In recent years, machine learning techniques have received increasing attention as a promising approach to differentiating patients from healthy subjects. Therefore, some resting-state functional magnetic resonance neuroimaging (R-fMRI) studies have used interregional functional connections as discriminative features. The aim of this study was to investigate ADHD-related spatially distributed discriminative features derived from wholebrain resting-state functional connectivity patterns using machine learning. Patients and Methods: We measured the interregional functional connections of the R-fMRI data from 40 ADHD patients and 28 matched typically developing controls. Machine learning was used to discriminate ADHD patients from controls. Classification performance was assessed by permutation tests. Results: The results from the model with the highest classification accuracy showed that 85.3% of participants were correctly identified using leave-one-out cross-validation (LOOV) with support vector machine (SVM). The majority of the most discriminative functional connections were located within or between the cerebellum, default mode network (DMN) and frontoparietal regions. Approximately half of the most discriminative connections were associated with the cerebellum. The cerebellum, right superior orbitofrontal cortex, left olfactory cortex, left gyrus rectus, right superior temporal pole, right calcarine gyrus and bilateral inferior occipital cortex showed the highest discriminative power in classification. Regarding the brain-behaviour relationships, some functional connections between the cerebellum and DMN regions were significantly correlated with behavioural symptoms in ADHD (P < 0.05). Conclusion: This study indicated that whole-brain resting-state functional connections might provide potential neuroimaging-based information for clinically assisting the diagnosis of ADHD.

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The putamen is a neural hub which integrates projections from diverse cortical regions and relays to the thalamus and other cortex regions. Numerous studies have reported morphological and functional abnormalities in the putamen. For example, a previous structural magnetic resonance imaging (MRI) study found that participants with ADHD had significantly smaller volume in the putamen than healthy controls. 7 A meta-analysis study has also documented the putamen abnormality in children with ADHD. 8 Abnormal functional connectivity between the putamen and thalamic regions related to spatial working memory processing was observed in ADHD. 9 A resting-state functional MRI (R-fMRI) study observed altered functional connectivity of the putamen in ADHD patients. 10 These studies indicated that the alterations in the putamen may involve ADHD.Granger causality analysis (GCA) is an approach to identify whether the current time series in a brain region or network (X) can be predicted by the past time series of another (Y). GCA