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Previous neuroimaging studies have revealed abnormal functional connectivity of brain networks in patients with major depressive disorder (MDD), but findings have been inconsistent. A recent big‐data study found abnormal intrinsic functional connectivity within the default mode network in patients with recurrent MDD but not in first‐episode drug‐naïve patients with MDD. This study also provided evidence for reduced default mode network functional connectivity in medicated MDD patients, raising the question of whether previously observed abnormalities may be attributable to antidepressant effects. The present study (ClinicalTrials.gov identifier: NCT03294525) aimed to disentangle the effects of antidepressant treatment from the pathophysiology of MDD and test the medication normalization hypothesis. Forty‐one first‐episode drug‐naïve MDD patients were administrated antidepressant medication (escitalopram or duloxetine) for 8 weeks, with resting‐state functional connectivity compared between posttreatment and baseline. To assess the replicability of the big‐data finding, we also conducted a cross‐sectional comparison of resting‐state functional connectivity between the MDD patients and 92 matched healthy controls. Both Network‐Based Statistic analyses and large‐scale network analyses revealed intrinsic functional connectivity decreases in extensive brain networks after treatment, indicating considerable antidepressant effects. Neither Network‐Based Statistic analyses nor large‐scale network analyses detected significant functional connectivity differences between treatment‐naïve patients and healthy controls. In short, antidepressant effects are widespread across most brain networks and need to be accounted for when considering functional connectivity abnormalities in MDD., The present study aimed to disentangle the effects of antidepressant treatment from the pathophysiology of MDD and test the medication normalization hypothesis. Both Network‐Based Statistic analyses and large‐scale network analyses revealed intrinsic functional connectivity decreases in extensive brain networks after treatment, while no significant functional connectivity differences were found between treatment‐naïve patients and healthy controls. These results indicate that antidepressant effects are widespread across most brain networks and need to be accounted for when considering functional connectivity abnormalities in MDD.

Concerns regarding reproducibility of resting-state functional magnetic resonance imaging (R-fMRI) findings have been raised. Little is known about how to operationally define R-fMRI reproducibility and to what extent it is affected by multiple comparison correction strategies and sample size. We comprehensively assessed two aspects of reproducibility, test-retest reliability and replicability, on widely used R-fMRI metrics in both between-subject contrasts of sex differences and within-subject comparisons of eyes-open and eyes-closed (EOEC) conditions. We noted permutation test with Threshold-Free Cluster Enhancement (TFCE), a strict multiple comparison correction strategy, reached the best balance between family-wise error rate (under 5%) and test-retest reliability/replicability (e.g., 0.68 for test-retest reliability and 0.25 for replicability of amplitude of low-frequency fluctuations (ALFF) for between-subject sex differences, 0.49 for replicability of ALFF for within-subject EOEC differences). Although R-fMRI indices attained moderate reliabilities, they replicated poorly in distinct datasets (replicability

Recent imaging connectome studies demonstrated that the human functional brain network follows an efficient small-world topology with cohesive functional modules and highly connected hubs. However, the functional motif patterns that represent the underlying information flow remain largely unknown. Here, we investigated motif patterns within directed human functional brain networks, which were derived from resting-state functional magnetic resonance imaging data with controlled confounding hemodynamic latencies. We found several significantly recurring motifs within the network, including the two-node reciprocal motif and five classes of three-node motifs. These recurring motifs were distributed in distinct patterns to support intra- and inter-module functional connectivity, which also promoted integration and segregation in network organization. Moreover, the significant participation of several functional hubs in the recurring motifs exhibited their critical role in global integration. Collectively, our findings highlight the basic architecture governing brain network organization and provide insight into the information flow mechanism underlying intrinsic brain activities. Hum Brain Mapp 38:2734-2750, 2017. © 2017 Wiley Periodicals, Inc.

We used resting-state functional MRI to investigate spatial patterns of spontaneous brain activity in 22 healthy elderly subjects, as well as 16 mild cognitive impairment (MCI) and 16 Alzheimer's disease (AD) patients. The pattern of intrinsic brain activity was measured by examining the amplitude of low-frequency fluctuations (ALFF) of blood oxygen level dependent signal during rest. There were widespread ALFF differences among the three groups throughout the frontal, temporal, and parietal cortices. Both AD and MCI patients showed decreased activity mainly in the medial parietal lobe region and lentiform nucleus, while there was increased activity in the lateral temporal regions and superior frontal and parietal regions as compared with controls. Compared with MCI, the AD patients showed decreased activity in the medial prefrontal cortex and increased activity in the superior frontal gyrus and inferior and superior temporal gyri. Specifically, the most significant ALFF differences among the groups appeared in the posterior cingulate cortex, with a reduced pattern of activity when comparing healthy controls, MCI, and AD patients. Additionally, we also showed that the regions with ALFF changes had significant correlations with the cognitive performance of patients as measured by mini-mental state examination scores. Finally, while taking gray matter volume as covariates, the ALFF results were approximately consistent with those without gray matter correction, implying that the functional analysis could not be explained by regional atrophy. Together, our results demonstrate that there is a specific pattern of ALFF in AD and MCI, thus providing insights into biological mechanisms of the diseases.