (bottom) and the gender-specific subsets (top). The x-axis shows the actual age in years and the y-axis the predicted age in years during the cross-validation.

More »

Fig 3 Expand

Table 4.

Prediction results for the ADNI dataset.

More »

Table 4 Expand

Table 5.

Prediction outcome using the correlation-based regression method for total intelligence.

More »

Table 5 Expand

Table 6.

Prediction outcome using the correlation-based regression method for crystallized intelligence.

More »

Table 6 Expand

Table 7.

Prediction outcome using the correlation-based regression method for fluid intelligence.

More »

Table 7 Expand

Fig 4.

Prediction results for the HCP dataset (total intelligence) for NICARA and the 1015 ROI dataset from braingraph.org.

The x-axis shows the actual values and the y-axis the predicted values during the cross-validation.

More »

Fig 4 Expand

Fig 5.

Prediction results for the HCP dataset (fluid intelligence) for NICARA and the 1015 ROI dataset from braingraph.org.

The x-axis shows the actual values and the y-axis the predicted values during the cross-validation.

More »

Fig 5 Expand

Fig 6.

Prediction results for the HCP dataset (crystallized intelligence) for NICARA and the 1015 ROI dataset from braingraph.org.

The x-axis shows the actual values and the y-axis the predicted values during the cross-validation.

More »

Fig 6 Expand

Fig 7.

MAE of crystallized intelligence prediction.

Total dataset: green, Female subset: blue, Male subset: red. *: p < 0.05 without correction based on the Wilcoxon signed-rank test for paired absolute errors.

More »

Fig 7 Expand

Fig 8.

MAE of fluid intelligence prediction.

Total dataset: green, Female subset: blue, Male subset: red. *: p < 0.05 without correction based on the Wilcoxon signed-rank test for paired absolute errors.

More »

Fig 8 Expand

Table 8.

P-values from the comparison between crystallized and fluid intelligence.

More »

Table 8 Expand