The aim of the present study was to characterize patterns of ANT performance in children with an ADHD diagnosis. On the measures of the three attention networks, the results revealed no statistically significant differences between the group of children with ADHD, the group of children with other psychiatric diagnoses and the group of children without any diagnosis. However, the children diagnosed with ADHD showed a lower accuracy score as well as a more variable response pattern (i.e. a higher SE of RT) than the other groups.
The results confirmed the expectation of lower accuracy scores in the ADHD group compared to what was shown in the other two groups. The ADHD group reported more wrong responses and showed a trend towards more omissions errors compared to the non-ADHD groups. The high number of omission errors in the ADHD group indicated a higher level of inattention than in children belonging to the two other groups, a finding that confirms earlier findings in studies using the Conners' CPT [16
]. The results did also support the prediction of high response variability in the ADHD group. However, the variability of SE was not different between the three groups. According to Conners [32
], a pattern of higher Hits SE RT than Variability SE suggests a poor consistency of responses that did not change as the test progressed. This supports the idea that problems related to inattention rather than vigilance are characteristic of children with ADHD.
Our findings with respect to vigilance are in conflict with results from studies using CPT, suggesting that loss of vigilance as the test progresses is characteristic of children with an ADHD diagnosis [12
]. It is well known that children perform better on tasks with a vivid feedback and on tasks that have an underlying story [30
]. The child version of the ANT is more similar to a computer-game with immediate and clear feedback on performance than the Conners' CPT. The ANT includes a character (the fish), a narrative (is hungry, help feed him), and auditory and visual feedback (fish blowing bubbles and wagging its tail as well as exciting sound), and these features have been found to improve the performance on more game-like versions of the CPT [34
]. This and the fact that the ANT has just three time blocks compared to six in the CPT, may have made the vigilance measure less sensitive to a core problem of children with ADHD [12
The FSIQ score was strongly correlated with both error and variability measures, but only in the ADHD group. When included as a covariate, all differences between the ADHD group and the two other groups became non-significant. There is an ongoing debate whether or not one should control for IQ in studies of cognitive function in children with ADHD [15
]. Several studies have shown that children with ADHD tend to obtain lower IQ scores than other children [35
], and that the neurocognitive disorders of ADHD in itself can cause poor performance on intelligence tests [38
]. Actually, a meta-analysis found a strong association between ADHD and FSIQ (d
= .61) [35
]. This is supported by the results in the present study, showing that the highest and most widespread correlations were found in the ADHD group. If reduced IQ is a developmental consequence of the ADHD disorder, then, by controlling for IQ, one may very well control for a part of the disorder [35
]. This has led Barkley [38
] to argue that it is probably unwise to control for IQ score in studies comparing ADHD groups and controls, and that studies of ADHD should rather report results with and without controlling for IQ scores [40
], as done in the present study.
While the IQ scores showed the strongest associations with errors, age was more strongly associated with the Hit RT and variability measures. Age was correlated with faster overall RT in the non-ADHD groups, confirming earlier findings that RT improves with age [30
]. However, age was not significantly correlated to any of the dependent ANT measures in the ADHD group, suggesting that children with ADHD do not show the expected improvement of RTs as they age. The results revealed no significant group differences on the efficiency and error measures of the three attention networks. These results are in accordance with Booth's [9
] findings in a study using the same child version of the ANT as in the present study. However, the results did not support the findings of Konrad et al. [11
], who showed a significant deficit in the efficiency of the conflict network. One explanation may be that they used a modified ANT procedure. Rueda et al. [30
] found that the fish target used in the present study as well as a paradigm including only valid cues generates a smaller interference effect of incongruent flankers than the arrow target. This implies that the paradigm used in the present study may have made it easier for the children to solve the conflict between the congruent and incongruent flankers than in the study of Konrad and collaborators [11
], and may indicate a need for revision of the child version of the ANT in future studies of children with an ADHD diagnosis.
Based on the behavioral measures of the attention networks, one should not exclude the possibility of a characteristic neural activity in children with ADHD, as suggested by Rodriguez [10
] and Konrad et al. [11
]. From these studies one may argue that children with ADHD use different strategies for completing tasks than their peers, and that behavioral measures are not sensitive enough to detect this difference [11
]. However, the high number of errors reported by children with ADHD in the present study may be used to support the idea of a less effective use of strategies in children with ADHD than in their non-ADHD peers.
Strengths and weaknesses
As in all research including children with an ADHD diagnosis, the present results are colored by the high degree of heterogeneity within the diagnostic group. In the present study, information about subgroups of ADHD and symptom load was not included. Both Booth [9
] and Rodriguez [10
] found a difference between the DSM-IV defined diagnostic subgroups of ADHD on the network measures. On the other hand, Seidman [36
] argues that there are more similarities between the subgroups of ADHD than dissimilarities when it comes to measures of cognitive functions. We have calculated the within response variability according to Conners [32
]. According to Russell et al. [41
], more extended calculations may give more adequate measures of variability and should be considered in further studies.
The main strength of the study was the case-control selected sample of children with ADHD, and that the results probably are less biased by co-morbid problems than clinical studies. However, no child was excluded due to a low FSIQ score, although some of the BCS participants with very low FSIQ score were excluded because they were unable to perform the ANT. The high correlations between the FSIQ score and error and variability measures in the ADHD group indicate that by excluding children with low total IQ scores, one may have excluded a specific group of ADHD children [39
Although there have been several studies of the neuropsychological characteristics and the neural basis of ADHD, the deficits of attention in children with this behavioral diagnosis are still poorly understood. To conduct studies of this complex issue, appropriate neurocognitive models that operationalize different aspects of the attention system are necessary. The attention network theory provides one such model and can be used both in group studies and in the clinical evaluation of individual children. In a neuropsychological examination, the range of variables from the ANT may help to characterize the strengths and difficulties of a child. Studies of the attention networks in children with ADHD may contribute to a better understanding of the disorder and to the development of appropriatetraining and treatment methods [42