Zonglei Zhen
Beijing Normal University
80 Papers
117 Citations
Zonglei Zhen is an academic researcher from Beijing Normal University. The author has contributed to research in topics: Computer science & Functional magnetic resonance imaging. The author has an hindex of 19, co-authored 62 publications. Previous affiliations of Zonglei Zhen include Chinese Academy of Sciences & McGovern Institute for Brain Research.
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Papers
The face module emerges from domain-general visual experience: a deprivation study on deep convolutional neural network
TL;DR: This study provides undisputable evidence on the role of nature versus nurture in developing the domain-specific modules that domain- Specificity may evolve from non-specific stimuli and processes without genetic predisposition, which is further fine-tuned by domain- specific experience.
Mapping Informative Clusters in a Hierarchial Framework of fMRI Multivariate Analysis
TL;DR: The hierarchical framework of multivariate approach is suitable for both pattern classification and brain mapping in fMRI studies and showed better performance in the robustness of functional brain mapping than traditional voxel-based multivariate methods.
A Multi-Atlas Labeling Approach for Identifying Subject-Specific Functional Regions of Interest.
Lijie Huang,Guangfu Zhou,Zhaoguo Liu,Xiaobin Dang,Zetian Yang,Xiangzhen Kong,Xu Wang,Yiying Song,Zonglei Zhen,Jia Liu +9 more
TL;DR: This study improved the multi-atlas labeling approach for defining subject-specific fROIs by using a classifier-based atlas-encoding scheme and an atlas selection procedure to account for the large spatial variability across subjects.
From sMRI to task-fMRI: A unified geometric deep learning framework for cross-modal brain anatomo-functional mapping
TL;DR: Zhang et al. as mentioned in this paper proposed a unified geometric deep learning framework (BrainUGDL) to perform the cross-modal brain anatomo-functional mapping task, which learns the high-level global and local context information, respectively.
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DNNBrain: a unifying toolbox for mapping deep neural networks and brains
TL;DR: DNNBrain is presented, a Python-based toolbox designed for exploring internal representations in both DNNs and the brain and expects that this toolbox will accelerate scientific research in applying DNN’s to model biological neural systems and utilizing paradigms of cognitive neuroscience to unveil the black box of Dnns.