In this paper we examined resting-state brain activity in children with (C)APD, using two independent data-driven approaches: ReHo and ICA with different model order settings.
First, we should emphasize that to date there has only been one preliminary study published which aimed to develop an fMRI procedure to examine individuals with (C)APD . According to the authors’ best knowledge, this is the first study which applied rs-fMRI to investigate brain activity in (C)APD. Secondly, we used two different methods (ReHo and ICA) to analyze the same data set, in order to provide a more complex picture of DMN.
On the basis of one-sample t-tests performed in children with (C)APD and in the control group, with the use of two analysis methods, we clearly demonstrated patterns of activity consistent with the default mode network . However, ReHo analysis revealed differences in resting-state brain activity in the (C)APD group, relative to controls. Specifically, a significant ReHo decrease was found in the PCC/pCu and the SFG (BA 10) in patients. The ICA showed that the model order selection, as well as component selection can both significantly affect the results. Therefore, due to inconsistent results in two-sample t-tests, drawing conclusions about group differences based on ICA does not seem eligible.
Rs-fMRI in (C)APD
In the present study we used a rs-fMRI paradigm to investigate brain activity in (C)APD (and not an active task). There were several reasons why we did so. First, previous fMRI studies in children with (C)APD showed that their concentration and tests performance decreases with increased duration of examination . Then the possible group differences in brain activations may results from attentional lapses, only caused by the duration of the experiment rather than the modality-specific impairment. Resting state-fMRI, which is of very short duration, enables to overcome this limitation. Secondly, a paradigm that does not require children to cooperate actively, might diminish motion artifacts, resulting from reacting to stimulation.
Furthermore, a rs-fMRI paradigm allows us to examine a whole brain network rather than focal activations associated with a particular task. As (C)APD children in the present study showed deficits in all behavioral (C)APD screening tests, it would be advisable to apply as many as five different cognitive tasks in an MR scanner in each child. It would not be possible within a single fMRI session and it would be problematic to ask the subject to participate in an fMRI experiment several times in a short period of time.
Default mode network and attention
The ReHo results of the study are interesting, as the posterior cingulate cortex (PCC) and the precuneus not only form a central node in DMN in the human brain but they have also been suggested to play an important role in attention and goal-directed cognition [30, 31]. PCC shows high connectivity to the frontal network involved in cognitive control and attention demanding tasks . Moreover, a specific pattern of PCC/pCu activity has been found in several rs-fMRI studies in ADHD .
Additionally, altered connectivity between the anterior (prefrontal cortex) and the posterior (posterior cingulate/precuneus) components of the DM network [18, 32] has been reported in subjects with ADHD. In our study we did not assess the functional connectivity directly, but we also found alternations in corresponding regions in ReHo analysis. As ReHo corresponds to connectivity at the local level, the revealed decreased ReHo values may reflect low regional metabolism  in PCC/pCu and the SFG (BA 10). This is in line with other studies linking attention disorders with disrupted consolidation of the DMN .
The atypical activity found in the region of PCC may suggest similar brain mechanisms underpinning (C)APD and ADHD. This can also indicate that rs-fMRI cannot differentiate between the modality-specific attention problems observed in (C)APD and general attention impairments.
A number of studies have suggested that dysregulation of DMN may be associated with lapses of attention and errors during cognitively engaging tasks . According to default-mode interference hypothesis inefficacious transition from rest to task may account for impaired cognitive task performance . It deserves further consideration, to investigate whether errors observed in (C)APD diagnostic batteries originate from general attention problems or a modality-specific perceptual dysfunction, as suggested by several authors . Interpretative issues related to ICA with regard to the DMN analysis are discussed in the next section.
ICA or ReHo?
In the present study two different methods (ICA and ReHo) to analyze the rs-fMRI data were applied. Except for purely methodological studies, researchers usually choose only one approach to analyze the data. This may lead to some discrepancies between studies using different analysis techniques  or even only ICA but with different model settings .
