In this study, we examined the correlation between ADHD/ASD traits and the integrity of the triple networks in subclinical populations. At the behavioural level, ASRS scores (i.e., ADHD traits) were positively correlated with performance in the CPT, whereas AQ scores (i.e., ASD traits) were not. In the FC analyses, the ASRS and AQ scores were differentially correlated with intra- and inter-network connectivity among various ROIs in the DMN, SN, and FPN. During the auditory oddball task, ASRS scores were positively correlated with FC values within the DMN, whereas AQ scores were positively correlated with those within the FPN. ASRS and AQ scores were positively and negatively correlated with FC between the ROIs in the FPN and the SN, respectively. During Rest, only AQ scores were negatively correlated with FC values within the SN, and there was a positive correlation AQ scores and FC between the DMN and SN. Figure1 shows the relationship between AQ and ASRS scores and the triple network.
Relationship between ADHD/ASD traits and CPT performance
Adults and children with ADHD generally show lower performance on the CPT (47-49) . However, there are no consistent reports regarding the association between ASD and CPT performance (49, 50) .
Our results indicate that the higher the ASRS score, the more favourable the CPT performance and the shorter the reaction time. This suggests that ADHD traits beneath the diagnostic threshold may promote attentional retention functions. A previous questionnaire study reported that CPT performance was intact in healthy children with low-to-moderate ADHD symptoms, indicating that CPT performance can vary widely among different levels of ADHD severity (51).
To the best of our knowledge, this study is the first to indicate an association between favourable CPT performance and susceptibility to subclinical-level ADHD. Moderate levels of media multitasking are expected to be associated with enhanced cognitive control, and several reports suggest an inverted U-shaped relationship between attentional performance and media multitasking (52, 53). Adults with ADHD are known to choose multitasking tasks quite often (54). Considering the potential preference for multitasking in individuals with subclinical ADHD, intermediate-level ADHD traits are also expected to demonstrate an inverted U-shaped relationship with attentional processing. If the inverted U-shaped model is accepted, the participants in the present study would be distributed on the left side of the curve. In particular, those with higher (but still subclinical) ADHD traits would be located near the apex.
Two hypotheses have been proposed regarding the relationship between media multitasking and attentional functioning: the scattered attention hypothesis and the trained attention hypothesis. The scattered attention hypothesis argues that long-term media multitasking weakens attentional control, meaning that individuals exposed to a multitasking lifestyle are less capable of maintaining focus on relevant tasks in the presence of distractions (52). In contrast, the trained attention hypothesis argues that frequent multitasking enhances cognitive control and positively affects attention (55). The results of the current study suggest that individuals with subclinical ADHD perform better in the CPT, which may be consistent with the trained attention hypothesis.
Relationship between ADHD traits and the triple networks
Previous studies have reported functional deficits in the DMN among individuals with ADHD (21, 56) (55, 57) (20) (58) (59) (60) (61). The DMN is commonly activated when the brain is free from external cognitive demands or when it is performing internal tasks (62, 63). However, individuals with ADHD exhibit reduced FCs in the DMN during the resting state and reduced inhibitory changes in FCs during task performance (64-66). Our results also showed that ADHD traits were positively correlated with the intra-network integrity of the DMN during tasks. This indicated that in terms of DMN activities, people with subclinical ADHD traits and those with ADHD share some common neural bases .
Our analysis of inter-network relationships among the triple networks showed that subclinical ADHD traits were positively associated with the integrity of SN–FPN FCs. To the best of our knowledge, no other study has reported increased FC between the SN and FPN in individuals with ADHD. Previous studies in the general population have suggested that the FC between the SN and FPN—including the FC between the cerebellum (involved in the SN) and prefrontal cortex (involved in the FPN)—increases in response to cognitive demands, especially during auditory cognitive tasks (67-70). Thus, the positive associations between ADHD traits and the SN (cerebellum)–FPN (frontal gyrus, including the cingulate) FCs during the oddball task (as observed in the current study) may indicate improved sustained attentional functions (insofar as the level of ADHD traits is lower than intermediate). The increased SN–FPN FCs may also explain the results of the behavioural part of this study—that is, improved performance in the CPT by individuals with a higher (but still subclinical) level of ADHD traits.
Relationship between ASD traits and the triple networks
Our analysis of intra- and inter-network FCs revealed differential changes in FCs in association with ASD traits. Our results are partially consistent with those of previous rs- and task-based fMRI studies (21, 23, 71-75). In particular, we note the decreased FCs within the SN during the rest period.
The SN detects salient internal and external stimuli and regulates other brain regions by switching the brain networks (8, 76). Therefore, the decrease in FCs within the SN and their associations with symptom severity (71, 77) suggest that the SN may contribute to both overactive and underactive brain functions in individuals with ASD. For example, emotion dysregulation—a common clinical symptom of ASD (78, 79)—may be explained by the failure of the cognitive control of emotion (i.e., the FPN function) caused by problems in attention when “selecting” stimulus importance (i.e., the “switching” function of the SN). Previous studies have hypothesized that an increased SN–DMN FC is potentially associated with repetitive negative self-thoughts in ASD (80). Previous fMRI studies have also reported that in depression, dysfunction within the SN contributes to abnormal engagement and disengagement of the DMN and FPN. This may cause difficulties in disengaging the processing of negative information, thus contributing to the worsening of negative thoughts (81, 82). The mechanism of negative thoughts in ASD may be similar to that in depression, which is often a major comorbid disorder in ASD(83, 84).
ASD traits were negatively associated with FCs within the SN (during the resting state) and those between the SN and FPN (during the oddball task). This indicated that in terms of selective attentional processing, even people with subclinical ASD traits share common neural bases with those with clinical-level ASD. This may cause problems in attention when “selecting” stimulus importance. ASD traits were positively associated with the FCs of the FPN under the oddball paradigm; this is consistent with the hypothesis that in ASD adults, sustained attention is not significantly different from typical development (85, 86).
Limitations
Our study had some limitations. First, the sample size was relatively small, and the number of individuals with clinical ASD or ADHD traits was quite small. A total of 9 participants were screened as positive for ADHD according to Part A of the ASRS. Using a cut-off score of 33 for the AQ (87), 6 participants were screened as positive for ASD. Finally, 4 participants who had been screened as positive for ADHD exceeded the cut-off score for the AQ.
Second, we did not examine continuity in attentional functions and neural substrates among people with clinical traits. Because we recruited only subclinical participants, we can only evaluate continuity based on comparisons with the results of prior studies. Further studies are needed to perform direct comparisons with between patients with subclinical vs. clinical traits.
Finally, the present study used the CPT to assess attentional function. However, this test is known to be less sensitive in adolescents with ADHD than in children. Moreover, there is no significant difference in performance between high-functioning individuals with ADHD and typically developing people (36, 88). These reports suggest that the task difficulty of CPT may be too low to measure attentional function. Some studies have suggested that adding complex distractor stimuli to the CPT can increase the differences in performance between people with ADHD and typically developing individuals. In the present study, we considered the possibility that ADHD traits may facilitate the maintenance of attention. However, future studies should compare performances between individuals with ADHD and typically developing controls using more complex attentional tasks.