The present study was designed with two major goals. Firstly, we attempted to clarify the difficulties in eight factors of SA in children with ADHD. Secondly, we evaluated the predictability of SA on the EFs. The results highlighted that the performance of children with ADHD was poorer than TD in all the eight factors of SA except ST. Furthermore, the mean of RT in VIS, SR, and SO tasks was more in children with ADHD. We also found out some of the SA factors not only were correlated with EFs but also predicted them in ADHD and TD children.
Spatial Ability In Children With ADHD
We measured all SA factors in the present study. We explored that ADHD children had more difficulty in performing all of the SA tasks, comparing to the TD group. On the other hand, children with ADHD had deficits in static-intrinsic, dynamic-intrinsic, static-extrinsic and dynamic-extrinsic skills based on Uttal classification (9).
In line with our study, it was reported that children with ADHD had problems in the FC factor which was measured with an Embedded Figure test (30, 37) and SR factor which was examined with the Mental Rotation Moomies test in Jakobson and Kikas (29) study, and the Turning test and the Spatial Relation test in Aman and colleagues study (26). All of these tasks together with the SR task were employed in the current study to examine the ability of mental rotation of figures. In contrast with our study, when the Gestalt Closure task was applied for measuring CS factor, in Kalff's (30), and Mariani and Barkley's studies (39), children with ADHD did not perform differently from TD children. One possible reason for this contradiction can be related to the level of difficulty of the Gestalt which is more difficult than the Embedded Figure test and our CS task for children. In the literature review, we found that some studies investigated spatial ability with different terms and measured this ability with inappropriate tests such as the Benetton judgment line orientation, Benetton visual retention, and Rey Osterrieth Complex Figure that were not specific for each factor of spatial ability. It’s worthy to note that none of the above-mentioned tests are related to the nature of spatial ability factors (25, 28, 31, 32, 34, 35, and 40–42). At the neural level, anatomical and functional neuroimaging studies have revealed the difference in the parietal cortex especially the IPL area in children with ADHD comparing to normal children (18, 19, 61, and 62). The parietal cortex particularly the IPL, has known to be involved in many aspects of spatial processing and manipulation (14, 15). These findings may associate spatial ability problems in ADHD group with an abnormality in the IPL.
Regarding the ST task, significant differences were not found between the two groups. In tasks that measure ST ability such as our task, participants are asked to predict not only where several moving objects will interrupt, but also to decide when this interception might occur. Thus, this task is to evaluate the ability to represent time and use this information to calculate relative velocity, which is then used to extrapolate a viable intercept, and to make an appropriate spatial judgment (63). Consequently, it can be inferred that performing the ST task needs the participant to divide his/her attention since the ability to attend and respond to multiple tasks or task demands simultaneously divided attention (64). The fact that children with ADHD have been reported to perform similar to, or better than children without ADHD on tasks that require divided attention, can be the reason for a similar performance on the ST tasks in ADHD and TD groups (65).
One of our findings was related to differences between the mean of RT in the SA tasks in two groups of participants. In regards to the results, children with ADHD consumed more reaction time than TD children in the VIS, SR, and SO tasks. SA factors are highly consistent with both the hierarchical models e.g., Carroll (66), and the nonhierarchical Radex models of human intelligence(67). Both models suggest a complexity continuum along which cognitive tasks can be organized. In these models, the more complex a task is, the more strongly it tends to be correlated with general intelligence (G) and the higher it is placed in the hierarchy (in the hierarchical models) or the closer it is placed to the center of the configuration (in the Radex models). Besides, this complexity continuum nicely corresponds to the degree of central executive involvement. From this perspective, more complex tasks such as the VIS, SR, and SO compared with the FC, CS, and PS tasks need more time for solving their items. Since ADHD children, in general, have slower processing performance comparing to the typical population (68, 69), it seems logical that they need more time to response more difficult tasks.
Prediction Of Executive Functions With Spatial Ability Factors
Considering our findings, children with ADHD performed all EFs tasks poorer than TD children. These results frequently proved in previous studies (70, 71). Based on the second our aim, results indicated that working memory and cognitive flexibility were predicted by some SA factors in ADHD children.
The regression analysis revealed that the working memory can be predicted by ACC of CS, PS, SO, and SD phase of WF tasks. These results are well justified by Baddeley and Hitch's working memory theory (72). The theory proposed a model containing three components: the central executive, the phonological loop, and the visuospatial sketchpad. The CS factor is concerned with the speed of apprehending and identifying a visual pattern, often in the absence of complete stimuli. Performance on the CS tasks (such our task) is likely to be aided by strategic mental searches of possible shapes, and hence the contribution of visuospatial and executive components of working memory theory may be relatively high. The PS factor was defined as the speed in finding figures and making comparisons between them. The concept of PS can be considered to be the centroid of several sub-factors (73). The sub-factors have been defined as the speed of symbol discrimination, speed of making comparisons and speed of form discrimination as in recognizing predetermined, but novel configurations (74). The ability to maintain spatial representations may be essential ingredients of all these sub factors. SO factor requires considerable reasoning skill and participants may solve items by mentally rotating and manipulating them rather than moving an image of the self to the desired perspective. Therefore, it requires maintaining orientation a visual pattern and manipulating its mental representation in the mind. It can be deduced that two of the three components of working memory theory (visuospatial sketchpad stores and central executive) involve in solving SO tasks. Working memory includes holding information in mind and the SD phase of the WF task needs to hold possible paths information and to choose the shortest. Taken together, the prediction of working memory by the CS, PS, SO, and SD in our study was not unexpected.
