Altered resting-state functional connectivity (rsFC) has been noted in large-scale functional networks in attention-deficit/hyperactivity disorder (ADHD). However, identifying consistent abnormalities of functional networks is difficult due to varied methods and results across studies. To integrate rsFC alterations and search for coherent patterns of intrinsic functional network impairments in ADHD, this research conducts a coordinate-based meta-analysis of voxel-wise seed-based rsFC studies comparing rsFC between ADHD patients and healthy controls. A total of 25 datasets from 21 studies including 700 ADHD patients and 580 controls were analyzed. We extracted the coordinates of seeds and between-group effects. Each seed was then categorized into a seed-network by its location within priori 7-network parcellations. Then, pooled meta-analyses were conducted for the default mode network (DMN), frontoparietal network (FPN) and affective network (AN) separately, but not for the ventral attention network (VAN), dorsal attention network (DAN), somatosensory network (SSN) and visual network due to a lack of primary studies. The results showed that ADHD was characterized by hyperconnectivity between the FPN and regions of the DMN and AN as well as hypoconnectivity between the FPN and regions of the VAN and SSN. These findings not only support the triple-network model of pathophysiology associated with ADHD but also extend this model by highlighting the involvement of the SSN and AN in the mechanisms of network interactions that may account for motor hyperactivity and impulsive symptoms.

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BackgroundAlthough dysfunction of amygdala-related circuits is centrally implicated in major depressive disorder (MDD), little is known about how this dysfunction differs between adult and adolescent MDD patients.MethodsVoxel-wise meta-analyses of abnormal amygdala resting-state functional connectivity (rsFC) were conducted in adult and adolescent groups separately, followed by a quantitative meta-analytic comparison of the two groups.FindingsNineteen studies that included 665 MDD patients (392 adults and 273 adolescents) and 546 controls (341 adults and 205 adolescents) were identified in the current study. Adult-specific abnormal amygdala rsFC in MDD patients compared to that in controls was located mainly within the affective network, including increased connectivity with the right hippocampus/parahippocampus and bilateral ventromedial orbitofrontal cortex and decreased connectivity with the bilateral insula and the left caudate. Adolescent MDD patients specifically demonstrated decreased amygdala rsFC within the cognitive control network encompassing the left dorsolateral prefrontal cortex and imbalanced amygdala rsFC within the default mode network, which was manifested as hyperconnectivity in the right precuneus and hypoconnectivity in the right inferior temporal gyrus. Additionally, direct comparison between the two groups showed that adult patients had strengthened amygdala rsFC with the right hippocampus/parahippocampus as well as the right inferior temporal gyrus and weakened amygdala rsFC with the bilateral insula compared to that in adolescent patients.InterpretationDistinct impairments of amygdala-centered rsFC in adult and adolescent patients were related to different network dysfunctions in MDD. Adult-specific amygdala rsFC dysfunction within the affective network presumably reflects emotional dysregulation in MDD, whereas adolescent-specific amygdala rsFC abnormalities in networks involved in cognitive control might reflect the neural basis of affective cognition deficiency that is characteristic of adolescent MDD.FundThis study was supported by a grant from the National Natural Science Foundation of China (81671669) and by a Sichuan Provincial Youth Grant (2017JQ0001).

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Background: Bipolar disorder (BD) is a mental disorder characterized by mood fluctuations between an acute episodic state of either mania or depression and a clinically remitted state. Dysfunction of large-scale intrinsic brain networks has been demonstrated in this disorder, but it remains unknown whether those network alterations are related to different states. Methods: In the present study, we performed a meta-analysis of whole-brain seed-based resting-state functional connectivity (rsFC) studies in BD patients to compare the intrinsic function of brain networks between episodic and remitted states. Thirty-nine seed-based voxel-wise rsFC datasets from thirty publications (1047 BD patients vs 1081 controls) were included in the meta-analysis. Seeds were categorized into networks by their locations within a priori functional networks. Seed-based d mapping analysis of between-state effects identified brain systems in which different states were associated with increased connectivity or decreased connectivity within and between each seed network. Findings: We found that BD patients presented decreased connectivity within the affective network (AN) in acute episodes but not in the remitted state of the illness. Similar decreased connectivity within the defaultmode network (DMN) was also found in the acute state, but it was replaced by increased connectivity in the remitted state. In addition, different patterns of between-network dysconnectivity were observed between the acute and remitted states. Interpretation: This study is the first to identify different patterns of intrinsic function in large-scale brain networks between the acute and remitted states of BD through meta-analysis. The findings suggest that a shift in network function between the acute and remitted states may be related to distinct emotional and cognitive dysfunctions in BD, which may have important implications for identifying clinically relevant biomarkers to guide alternative treatment strategies for BD patients during active episodes or remission.

Previous resting-state functional magnetic resonance imaging (rs-fMRI) studies of obsessive-compulsive disorder (OCD) have facilitated our understanding of OCD pathophysiology based on its intrinsic activity. However, whether the group difference derived from univariate analysis could be useful for informing the diagnosis of individual OCD patients remains unclear. We aimed to apply multivariate pattern analysis of different rs-fMRI parameters to distinguish drug-naive patients with OCD from healthy control subjects (HCS). Fifty-four drug-naive OCD patients and 54 well-matched HCS were recruited. Four different rs-fMRI parameter maps, including the amplitude of low-frequency fluctuations (ALFF), fractional amplitude of low-frequency fluctuations (fALFF), regional homogeneity (ReHo) and functional connectivity strength (FCS), were calculated. Training of a support vector machine (SVM) classifier using rs-fMRI maps produced voxelwise discrimination maps. Overall, the classification accuracies were acceptable for the four rs-fMRI parameters. Excellent performance was achieved when ALFF maps were employed (accuracy, 95.37%, p < 0.01), good performance was achieved by using ReHo maps, weaker performance was achieved by using fALFF maps, and fair performance was achieved by using FCS maps. The brain regions showing the greatest discriminative power included the prefrontal cortex, anterior cingulate cortex, precentral gyrus, and occipital lobes. The application of SVM to rs-fMRI features may provide potential power for OCD classification.

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