Yu Zhang

Energy inefficiency underpinning brain state dysregulation in individuals with major depressive disorder

This study identifies energy inefficiency as a mechanism underlying brain state dysregulation in major depressive disorder, linking it to specific brain regions and biological factors.

Cross-Species Cortical Geometry Reveals Conserved Gradients Across Primates and Human-Specific Expansion

The paper develops a cross-species cortical alignment framework to analyze structural connectivity and cortical expansion across primates, revealing conserved geometric patterns and human-specific expansions.

Converging Topographic Axes of Connectivity and Genetic Architectures Scaffold Cortical Patterning

The paper identifies genetic and connectivity gradients that organize cortical patterning along three topographic axes.

Right posterior theta reflects human parahippocampal phase resetting by salient cues during goal-directed navigation

The paper investigates theta phase resetting in the human parahippocampal gyrus during navigation, finding it correlates with BOLD activation in specific PHG clusters.

BAI-Net: Individualized Anatomical Human Cerebral Cartography using Graph Convolutional Network

BAI-Net improves individualized brain mapping by integrating topological priors and connectivity data, showing better performance than traditional clustering methods.

Interpretable brain decoding from sensations to cognition to action: graph neural networks reveal the representational hierarchy of human cognition

This paper introduces biologically-constrained graph neural networks to decode cognitive processes, revealing functional gradients from sensation to cognition and showing improved inter-subject alignment and behavioral prediction.

Deep learning models of cognitive processes constrained by human brain connectomes

This study shows that deep graph neural networks using human connectomes improve cognitive decoding accuracy and robustness by integrating brain dynamics with high-order graph convolutions.

Uncovering the Genetic Profiles Underlying the Intrinsic Organization of the Human Cerebellum

The paper identifies 443 network-specific genes in the human cerebellum and links their co-expression patterns to intra-cerebellar functional connectivity, revealing gene subsets related to neurodevelopment and neurotransmission.

Representational learning of brain responses in executive function and higher-order cognition using deep graph convolutions

This paper uses deep graph convolutions to decode brain activity across cognitive domains, finding that integration boosts high-order cognition decoding while segregation suffices for motor tasks.

Functional Annotation of Human Cognitive States using Deep Graph Convolution

This paper develops a multidomain brain decoder to identify cognitive states from fMRI data with high accuracy across multiple cognitive domains.

Unraveling reproducible dynamic states of individual brain functional parcellation

This paper introduces a method to identify dynamic states of brain parcellations, finding that dynamic parcellations are more reproducible than static ones and reveal distinct states in heteromodal cortices.

Transferability of Brain decoding using GraphConvolutional Networks

This study investigates the transferability of deep neural networks in brain decoding using fMRI data, finding that scanner site conditions significantly impact feature transfer compared to task domains.

Local vulnerability and global connectivity jointly shape neurodegenerative disease propagation

The paper uses an agent-based model to simulate neurodegenerative disease spread, showing how local vulnerability and network connectivity drive Parkinson's disease progression.

Neurobehavioural Correlates of Obesity are Largely Heritable

This study investigates the genetic overlap between obesity and neurobehavioural factors using brain imaging data from the Human Connectome Project, finding significant genetic correlations between obesity and brain morphology, cognitive function, and personality traits.

Anatomical And Functional Organization Of The Human Substantia Nigra And Its Connections

The paper uses diffusion and functional MRI data to identify a tripartite parcellation of the human substantia nigra based on connectivity and functional coding of value and salience, linking these to impulsivity traits.