A5100329091- Functional Brain Connectivity Studies
- EEG and Brain-Computer Interfaces
- Neural dynamics and brain function
- Neural and Behavioral Psychology Studies
- Renin-Angiotensin System Studies
- Psychology of Moral and Emotional Judgment
- Stress Responses and Cortisol
- Face Recognition and Perception
- Cell Image Analysis Techniques
- Advanced MRI Techniques and Applications
- Memory and Neural Mechanisms
- Advanced Neuroimaging Techniques and Applications
- Neuroscience and Music Perception
- Genomics and Phylogenetic Studies
- Nanomaterials for catalytic reactions
- Statistical Methods and Inference
- Sleep and Wakefulness Research
- Blood Pressure and Hypertension Studies
- Adsorption and biosorption for pollutant removal
- Cancer, Stress, Anesthesia, and Immune Response
- Traditional and Medicinal Uses of Annonaceae
- Mental Health Research Topics
- Neuroendocrine regulation and behavior
- Synthetic Organic Chemistry Methods
- Electrochemical sensors and biosensors
Guiyang Medical University
2024
Max Planck Institute for Human Cognitive and Brain Sciences
2021-2024
Essen University Hospital
2023-2024
Shenzhen Technology University
2023
University of Electronic Science and Technology of China
2022
University of Cambridge
2022
Army Medical College
2022
Army Medical University
2022
Chongqing University
2015-2022
OriginWater (China)
2022
In this paper, we report a knowledge-based potential function, named the OPUS-Ca potential, that requires only Calpha positions as input. The contributions from other atomic were established pseudo-positions artificially built trace for auxiliary purposes. function is formed based on seven major representative molecular interactions in proteins: distance-dependent pairwise energy with orientational preference, hydrogen bonding energy, short-range packing tri-peptide three-body and solvation...
Abstract Reconstructing axonal projections of single neurons at the whole-brain level is currently a converging goal neuroscience community that fundamental for understanding logic information flow in brain. Thousands from different brain regions have recently been morphologically reconstructed, but corresponding physiological functional features these reconstructed are unclear. By combining two-photon Ca 2+ imaging with targeted single-cell plasmid electroporation, we reconstruct brain-wide...
Sleep deprivation is a prevalent issue that impacts cognitive function. Although numerous neuroimaging studies have explored the neural correlates of sleep loss, inconsistencies persist in reported results, necessitating an investigation into consistent brain functional changes resulting from loss.
BACKGROUND Adolescent major depressive disorder (MDD) is a significant mental health concern that often leads to recurrent depression in adulthood. Resting-state functional magnetic resonance imaging (rs-fMRI) offers unique insights into the neural mechanisms underlying this condition. However, despite previous research, specific vulnerable brain regions affected adolescent MDD patients have not been fully elucidated. AIM To identify consistent using rs-fMRI and activation likelihood...
Waiting is an indispensable and inevitable part of man-machine voice interaction. The user interface (VUI) feedback mechanism a key factor affecting interaction's waiting experience. time most available interfaces fixed or decided by the processing hardware software, which has not been designed cannot offer users good interaction In this paper, speech rate user-machine collected through prototype experimentation. Besides, users' perception different interfaces' settings studied based on...
Abstract While disgust originates in the hard-wired mammalian distaste response, conscious experience of humans strongly depends on subjective appraisal and may even extend to sociomoral contexts. In a series studies, we combined functional magnetic resonance imaging (fMRI) with machine-learning based predictive modeling establish comprehensive neurobiological model disgust. The developed neurofunctional signature accurately predicted momentary self-reported across discovery ( n =78)...
Major depressive disorder (MDD) in adolescents and young adults contributes significantly to global morbidity, with inconsistent findings on brain structural changes from magnetic resonance imaging studies. Activation likelihood estimation (ALE) offers a method synthesize these diverse identify consistent anomalies.
Nanopore sequencing, also known as single-molecule real-time is a third/fourth generation sequencing technology that enables deciphering single DNA/RNA molecules without the polymerase chain reaction. Although nanopore has made significant progress in scientific research and clinical practice, its application been limited compared with next-generation (NGS) due to specific design principle data characteristics, especially hotspot mutation detection. Therefore, we developed Nano2NGS-Muta...
A mechanism involving transient transmembrane secretion of H<sub>2</sub>O<sub>2</sub> for the citral-caused inhibition aflatoxin production from a fungus was revealed.
