As optimal task performance requires focusing on the task-relevant numerical dimension, larger facilitation from physical size information reflects the intrusion of the task-irrelevant stimulus dimension into processing. Hence, this effect is a marker of failure to inhibit the task-irrelevant stimulus dimension. Second, there was a larger distance effect in DD than in controls in the physical size decision Stroop task ( Supplementary Fig. 2H). This means that task-irrelevant numerical information had a larger effect on RT in

DD than in controls. Third and fourth, trail-making A (Mean/SE: DD = 58.3 ± 5.4 sec; Control = 41.3 ± 2.0 sec) and mental rotation (DD = 66.7 ± 4.4 sec; Control = 56.0 ± 3.5 sec) solution times were longer in DD than in controls. Further, this website there was a marginally larger congruency effect in the animal size decision Stroop task in DD than in controls ( Supplementary Fig. 2B). This means that task-irrelevant physical size information had marginally larger effect on RT in DD than in controls. Again, both permutation testing and confidence interval estimation showed that symbolic and non-symbolic slope was a highly non-discriminative parameter between groups. There were no effects

in coefficient of variation (see Supplementary Fig. 3). Regression analysis was used to study the relative weight of variables which significantly discriminated between DD and control and correlated with maths performance. The three visuo-spatial memory measures ERK inhibitor datasheet (Dot Matrix, OOO Recall and Processing) were averaged to form a single ‘Visuo-spatial memory’ measure. Molecular motor The RT facilitation effect from the numerical Stroop task and the RT distance effect from the physical size decision Stroop task were averaged to form an ‘Inhibition’ score because only these measures showed

a significant correlation with maths performance (see correlations in Figs. 2 and 3). The counting-range slope from accuracy data was also used because this also showed a significant correlation with maths performance. Correlations between the above variables and maths scores are shown in Table 4. The above three variables were entered into the analysis simultaneously. The regression had a significant fit [R2 = .583, F(20,3) = 9.30, p < .0001]. Visuo-spatial WM [Standardized Beta (β) = .48, t(20) = 3.2, p = .0045] was a significant predictor and Inhibition [β = .36, t(20) = 2.06, p = .0522] was a marginally significant predictor. Subitizing slope was a non-significant predictor [β = −.17, t(20) = −1.02, p = .31]. When only Visuo-spatial WM and Inhibition were entered into the regression the overall fit remained unchanged: [R2 = .561, F(21,2) = 13.39, p < .0001]. Visuo-spatial WM: β = .48, t(21) = 3.24, p = .0039. Inhibition: β = .45, t(21) = 3.00, p = .0068. When verbal IQ (WISC Vocabulary), Raven score and processing speed were added to the regression, the overall fit increased [R2 = .633, F(20,3) = 9.30, p < .