One of the most popular techniques applied in resting-state fMRI studies has been ICA . The main advantage of this method is lack of any initial assumptions about the spatial location of brain activations, which makes it suitable for exploratory fMRI analysis . ICA is, however, not without its challenges, as it requires an arbitrary decision on the dimensionality reduction, as the number of components to estimate is not fixed and should be selected according to the data quality and the complexity of the results one wishes to obtain [e.g. resting state networks (RSN) may be separated into sub-networks reflecting their fine-grained nature] [36, 37]. Also, components representing networks of interest might be selected differently based on various templates which may lead to divergent results, as was presented in our study. Therefore, the reproducibility of the results obtained with ICA might be questioned, which has also been emphasized by other authors . The issue of inconsistent ICA results has hardly been discussed and not resolved yet . Thus, group ICA should be used with caution when drawing inferences about group differences.
Another approach widely used to the evaluation of rs-fMRI is regional homogeneity (ReHo), which investigates the temporal congruency of the regional BOLD signal in various brain regions [38, 39]. Both ReHo and ICA represent a connectivity analysis but they are performed with different mathematical approaches. While ReHo reveals correlations between slow fluctuations of the BOLD MR signal in various brain regions, ICA determines networks related to the decomposed temporal signal fluctuations. Importantly, ReHo is relatively insensitive to possible region-to region or trial-to-trial variability of the BOLD signal, which makes it complimentary to ICA . The possible discrepancies in the results (which were demonstrated in our study) may be due to the fact that in ICA, the mean time course of a whole network is compared with the time course of individual voxels within that network , whereas ReHo seeks for correlations between the BOLD fluctuations of a small group of voxels with the adjacent ones. This might suggest that ReHo is more sensitive to local changes of functional connectivity and the ICA approach examines long-range connectivity .
Additionally, in ICA, due to differences in the model settings used in various studies results might be not reproducible. Also, possible inter-group differences might be concealed, as they may emerge in the components not included in further analysis.
Taking into account the aforementioned considerations, we recommend ReHo as the method providing more stable results in DMN network compared to the ICA.
The effect of motion
As a number of studies indicate that disruptions in BOLD signal resulting from head motion may create spurious patterns of correlations in rs-fMRI we made sure that in our study the two groups did not differ either in their motion parameters or in tSNR [29, 41]. Originally our study group was twice as big but after the motion parameter analysis we decided to eliminate participants whose motion might have confounded the results. We decided to exclude participants rather than apply “scrubbing” methods, as it was reported that this procedure does not always remove all motion-related signal and that these are most efficient when periods of motion are within a single TR . In children, however, the periods of motion span across multiple TRs. Consequently, replacing time points in which movements occurred with adjacent ones may contribute to losing the signal of interest.
Limitations of the study
The presented findings are promising but several methodological limitations should be indicated (which are not confined to the present study). First, although there is a growing interest in rs-fMRI studies, interpretative issues remain to be resolved before the alternations in the intrinsic brain activity can serve as an indicator of cognitive dysfunction .
We suggest that group differences, showed in the ReHo analysis, reflect limited regional neuronal synchronization in (C)APD, which might mean that detected neurons do not behave in a coherent fashion during rest. However, considering the fact that physiology underlying spontaneous BOLD response might be different to that when performing a task, it is under debate whether alternations found in this study directly underlie behavioral problems manifested by individuals with (C)APD.
Finally, although we performed ICA with different model orders, we only selected components which represented DMN and compared that particular components with the results obtained with ReHo. The rationale was that from all the reported resting-state brain networks, only DMN is considered to be involved in the introspective modes of cognition, encompassing the shift between the internally and the externally directed attention . Nevertheless, it is possible that selecting components reflecting different resting state networks would provide additional valuable results.
Since the ReHo approach revealed significant differences in DMN in children with (C)APD, relative to controls, we conclude that this matter deserves further consideration. Applying different neuropsychological and neuroimaging methods (including also task-based fMRI paradigms) might be helpful in differentiating developmental CAPD from other developmental cognitive disorders and further elucidate the neural basis of (C)APD.