A new and highly efficient annulation-retro-Claisen cascade, which involves the [4 + 1] or [5 annulation of α-benzoylacetates with bielectrophilic peroxides a subsequent debenzoylation process under mild basic conditions, has been developed for rapid construction valuable tetrahydrofuran- dihydropyran-2-carboxylates in good yields. By employing reaction, unified total synthesis γ- δ-lactone natural products such as (±)-tanikolide, (±)-goniothalamins, (±)-7-epi-goniodiol, (±)-plakolide...
ABSTRACT Establishing replicable inter-individual brain-wide associations is key to advancing our understanding of the crucial links between brain structure, function, and behavior, as well applying this knowledge in clinical contexts. While replicability sample size requirements for anatomical functional MRI-based brain-behavior have been extensively discussed recently, systematic assessments are still lacking diffusion-weighted imaging (DWI), despite it being dominant non-invasive method...
Understanding large-scale brain dynamics is a grand challenge in neuroscience. We propose functional connectome-based Hopfield Neural Networks (fcHNNs) as model of macro-scale dynamics, arising from recurrent activity flow among regions. An fcHNN neither optimized to mimic certain characteristics, nor trained solve specific tasks; its weights are simply initialized with empirical connectivity values. In the framework, understood relation so-called attractor states, i.e. neurobiologically...
Understanding large-scale brain dynamics is a grand challenge in neuroscience. We propose functional connectome-based Hopfield Neural Networks (fcHNNs) as model of macro-scale dynamics, arising from recurrent activity flow among regions. An fcHNN neither optimized to mimic certain characteristics, nor trained solve specific tasks; its weights are simply initialized with empirical connectivity values. In the framework, understood relation so-called attractor states, i.e. neurobiologically...
Abstract Understanding large-scale brain dynamics is a grand challenge in neuroscience. We propose functional connectome-based Hopfield Neural Networks (fcHNNs) as model of macro-scale dynamics, arising from recurrent activity flow among regions. An fcHNN neither optimized to mimic certain characteristics, nor trained solve specific tasks; its weights are simply initialized with empirical connectivity values. In the framework, understood relation so-called attractor states, i.e....
Abstract Multivariate predictive models play a crucial role in enhancing our understanding of complex biological systems and developing innovative, replicable tools for translational medical research. However, the complexity machine learning methods extensive data pre-processing feature engineering pipelines can lead to overfitting poor generalizability. An unbiased evaluation necessitates external validation, which involves testing finalized model on independent data. Despite its...
ABSTRACT Adaptive human learning utilizes reward prediction errors (RPEs) that scale the differences between expected and actual outcomes to optimize future choices. Depression has been linked with biased RPE signaling an exaggerated impact of negative on which may promote amotivation anhedonia. The present proof-of-concept study combined computational modelling multivariate decoding neuroimaging determine influence selective competitive angiotensin II type 1 receptor antagonist losartan...
Abstract The involvement of specific basal ganglia-thalamocortical circuits in response inhibition has been extensively mapped the last few decades. However, pivotal brain nodes and directed casual regulation within this inhibitory circuit humans remains controversial. Here, we capitalize on recent progress robust biologically plausible causal modelling (DCM-PEB) a large fMRI dataset (n=218) to determine key nodes, their modulation via biological variables (sex) performance control...
Abstract Adaptive human learning utilizes reward prediction errors (RPEs) that scale the differences between expected and actual outcomes to optimize future choices. Depression has been linked with biased RPE signaling an exaggerated impact of negative on which may promote amotivation anhedonia. The present proof-of-concept study combined computational modelling multivariate decoding neuroimaging determine influence selective competitive angiotensin II type 1 receptor antagonist losartan...
Abstract Exaggerated arousal and dysregulated emotion-memory interactions are key pathological dysregulations that accompany the development of post-traumatic stress disorder (PTSD). Current treatments for PTSD moderate efficacy preventing already during exposure to threatening events may attenuate PTSD-symptomatology. In a preregistered double-blind, between-subject, placebo-controlled pharmaco-fMRI design, present proof-of-concept study examined potential single dose angiotensin II type 1...
Abstract While disgust originates in the hard-wired mammalian distaste response, conscious experience of humans strongly depends on subjective appraisal and may even extend to sociomoral contexts. In a series studies, we combined functional magnetic resonance imaging (fMRI) with machine-learning based predictive modeling establish comprehensive neurobiological model disgust. The developed neurofunctional signature accurately predicted momentary self-reported across discovery (n=78)...