Fine-scale striatal parcellation using diffusion MRI tractography and graph neural networks.

The striatum, a crucial part of the basal ganglia, plays a key role in various brain functions through its interactions with the cortex. The complex structural and functional diversity across subdivisions within the striatum highlights the necessity for precise striatal segmentation. In this study, we introduce a novel deep clustering pipeline for automated, fine-scale parcellation of the striatum using diffusion MRI (dMRI) tractography.

Amygdala-centered fusional connections characterized nonmotor symptoms in Parkinson's disease.

The importance of nonmotor symptoms in understanding the pathogenesis of the heterogeneity of Parkinson's disease has been highlighted. However, the validation of specific brain network biomarkers in nonmotor symptom subtypes is currently lacking. By performing a new approach to compute functional connectivity with structural prior using magnetic resonance imaging, the present study computed both functional connectivity and fusional connectivity features in the nonmotor symptom subtypes of Parkinson's disease, one characterized by cognitive impairment with late onset and the other depression with early onset.

An integrative multi-omics approach reveals metabolic mechanism of flavonoids during anaerobic fermentation of de'ang pickled tea.

Anaerobic fermentation (AF) is critical process for Yunnan De'ang pickled tea production. Therefore, widely targeted metabolomics and metagenomics were integrated to reveal the AF mechanism. Lactic acid bacteria (LAB) (e.

The mediation role of gray matter volume in the relationship between childhood maltreatment and psychological resilience in adolescents with first-episode major depressive disorder.

Previous studies have revealed morphologic alterations in patients with major depressive disorder (MDD) with experiences of childhood trauma. However, the underlying neural mechanisms remain largely unknown. This study aims to explore the brain structural changes and their possible mediation role in the relationship between childhood maltreatment and psychological resilience in drug-naïve adolescents with first-episode MDD.

Neural signatures of default mode network subsystems in first-episode, drug-naive patients with major depressive disorder after 6-week thought induction psychotherapy treatment.

Evidence indicates that the default mode network (DMN) plays a crucial role in the neuropathology of major depressive disorder (MDD). However, the neural signatures of DMN subsystems in MDD after low resistance Thought Induction Psychotherapy (TIP) remain incompletely understood. We collected functional magnetic resonance imaging data from 20 first-episode, drug-naive MDD and 20 healthy controls (HCs).

Enhanced group-level dorsolateral prefrontal cortex subregion parcellation through functional connectivity-based distance-constrained spectral clustering with application to autism spectrum disorder.

The dorsolateral prefrontal cortex (DLPFC) assumes a central role in cognitive and behavioral control, emerging as a crucial target region for interventions in autism spectrum disorder neuroregulation. Consequently, we endeavor to unravel the functional subregions within the DLPFC to shed light on the intricate functions of the brain. We introduce a distance-constrained spectral clustering (SC-DW) methodology that leverages functional connection to identify distinctive functional subregions within the DLPFC.

Comprehensive exploration of multi-modal and multi-branch imaging markers for autism diagnosis and interpretation: insights from an advanced deep learning model.

Autism spectrum disorder is a complex neurodevelopmental condition with diverse genetic and brain involvement. Despite magnetic resonance imaging advances, autism spectrum disorder diagnosis and understanding its neurogenetic factors remain challenging. We propose a dual-branch graph neural network that effectively extracts and fuses features from bimodalities, achieving 73.

Effects of rTMS Intervention on Functional Neuroimaging Activities in Adolescents with Major Depressive Disorder Measured Using Resting-State fMRI.

Repetitive transcranial magnetic stimulation (rTMS) to the left dorsolateral prefrontal cortex (L-DLPFC) is commonly used for the clinical treatment of major depressive disorder (MDD). The neuroimaging biomarkers and mechanisms of rTMS are still not completely understood. This study aimed to explore the functional neuroimaging changes induced by rTMS in adolescents with MDD.

Cortical thickness reductions associate with brain network architecture in major depressive disorder.

Background: Cortical thickness reductions in major depressive disorder are distributed across multiple regions. Research has indicated that cortical atrophy is influenced by connectome architecture on a range of neurological and psychiatric diseases. However, whether connectome architecture contributes to changes in cortical thickness in the same manner as it does in depression is unclear.

Widely targeted metabolomics and HPLC analysis elaborated the quality formation of Yunnan pickled tea during the whole process at an industrial scale.

Yunnan pickled tea is produced from fresh tea-leaves through fixation, rolling, anaerobic fermentation and sun-drying. In this study, widely targeted metabolomics using UHPLC-QQQ-MS/MS and HPLC analysis were carried out to elaborate its quality formation during the whole process. Results confirmed the contribution of preliminary treatments and anaerobic fermentation to the quality formation.