Our findings indicated that cognitive flexibility is predicted by ACC of the SO, FC, CS, and SR tasks. The ability to change perspectives spatially is known to be one of the aspects of cognitive flexibility, concerning this (e.g., “What would this look like if I viewed it from a different direction?” fact (3), the prediction of cognitive flexibility by SO factor in ADHD children is logical in the current study. We also found out that children’s performance in the FC and CS tasks predicted the performance of them in WSCT. For an explanation of results, it may point to visual global and local processing. To solve FC problems, children should find a hidden specific stimulus in a complex and ambiguous visual pattern. Finding a specific stimulus depends on the ability to shift global processing to local processing, however children in CS tasks have to switch from local to global processing to recognize incomplete stimulus. Since each item of FC and CS tasks contain four complex patterns, children must shift processing quickly among the patterns. Furthermore, the answer to each trial of two tasks is consistent with the nature of cognitive flexibility. Finally, SR factor was able to predict cognitive flexibility. This factor is defined by the tasks in which participants are required to determine whether the two presented stimuli (animals in the current task) are identical or mirror images of each other. To overcome the challenge, the participant should frequently switch between upright and rotated positions of animal in mind to understand two animals are the same or different, so cognitive flexibility partly involves in solving the task. According to what was explained, it is logical to predict cognitive flexibility by mentioned spatial factors.
In our study, although children with ADHD had a deficit in inhibitory control, this cognitive function was not predicted by any of the SA factors. Inhibition is defined as the ability to revoke or suppress an action which is irrelevant, no longer needed, and/or inappropriate (75–77). Inhibition is known to be divided into 2 subgroups of pre-potent response and resistance to distractor interference. However, the third component of inhibition is defined by some as the coined resistance to proactive interference (76, 78). In the current study, we focused on pre-potent response inhibition and utilized the Go/No-Go task for measuring it. Our spatial ability tasks didn't require to suppress a pre-potent stimulus, but it is not unlikely that interference and proactive inhibition at least relate to some of the SA factors.
This is the first regression analysis that examines the prediction of EFs by SA factors on in ADHD children. Therefore, there is a requirement for our findings to be confirmed through the next researches. The results of our study indicated that children with ADHD are less accurate than TD children in the three EFs tasks and also different aspects of the SA were related to major EFs tasks. Furthermore, they could predict the performance of children with ADHD in two EFs tasks. These behavioral findings are in correspondence with neuroimaging evidence about inter-correlation between the parietal and frontal coteries (19, 62, and 79).
The other finding of this part of the study indicated that in TD as well as children with ADHD some of the spatial ability factors were able to predict their performance in both working memory and cognitive flexibility. That way, the PS was able to predict working memory and ACC of the CS, VIS, ML, and LP of WF tasks were able to predict cognitive flexibility. Spatial ability factors in children with ADHD were not able to predict response inhibition, this result was the same in TD children. Since the existence of functional relationships and interactions between the parietal cortex and the prefrontal cortex has been confirmed, predicting the performance of TD children in some spatial factors on working memory, and cognitive flexibility is rational. But the reason why different spatial factors in the two groups were able to predict the performance of these two executive functions is probably due to the unusual interactions between the impaired prefrontal cortex and the parietal cortex in children with ADHD (19, 62, and 79) and also can be to attributable to anatomical and clinical heterogeneity in this disorder (80). Functional neuroimaging studies are required in both ADHD and TD children separately in order to an accurate understanding of this subject.
Limitations And Future Directions
Concerning the current study, the following limitations are noteworthy. Firstly, ADHD is a clinically heterogeneous disorder with a high rate of comorbid conditions, thus making it extremely difficult to completely control the comorbidity of a representative sample of children with ADHD. In the present study, ADHD was the main diagnosis, without any other diagnosis, although comorbid emotional or behavioral symptomatology may exist in some cases, without constituting a disorder in themselves. Secondly, the sample size was small, specifically for regression analysis and also the ADHD group was limited by the low number of females among the participants. Thus, the results of this study may be more applicable to the male population with ADHD, which is the population that most frequently suffer this disorder.
Since our study showed that at least some of the SA factors and EFs impairments were related to each other and SA impairment reflected the disruption of EFs, we suggest to examine and report the effectiveness of various spatial training programs not only on the enhancement of spatial factors but also EFS in people with ADHD. Besides, functional neuroimaging studies on ADHD people should take these cognitive functions into account.