Biology subjects

Yan, C.-G.

Publications and source records attributed to Yan, C.-G..

4 recordsLinked to original sources

bioRxiv2018

Reduced but not Enhanced Default Mode Network Functional Connectivity in Major Depressive Disorder: Evidence from 25 Cohorts in the REST-meta-MDD Project

Major Depressive Disorder (MDD) is common and disabling, but its neural pathophysiology remains unclear. Functional brain network studies in MDD have largely had limited statistical power and data analysis approaches have varied widely. The REST-meta-MDD Project of resting-state fMRI (R-fMRI) addresses these issues. The 25 research groups in China composing the REST-meta-MDD Project contributed R-fMRI data of 1,300 patients with MDD and 1,128 normal controls (NCs). The data were preprocessed locally with a standardized protocol prior to aggregated group analyses. We focused on functional connectivity (FC) within the default mode network (DMN), frequently reported to show increased FC in MDD. We found decreased instead of increased DMN FC when comparing 848 MDDs with 794 NCs from 17 sites after data exclusion. We found FC reduction only in recurrent MDD, not in first-episode drug-naive MDD. Decreased DMN FC was associated with medication usage but not with MDD duration. DMN FC was also positively related to symptom severity but only in recurrent MDDs. Exploratory analyses also revealed alterations of local intrinsic activity in MDD. We confirmed the key role of DMN in MDD but found reduced rather than increased FC within the DMN. Future studies should test whether decreased DMN FC mediates treatment response. This manuscript announces the publicly available resting-state fMRI indices of the REST-meta-MDD consortium shared via the R-fMRI Maps Project.\n\nSIGNIFICANCE STATEMENTFunctional connectivity within the default mode network in major depressive disorder patients has been frequently reported abnormal but with contradicting directions in previous small sample size studies. By creating the REST-meta-MDD consortium containing neuroimaging data of 1,300 depressed patients and 1,128 normal controls from 25 research groups in China, we found decreased default mode network functional connectivity in depressed patients, driven by patients with recurrent depression, and associated with current medication treatment but not with disease duration. These findings suggest that default mode network functional connectivity remains a prime target for understanding the pathophysiology of depression, with particular relevance to revealing mechanisms of effective treatments.

neuroscience↗

bioRxiv2018

Physiological Significance of R-fMRI Indices in Detecting Structural Brain Lesions

Resting-state functional MRI (R-fMRI) research has recently entered the era of \"big data\", however, few studies have provided a rigorous validation of the physiological underpinnings of R-fMRI indices. Although studies have reported that various neuropsychiatric disorders exhibit abnormalities in R-fMRI measures, these \"biomarkers\" have not been validated in differentiating structural lesions (brain tumors) as a concept proof. We enrolled 60 patients with intracranial tumors located in the unilateral cranial cavity and 60 matched normal controls to test whether R-fMRI indices can differentiate tumors, which represents a prerequisite for adapting such indices as biomarkers for neuropsychiatric disorders. Common R-fMRI indices of tumors and their counterpart control regions, which were defined as the contralateral normal areas (for amplitude of low frequency fluctuations (ALFF), fractional ALFF (fALFF), regional homogeneity (ReHo) and degree centrality (DC)) and ipsilateral regions surrounding the tumors (for voxel-mirrored homotopic connectivity (VMHC)), were comprehensively assessed. According to paired t-tests with a Bonferroni correction, only ALFF (both with and without Z-standardization) and VMHC (Fishers r-to-z transformed) could successfully differentiate substantial tumors from their counterpart normal regions in patients. And DC was not able to differentiate tumor from normal unless employed Z-standardization. To validate the lower power in the between-subject design than in the within-subject design, each metric was calculated in a matched control group, and two-sample t-tests were used to compare the patient tumors and the normal controls at the same area. Only ALFF (and that with Z-standardization) along with VMHC succeeded in differentiating significant differences between tumors and the sham tumors areas of normal controls. This study tested the premise of R-fMRI biomarkers for differentiating lesions, and brings a new understanding to physical significance of the Z-standardization.

neuroscience↗

bioRxiv2018

Altered Developmental Trajectories in Intrinsic Function between Default, Salience, and Executive Networks in High-Functioning Autism

Although many studies have focused on abnormal patterns of brain functional connectivity in Autism spectrum disorder (ASD), one important factor, the developmental effect of brain networks was largely overlooked. To clarify the abnormal developmental trajectory of brain functional connectivity in ASD, we focused on the age-related changes in three \"core\" neurocognitive networks: default mode network (DMN), salience network (SN) and central executive network (CEN, also divided into left and right CEN, i.e., lCEN and rCEN). The development of intrinsic functional connectivity (iFC) within and between these networks were analyzed in 107 Chinese participants, including children, adolescents, and adults (54 patients with ASD and 53 typically developed (TD) participants; ages 6-30 years). We found that diagnosis-related distinctions in age-related changes suggest three maturation patterns in networks or nodes iFC: delayed (iFC between SN and rCEN), ectopic (iFC between SN and DMN, and iFC between posterior cingulate cortex (PCC) and right anterior insula/dorsal anterior cingulate cortex (dACC)), and failure maturation (iFC between dACC and ventral medial prefrontal cortex). Compared with age-matched TD participants, ASD patients in children and adolescents exhibited hypo-connectivity, while that in adults showed hyper-connectivity. In addition, an independent verification based on Autism Brain Imaging Data Exchange (ABIDE) datasets confirmed our findings of developmental trajectories in ASD group, which also showed unchanged functional connectivity with age between DMN and SN and increasing iFC between rCEN and SN. The conspicuous differences in the development of three \"core\" networks in ASD were demonstrated, which may lead a nuanced understanding towards the abnormal brain network maturation trajectory of autism.

neuroscience↗

bioRxiv2017

A Comprehensive Assessment Of Reproducibility Of R-fMRI Metrics On The Impact Of Different Strategies For Multiple Comparison Correction And Small Sample Size

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 < 0.3 for between-subject sex differences, < 0.5 for within-subject EOEC differences). By randomly drawing different sample sizes from a single site, we found reliability, sensitivity and positive predictive value (PPV) rose as sample size increased. Small sample sizes (e.g., < 80 (40 per group)) not only minimized power (sensitivity < 2%), but also decreased the likelihood that significant results reflect \"true\" effects (PPV < 0.26) in sex differences. Our findings have implications for how to select multiple comparison correction strategies and highlight the importance of sufficiently large sample sizes in R-fMRI studies to enhance reproducibility.

neuroscience↗