Table 3.

Linear models assessing the relationship between classification accuracy and residual correlations in attended and ignored conditions.

Hemisphere	Lobe	Variable	Estimate	Std. Error	t value	p
Left	Occipital	Intercept	0.069	0.140	0.494	0.625
		Residual Correlations	2.081	0.554	3.760	6.85 × 10−4***
		Condition	0.023	0.089	0.263	0.794
		Residual Correlations × Condition	−0.554	0.375	−1.478	0.149
	Temporal	Intercept	0.091	0.037	2.425	0.018*
		Residual Correlations	2.094	0.307	6.825	4.32 × 10−9***
		Condition	0.042	0.024	1.786	0.079
		Residual Correlations × Condition	−0.814	0.196	−4.164	9.85 × 10−5***
	Parietal	Intercept	0.172	0.036	4.818	5.85 × 10−6***
		Residual Correlations	0.720	0.229	3.148	0.002
		Condition	0.003	0.024	0.120	0.905
		Residual Correlations × Condition	−0.286	0.160	−1.794	0.076
	Frontal	Intercept	0.211	0.015	14.344	< 2.00 × 10−16***
		Residual Correlations	0.192	0.129	1.492	0.138
		Condition	−0.005	0.010	−0.548	0.584
		Residual Correlations × Condition	−0.108	0.082	−1.315	0.190
Right	Occipital	Intercept	0.218	0.180	1.209	0.235
		Residual Correlations	1.981	0.788	2.512	0.017*
		Condition	−0.024	0.114	−0.207	0.837
		Residual Correlations × Condition	−0.664	0.504	−1.318	0.197
	Temporal	Intercept	0.118	0.030	3.896	2.43 × 10−4***
		Residual Correlations	2.157	0.286	7.552	2.37 × 10−10***
		Condition	0.021	0.019	1.060	0.293
		Residual Correlations × Condition	−0.764	0.180	−4.251	7.28 × 10−5***
	Parietal	Intercept	0.160	0.036	4.440	2.55 × 10−5***
		Residual Correlations	0.938	0.244	3.840	2.29 × 10−4***
		Condition	0.009	0.023	0.407	0.685
		Residual Correlations × Condition	−0.391	0.157	−2.496	0.014*
	Frontal	Intercept	0.210	0.014	15.519	< 2.00 × 10−16***
		Residual Correlations	0.022	0.130	0.167	0.868
		Condition	−0.007	0.008	−0.793	0.429
		Residual Correlations × Condition	−0.008	0.082	−0.097	0.923

Residual correlations in the attended and ignored conditions were used to predict classification accuracy values in each lobe and hemisphere. Bold values represent p-values surviving multiple comparisons correction (Bonferroni, 8 linear models).

^*p<.05.

^**p<.01.

^***p<.001.