Biology subjects

Mei, T.

Publications and source records attributed to Mei, T..

5 recordsLinked to original sources

bioRxiv2025

The Neural Architecture of Dream Recall Frequency: Insights from Interindividual Variations in Brain Structure and Function

Dreaming represents a complex and universal aspect of human sleep, yet it remains an intriguing phenomenon, with the neural mechanisms underlying dream experiences and their frequency not fully understood. This study employs a multimodal neuroimaging approach, integrating quantitative multi-parameter mapping, diffusion tensor imaging, and resting-state functional MRI, to investigate the neural correlates of dream recall frequency (DRF) in a large cohort of 258 healthy individuals. By employing Linked Independent Component Analysis (LICA), we were able to discern distinctive patterns of brain structure and function that correlated with variations in DRF. Our findings elucidate a complex relationship between dream recall and brain microstructure integrity, particularly in white matter regions of the orbitofrontal cortex, parahippocampal gyrus, superior parietal lobule, and occipital cortex. Higher DRF was related to increased white matter microstructure integrity in these regions and decreased gray matter volume in occipital and temporal areas. In terms of functional measures, higher DRF was associated with reduced connectivity across a range of resting-state networks, including the default mode, visual, and dorsal attention networks. This was particularly evident in the right precuneus and posterior cingulate cortex. These results suggest that enhanced dream recall may be related to the organization of higher-order visual and cognitive processing areas, supporting a top-down model of dreaming. This study contributes to a more comprehensive understanding of the neural substrates underlying individual differences in dream recall, offering a foundation for future investigations into the neurobiology and causal relationships of dreaming.

neuroscience↗

bioRxiv2023

Probing the DCAF12 interactions with MAGEA3 and CCT5 C-terminal degrons

DCAF12 is the substrate recognition component of the CRL4 E3 ligase complex that can recognize C-terminal double-glutamic acid degrons to promote degradation of its cognate substrates via the ubiquitin proteasome system. MAGEA3 and CCT5 proteins were reported to be cellular targets of DCAF12. To further characterize the DCAF12 interactions with both MAGEA3 and CCT5, we developed a suite of biophysical and a proximity-based cellular NanoBRET assays showing that both MAGEA3 and CCT5 C-terminal degron peptides interact with DCAF12 in nanomolar affinity in vitro and in cells. Furthermore, we report here the 3.17 [A] cryo-EM structure of DCAF12-DDB1-MAGEA3 complex revealing the key DCAF12 residues involved in C-terminal degron recognition and binding. Our study provides new tools and resources to enable the discovery of small molecule handles targeting the WDR domain of DCAF12 for future PROTAC design and development.

biochemistry↗

bioRxiv2022

Autism is associated with inter-individual variations of gray and white matter morphology

BackgroundAlthough many studies have explored atypicalities in gray and white matter (GM, WM) morphology of autism, most of them rely on unimodal analyses that do not benefit from the likelihood that different imaging modalities may reflect common neurobiology. We aimed to establish multimodal brain patterns that differentiate between autism and typically developing (TD) controls and explore associations between these brain patterns and clinical measures. MethodsWe studied 183 individuals with autism and 157 TD individuals (6-30 years) in a large deeply phenotyped autism dataset (EU-AIMS LEAP). Linked Independent Component Analysis was utilized to link all participants GM and WM images, and group comparisons of modality shared variances were examined. Subsequently, we performed a canonical correlation analysis to explore the aggregated effects between all multimodal GM-WM covariations and clinical profiles. ResultsOne multimodal pattern was significantly related to autism. This pattern was primarily associated with GM in bilateral insula, frontal, pre- and post-central, cingulate, and caudate areas, and co-occurred with altered WM features in the superior longitudinal fasciculus. The canonical analysis showed a significant multivariate correlation primarily between multimodal brain patterns that involved variation of corpus callosum, and symptoms of social affect in the autism group. ConclusionsOur findings demonstrate the assets of integrated analyses of GM and WM alterations to study the brain mechanisms that underpin autism, and show that the complex clinical autism phenotype can be interpreted by multimodal brain patterns that are spread across the brain involving both cortical and subcortical areas.

neuroscience↗

bioRxiv2020

Gray matter covariations and core symptoms of autism. The EU-AIMS Longitudinal European Autism Project

BackgroundVoxel-based Morphometry (VBM) studies in Autism Spectrum Disorder (autism) have yielded diverging results. This might partly be attributed to structural alterations being associating with the combined influence of several regions rather than with a single region. Further, these structural covariation differences may relate to continuous measures of autism rather than with categorical case-control contrasts. The current study aimed to identify structural covariation alterations in autism, and assessed canonical correlations between brain covariation patterns and core autism symptoms. MethodsWe studied 347 individuals with autism and 252 typically developing individuals, aged between 6 and 30 years, who have been deeply phenotyped in the Longitudinal European Autism Project (LEAP). All participants VBM maps were decomposed into spatially independent components using Independent Component Analysis. A Generalized Linear Model (GLM) was used to examine case-control differences. Next, Canonical Correlation Analysis (CCA) was performed to separately explore the integrated effects between all the brain sources of gray matter variation and two sets of core autism symptoms. ResultsGLM analyses showed significant case-control differences for two independent components. The first component was primarily associated with decreased density of bilateral insula, inferior frontal gyrus, orbitofrontal cortex, and increased density of caudate nucleus in the autism group relative to typically developing individuals. The second component was related to decreased densities of the bilateral amygdala, hippocampus, and parahippocampal gyrus in the autism group relative to typically developing individuals. The CCA results showed significant correlations between components that involved variation of thalamus, putamen, precentral gyrus, frontal, parietal, and occipital lobes, and the cerebellum, and repetitive, rigid and stereotyped behaviors and abnormal sensory behaviors in autism individuals. LimitationsOnly 55.9% of the participants with autism had complete questionnaire data on continuous parent-reported symptom measures. ConclusionsCovaried areas associated with autism diagnosis and/or symptoms are scattered across the whole brain and include the limbic system, basal ganglia, thalamus, cerebellum, precentral gyrus, and parts of the frontal, parietal, and occipital lobes. Some of these areas potentially subserve social-communicative behavior whereas others may underpin sensory processing and integration, and motor behavior.

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↗