Yi He



+45 5271 4597



Personal webpage


Research Interests

I am interested in brain connectome which typically employs three complementary methods (task fMRI, resting state fMRI and diffusion MR). Previously I focused on task fMRI and rsfMRI at the scale of vessels. My current interest focuses on translation of synchrotron data of brain tissue to diffusion MR. In the long term, we will combine diffusion MRI with fMRI and translate them to clinical application.

Research Groups

Preclinical Research Group
Microstructure and Plasticity

Curriculum Vitae



MSc in Biomedical Engineering, Southeast University, Nanjing, China


BSc in Biomedical Engineering, Central South University, Changsha, China


2018 - Present

Postdoc at DRCMR

2014 - 2017

PhD student at Department High-field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen. Germany

2013 - 2013

Research Associate at Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China

2011 - 2013

Research Assistant at Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China

Full CV


He Y, Wang M, Chen X, Pohmann R, Polimeni J, Scheffler K, Rosen B, Kleinfeld D and Yu X, Ultra-slow single-vessel BOLD and CBV-based fMRI spatiotemporal dynamics and correlations with neuronal intracellular calcium signals. Neuron, 2018, in press.

He Y, Wang M, Yu X. Directly mapping the single-vessel hemodynamic signal with Multi-echo Line-scanning fMRI (MELS-fMRI), Journal of Cerebral Blood Flow and Metabolism, under revision.

Yu X, He Y, Wang M, Merkle H, Dodd S, Afonso S and Koretsky AP. Sensory and optogenet-ically driven single-vessel fMRI. Nature Methods, 2016, 13: 337-340. doi:10.1038/nmeth.3765.

Wang M, He Y, Sejnowski T, Yu X. Positive and negative BOLD signals are regulated by Ca2+-mediated gliovascular interactions. Proceedings of the National Academy of Sciences, 2018, in press.

Miao F, Cheng Y, He Y, He Q and Li Y. A Wearable Context-Aware ECG Monitoring System Integrated with Built-in Kinematic Sensors of the Smartphone. Sensors. 2015, 15(5): 11465-11484.

Miao F, He Y, Liu J, Li Y and Ayoola I. Identifying typical physical activity on smartphone with varying positions and orientations. Biomedical Engineering. 2015, 14(1:32): 1-15.

He Y and Li Y. Physical Activity Recognition Utilizing the Built-In Kinematic Sensors of a Smartphone.  International Journal of Distributed Sensor Networks. 2013, Article ID 481580: 1-10.

He Y, Li Y and Yin C. Falling-Incident Detection and Alarm by Smartphone with Multimedia Messaging Service. E-Health Telecommunication Systems and Networks. 2012, 1: 1-5.