Fundamental functional differences between gyri and sulci: implications for brain function, cognition, and behavior

X Jiang, T Zhang, S Zhang, KM Kendrick… - …, 2021 - academic.oup.com
Folding of the cerebral cortex is a prominent characteristic of mammalian brains. Alterations
or deficits in cortical folding are strongly correlated with abnormal brain function, cognition …

[HTML][HTML] Hybrid high-order functional connectivity networks using resting-state functional MRI for mild cognitive impairment diagnosis

Y Zhang, H Zhang, X Chen, SW Lee, D Shen - Scientific reports, 2017 - nature.com
Conventional functional connectivity (FC), referred to as low-order FC, estimates temporal
correlation of the resting-state functional magnetic resonance imaging (rs-fMRI) time series …

Large-scale functional network overlap is a general property of brain functional organization: Reconciling inconsistent fMRI findings from general-linear-model-based …

J Xu, MN Potenza, VD Calhoun, R Zhang… - Neuroscience & …, 2016 - Elsevier
Functional magnetic resonance imaging (fMRI) studies regularly use univariate general-
linear-model-based analyses (GLM). Their findings are often inconsistent across different …

A generic framework for embedding human brain function with temporally correlated autoencoder

L Zhao, Z Wu, H Dai, Z Liu, X Hu, T Zhang, D Zhu… - Medical Image …, 2023 - Elsevier
Learning an effective and compact representation of human brain function from high-
dimensional fMRI data is crucial for studying the brain's functional organization. Traditional …

Characterizing functional brain networks via spatio-temporal attention 4D convolutional neural networks (STA-4DCNNs)

X Jiang, J Yan, Y Zhao, M Jiang, Y Chen, J Zhou… - Neural Networks, 2023 - Elsevier
Characterizing individualized spatio-temporal patterns of functional brain networks (FBNs)
via functional magnetic resonance imaging (fMRI) provides a foundation for understanding …

Cross-architecture performance prediction (XAPP) using CPU code to predict GPU performance

N Ardalani, C Lestourgeon, K Sankaralingam… - Proceedings of the 48th …, 2015 - dl.acm.org
GPUs have become prevalent and more general purpose, but GPU programming remains
challenging and time consuming for the majority of programmers. In addition, it is not always …

Modeling spatio-temporal patterns of holistic functional brain networks via multi-head guided attention graph neural networks (Multi-Head GAGNNs)

J Yan, Y Chen, Z Xiao, S Zhang, M Jiang, T Wang… - Medical Image …, 2022 - Elsevier
Mounting evidence has demonstrated that complex brain function processes are realized by
the interaction of holistic functional brain networks which are spatially distributed across …

Differentiable neural architecture search for optimal spatial/temporal brain function network decomposition

Q Li, X Wu, T Liu - Medical image analysis, 2021 - Elsevier
It has been a key topic to decompose the brain's spatial/temporal function networks from 4D
functional magnetic resonance imaging (fMRI) data. With the advantages of robust and …

A deep learning method for autism spectrum disorder identification based on interactions of hierarchical brain networks

N Qiang, J Gao, Q Dong, J Li, S Zhang, H Liang… - Behavioural Brain …, 2023 - Elsevier
Background It has been recently shown that deep learning models exhibited remarkable
performance of representing functional Magnetic Resonance Imaging (fMRI) data for the …

Functional brain network identification and fMRI augmentation using a VAE-GAN framework

N Qiang, J Gao, Q Dong, H Yue, H Liang, L Liu… - Computers in Biology …, 2023 - Elsevier
Recently, deep learning models have achieved superior performance for mapping functional
brain networks from functional magnetic resonance imaging (fMRI) data compared with …