Q
Qiyuan Tian
Researcher at Harvard University
Publications - 78
Citations - 1611
Qiyuan Tian is an academic researcher from Harvard University. The author has contributed to research in topics: Diffusion MRI & Medicine. The author has an hindex of 16, co-authored 60 publications receiving 885 citations. Previous affiliations of Qiyuan Tian include Stanford University & Fudan University.
Papers
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Journal ArticleDOI
Wiring and Molecular Features of Prefrontal Ensembles Representing Distinct Experiences
Li Ye,Li Ye,William E. Allen,Kimberly R. Thompson,Qiyuan Tian,Brian Hsueh,Charu Ramakrishnan,Ai-Chi Wang,Joshua H. Jennings,Avishek Adhikari,Casey H. Halpern,Ilana B. Witten,Alison L. Barth,Liqun Luo,Liqun Luo,Jennifer A. McNab,Karl Deisseroth +16 more
TL;DR: For example, the authors found that positive and negative-valence experiences in prefrontal cortex are represented by cell populations that differ in their causal impact on behavior, long-range wiring and gene expression profiles, with the major discriminant being expression of the adaptation-linked gene NPAS4.
Journal ArticleDOI
Resting-state “physiological networks”
Jingyuan E. Chen,Laura D. Lewis,Catie Chang,Qiyuan Tian,Nina E. Fultz,Ned A. Ohringer,Bruce R. Rosen,Jonathan R. Polimeni +7 more
TL;DR: It is shown that physiologically-coupled fluctuations alone can produce networks that strongly resemble previously reported resting-state networks, suggesting that, in some cases, the "physiological networks" seem to mimic the neuronal networks.
Journal ArticleDOI
Multimodal image registration and connectivity analysis for integration of connectomic data from microscopy to MRI.
Maged Goubran,Christoph Leuze,Brian Hsueh,Markus Aswendt,Li Ye,Qiyuan Tian,Michelle Y. Cheng,Ailey K. Crow,Gary K. Steinberg,Jennifer A. McNab,Karl Deisseroth,Michael Zeineh +11 more
TL;DR: An automated resource is developed that combines histologically cleared volumes with connectivity atlases and MRI, enabling the analysis of histological features across multiple fiber tracts and networks, and their correlation with in-vivo biomarkers, that can propel investigations of network alterations underlying neurological disorders.
Journal ArticleDOI
Double diffusion encoding MRI for the clinic.
TL;DR: Microscopic diffusion anisotropy measurements from DDE promise greater specificity to changes in tissue microstructure compared with conventional diffusion tensor imaging, but implementation of DDE sequences on whole‐body MRI scanners is challenging because of the limited gradient strengths and lengthy acquisition times.
Journal ArticleDOI
DeepDTI: High-fidelity six-direction diffusion tensor imaging using deep learning.
Qiyuan Tian,Berkin Bilgic,Berkin Bilgic,Qiuyun Fan,Congyu Liao,Chanon Ngamsombat,Chanon Ngamsombat,Yuxin Hu,Thomas Witzel,Kawin Setsompop,Kawin Setsompop,Jonathan R. Polimeni,Jonathan R. Polimeni,Susie Y. Huang,Susie Y. Huang +14 more
TL;DR: A new processing framework for DTI is presented that minimizes the data requirement of DTI to six diffusion-weighted images (DWIs) required by conventional voxel-wise fitting methods for deriving the six unique unknowns in a diffusion tensor using data-driven supervised deep learning.