Functional covariance connectivity of gray and white matter in olfactory-related brain regions in Parkinson's Disease

Y Wang, H Wei, S Du, H Yan, X Li, Y Wu… - Frontiers in …, 2022 - frontiersin.org
Before the onset of motor symptoms, Parkinson's disease (PD) involves dysfunction of the
anterior olfactory nucleus and olfactory bulb, causing olfactory disturbance, commonly …

A novel fMRI group data analysis method based on data-driven reference extracting from group subjects

Y Shi, W Zeng, N Wang, D Chen - Computer methods and programs in …, 2015 - Elsevier
Group-independent component analysis (GICA) is a well-established blind source
separation technique that has been widely applied to study multi-subject functional magnetic …

Brain functional plasticity driven by career experience: a resting-state fMRI study of the seafarer

N Wang, W Zeng, Y Shi, H Yan - Frontiers in psychology, 2017 - frontiersin.org
The functional connectome derived from BOLD resting-state functional magnetic resonance
imaging data represents meaningful functional organizations and a shift between distinct …

Olfactory functional covariance connectivity in Parkinson's disease: evidence from a Chinese population

S Du, Y Wang, G Li, H Wei, H Yan, X Li… - Frontiers in Aging …, 2023 - frontiersin.org
Introduction Central anosmia is a potential marker of the prodrome and progression of
Parkinson's disease (PD). Resting-state functional magnetic resonance imaging studies …

Early warning for human mental sub-health based on fMRI data analysis: an example from a seafarers' resting-data study

Y Shi, W Zeng, N Wang, S Wang, Z Huang - Frontiers in psychology, 2015 - frontiersin.org
Effective mental sub-health early warning mechanism is of great significance in the
protection of individual mental health. The traditional mental health assessment method is …

Dynamical complexity fingerprints of occupation-dependent brain functional networks in professional seafarers

H Yan, H Wu, Y Chen, Y Yang, M Xu, W Zeng… - Frontiers in …, 2022 - frontiersin.org
The complexity derived from resting-state functional magnetic resonance imaging (rs-fMRI)
data has been applied for exploring cognitive states and occupational neuroplasticity …

A Unified Multi-Modality Fusion Framework for Deep Spatio-Temporal-Spectral Feature Learning in Resting-State fMRI Denoising

M Lim, KS Heo, JM Kim, B Kang, W Lin… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
Resting-state functional magnetic resonance imaging (rs-fMRI) is a commonly used
functional neuroimaging technique to investigate the functional brain networks. However, rs …

A novel spectrum contrast mapping method for functional magnetic resonance imaging data analysis

Q Yu, Z Cai, C Li, Y Xiong, Y Yang, S He… - Frontiers in human …, 2021 - frontiersin.org
Many studies reported that spontaneous fluctuation of the blood oxygen level-dependent
signal exists in multiple frequency components and changes over time. By assuming a …

MARGM: A multi-subjects adaptive region growing method for group fMRI data analysis

Y Shi, M Li, W Zeng - Biomedical Signal Processing and Control, 2021 - Elsevier
Region growing has been utilized in the analysis of functional magnetic resonance imaging
(fMRI) data for many years, while some influential factors, such as the definition of growing …

Occupation-modulated language networks and its lateralization: A resting-state fMRI study of seafarers

H Wu, D Peng, H Yan, Y Yang, M Xu… - Frontiers in Human …, 2023 - frontiersin.org
Introduction Studies have revealed that the language network of Broca's area and
Wernicke's area is modulated by factors such as disease, gender, aging, and handedness …