Showing papers by "Xi-Nian Zuo published in 2023"
TL;DR: In this paper , the authors performed partial least squares regression and enrichment analysis to explore the relationship between gene transcriptional expression and the development of cortical thickness in childhood and adolescence, and found that the spatial model of normal cortical thinning during childhood and adolescent is associated with genes expressed predominantly in astrocytes, microglia, excitatory and inhibitory neurons.
Abstract: The cognitive and behavioral development of children and adolescents is closely related to the maturation of brain morphology. Although the trajectory of brain development has been depicted in detail, the underlying biological mechanism of normal cortical morphological development in childhood and adolescence remains unclear. By combining the Allen Human Brain Atlas dataset with two single‐site magnetic resonance imaging data including 427 and 733 subjects from China and the United States, respectively, we performed partial least squares regression and enrichment analysis to explore the relationship between the gene transcriptional expression and the development of cortical thickness in childhood and adolescence. We found that the spatial model of normal cortical thinning during childhood and adolescence is associated with genes expressed predominantly in astrocytes, microglia, excitatory and inhibitory neurons. Top cortical development‐related genes are enriched for energy‐related and DNA‐related terms and are associated with psychological and cognitive disorders. Interestingly, there is a great deal of similarity between the findings derived from the two single‐site datasets. This fills the gap between early cortical development and transcriptomes, which promotes an integrative understanding of the potential biological neural mechanisms.
2 citations
TL;DR: Yeo et al. as mentioned in this paper developed a model that integrates local and global approaches for estimating areal-level cortical parcellations, which is referred to as the Schaefer Parcellations.
1 citations
1 citations
TL;DR: In this article , the authors extended the frequency range and performed gradient analysis across multiple frequency bands of fast resting-state fMRI signals from the Human Connectome Project and condensed a frequency-rank cortical map of the highest gradient.
Abstract: The intrinsic organizational structure of the brain is reflected in spontaneous brain oscillations. Its functional integration and segregation hierarchy have been discovered in space by leveraging gradient approaches to low-frequency functional connectivity. This hierarchy of brain oscillations has not yet been fully understood, since previous studies have mainly concentrated on the brain oscillations from a single limited frequency range (~ 0.01-0.1 Hz). In this work, we extended the frequency range and performed gradient analysis across multiple frequency bands of fast resting-state fMRI signals from the Human Connectome Project and condensed a frequency-rank cortical map of the highest gradient. We found that the coarse skeletons of the functional organization hierarchy are generalizable across the multiple frequency bands. Beyond that, the highest integration levels of connectivity vary in the frequency domain across different large-scale brain networks. These findings are replicated in another independent dataset and demonstrated that different brain networks can integrate information at varying rates, indicating the significance of examining the intrinsic architecture of spontaneous brain activity from the perspective of multiple frequency bands.
TL;DR: In this article , a population neuro-geno-type gap exists due to high-altitude (HA) immigrants, and HA-related neurotypes are proposed to decipher their genetic roles.
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TL;DR: In this article , a large multi-site sample (1660 MDD patients vs. 1341 healthy controls) from Phase II of the Depression Imaging REsearch ConsorTium (DIRECT) was systematically delineated case-control difference maps of sgACC FC and examined their clinical relevance to previously identified TMS targets.
Abstract: The subgenual anterior cingulate cortex (sgACC) appears to play a central role in the pathophysiology of major depressive disorder (MDD). To wit, its functional interactive profile with the left dorsal lateral prefrontal cortex (DLPFC) has been shown to be related to treatment outcomes with transcranial magnetic stimulation (TMS) treatment outcomes. Nevertheless, previous research on sgACC functional connectivity (FC) in MDD has yielded inconsistent results, partly due to small sample sizes and limited statistical power of prior work. Here, leveraging a large multi-site sample (1660 MDD patients vs. 1341 healthy controls) from Phase II of the Depression Imaging REsearch ConsorTium (DIRECT), we systematically delineated case-control difference maps of sgACC FC and examined their clinical relevance to previously identified TMS targets. We also investigated case-control FC difference maps of left DLPFC sub-fields. In MDD patients we found significantly increased FC between sgACC and thalamus and reduced FC to a broad array of brain regions, including somatosensory area, occipital lobe, medial and lateral temporal lobe, and insular cortex, when global signal regression (GSR) was not implemented. Intriguingly, we found enhanced left DLPFC-sgACC FC in MDD patients when GSR was performed. We leveraged an prior independent sample to explore the possible relationship between the case-control differences regarding sgACC’s FC profiles and the treatment out comes of TMS. In sites in which open TMS treatment was administered, case-control differences in sgACC FC, with GSR, were related to clinical improvement. Next we tested whether the position of peak of the FC maps (previously identified TMS target) could be altered in MDD patients as compred with healthy controls (HC)s. We found the optimized TMS target differed in MDD patients. Several DLPFC sub-fields yielded case-control differences in whole-brain FC maps. In summary, we reliably delineated MDD-related abnormalities of sgACC FC profiles in a large sample. GSR was essential in applying case-control difference maps to identify optimized TMS targets. Our results highlight the functional heterogeneity of the left DLPFC and of precise TMS targets therein.
TL;DR: The Chinese Open Science Network (COSN) as mentioned in this paper was created to encourage early-career researchers in developing countries to start their own Open Science initiatives and engage in the global Open Science movement.
Abstract: Open Science is becoming a mainstream scientific ideology in psychology and related fields. However, researchers, especially early-career researchers (ECRs) in developing countries, are facing significant hurdles in engaging in Open Science and moving it forward. In China, various societal and cultural factors discourage ECRs from participating in Open Science, such as the lack of dedicated communication channels and the norm of modesty. To make the voice of Open Science heard by Chinese-speaking ECRs and scholars at large, the Chinese Open Science Network (COSN) was initiated in 2016. With its core values being grassroots-oriented, diversity, and inclusivity, COSN has grown from a small Open Science interest group to a recognized network both in the Chinese-speaking research community and the international Open Science community. So far, COSN has organized three in-person workshops, 12 tutorials, 48 talks, and 55 journal club sessions and translated 15 Open Science-related articles and blogs from English to Chinese. Currently, the main social media account of COSN (i.e., the WeChat Official Account) has more than 23,000 subscribers, and more than 1,000 researchers/students actively participate in the discussions on Open Science. In this article, we share our experience in building such a network to encourage ECRs in developing countries to start their own Open Science initiatives and engage in the global Open Science movement. We foresee great collaborative efforts of COSN together with all other local and international networks to further accelerate the Open Science movement.
TL;DR: In this paper , the authors compared seven common neuropsychiatric disorders, including depression, schizophrenia, bipolar disorder, depression, anxiety, and bipolar disorder with respect to the Lifespan Brain Chart.