Yirong Xiong

Intern at Max Planck Institute for Brain Research

prof_pic.jpg

credit:
Lunevani and Kalle

I’m currently doing an intership at Prof. Gilles Laurent’s lab in Frankfurt and I’m about to start my graduate study in XDBio program at Johns Hopkins University and Janelia Research Campus.

During my Master’s study at University of Tübingen, I majored in Neural Information Processing at Graduate Training Center of Neuroscience. I worked in Human and Machine Cognition Lab and studied how attention modulates learning and memory. Meanwhile I studied dynamical systems in spatial decision making with Dr. Vivek Sridhar in Konstanz. I did my master’s thesis in Burgalossi lab, and my lab rotation in Dr. Anna Levina’s lab. Before my study in Tübingen, I studied at Beijing Normal University and worked on corpus callosum topography using diffusion MRI (CCmapping).

My current research interests are learning and memory, especially in the context of spatial navigation. When I am not in lab, I enjoy writing popular science blogs. Besides, I love running, reading, cooking, and playing puzzles in my free time.

Fun fact about me: in the pilot scan of my own experiment, I found my left cerebellum is almost missing. Ever since that, this has been the best excuse of my poor dancing skill. I’ve made a Valentine’s day poster of my brain scan.

selected publications

  1. HBM
    Cortical mapping of callosal connections in healthy young adults
    Yirong Xiong, Liyuan Yang, Changtong Wang, Chenxi Zhao, Junhao Luo, Di Wu, Yiping Ouyang, Michel Thiebaut Schotten, and Gaolang Gong
    Human Brain Mapping, 2024
    Publisher: Wiley
  2. JNeuroscience
    Callosal fiber length scales with brain size according to functional lateralization, evolution, and development
    Liyuan Yang, Chenxi Zhao, Yirong Xiong, Suyu Zhong, Di Wu, Shaoling Peng, Michel Thiebaut Schotten, and Gaolang Gong
    Journal of Neuroscience, 2022
    Publisher: Soc Neuroscience
  3. CCN2023
    Selective Memory for Reward-Relevant Features Is Modulated by Expertise during Reward Learning
    Yirong Xiong, Nir Moneta, Mihaly Banyai, and Charley Wu
    2023