Disrupted functional networks within white-matter served as neural features in adolescent patients with conduct disorder.

Background: Conduct disorder (CD) has been conceptualized as a psychiatric disorder associated with white-matter (WM) structural abnormalities. Although diffusion tensor imaging could identify WM structural architecture changes, it cannot characterize functional connectivity (FC) within WM. Few studies have focused on disentangling the WM dysfunctions in CD patients by using functional magnetic resonance imaging (fMRI).

Depression mediated the relationships between precentral-subcortical causal links and motor recovery in spinal cord injury patients.

Depression after brain damage may impede the motivation and consequently influence the motor recovery after spinal cord injury (SCI); however, the neural mechanism underlying the psychological effects remains unclear. This study aimed to examine the casual connectivity changes of the emotion-motivation-motor circuit and the potential mediating effects of depression on motor recovery after SCI. Using the resting-state functional magnetic resonance imaging data of 35 SCI patients (24 good recoverers, GR and 11 poor recoverers, PR) and 32 healthy controls (HC), the results from the conditional Granger causality (GC) analysis demonstrated that the GR group exhibited sparser emotion-motivation-motor GC network compared with the HC and PR groups, though the in-/out-degrees of the emotion subnetwork and the motor subnetwork were relatively balanced in the HC and GR group.

Shared and distinct patterns of dynamic functional connectivity variability of thalamo-cortical circuit in bipolar depression and major depressive disorder.

Evidence has indicated abnormalities of thalamo-cortical functional connectivity (FC) in bipolar disorder during a depressive episode (BDD) and major depressive disorder (MDD). However, the dynamic FC (dFC) within this system is poorly understood. We explored the thalamo-cortical dFC pattern by dividing thalamus into 16 subregions and combining with a sliding-window approach.

Brain functional activity-based classification of autism spectrum disorder using an attention-based graph neural network combined with gene expression.

Autism spectrum disorder (ASD) is a complex brain neurodevelopmental disorder related to brain activity and genetics. Most of the ASD diagnostic models perform feature selection at the group level without considering individualized information. Evidence has shown the unique topology of the individual brain has a fundamental impact on brain diseases.

An individual-level weighted artificial neural network method to improve the systematic bias in BrainAGE analysis.

BrainAGE is a commonly used machine learning technique to measure the accelerated/delayed development pattern of human brain structure/function with neuropsychiatric disorders. However, recent studies have shown a systematic bias ("regression toward mean" effect) in the BrainAGE method, which indicates that the prediction error is not uniformly distributed across Chronological Ages: for the older individuals, the Brain Ages would be under-estimated but would be over-estimated for the younger individuals. In the present study, we propose an individual-level weighted artificial neural network method and apply it to simulation datasets (containing 5000 simulated subjects) and a real dataset (containing 135 subjects).

Multidisciplinary collaboration in diagnosis and treatment of neuroleptic malignant syndrome complicated with pneumonia: report of three cases.

Background: Neuroleptic malignant syndrome (NMS) is a relatively rare and a potentially fatal syndrome. It is a serious complication associated with antipsychotic therapy. NMS is easily prone to pneumonia, rhabdomyolysis and other problems.

Disorder-specific impaired neurocognitive function in major depression and generalized anxiety disorder.

Background: Generalized anxiety disorder (GAD) and major depressive disorder (MDD) are both highly prevalent and comorbid psychiatric disorders. Neurocognitive dysfunction has been commonly found in MDD, but the findings in GAD are inconsistent. Few studies have directly compared cognitive performance between GAD and MDD.

Different functional connectivity optimal frequency in autism compared with healthy controls and the relationship with social communication deficits: Evidence from gene expression and behavior symptom analyses.

Studies have reported that different brain regions/connections possess distinct frequency properties, which are related to brain function. Previous studies have proposed altered brain activity frequency and frequency-specific functional connectivity (FC) patterns in autism spectrum disorder (ASD), implying the varied dominant frequency of FC in ASD. However, the difference of the dominant frequency of FC between ASD and healthy controls (HCs) remains unclear.

Classification of major depressive disorder using an attention-guided unified deep convolutional neural network and individual structural covariance network.

Major depressive disorder (MDD) is the second leading cause of disability worldwide. Currently, the structural magnetic resonance imaging-based MDD diagnosis models mainly utilize local grayscale information or morphological characteristics in a single site with small samples. Emerging evidence has demonstrated that different brain structures in different circuits have distinct developmental timing, but mature coordinately within the same functional circuit.