Xiaodong Chen 


Dr. Chen obtained his B.S. degree in the Department of Biology at Inner Mongolia University, 1997-2002. During 2002-2008, Dr. Chen did vision researches for his PhD in the lab of Dr. Muming-Poo (Fellow of the American Academy of Sciences) and Dr. Yang Dan (University of California at Berkeley) at the Institute of Neuroscience, Chinese Academy of Sciences, Shanghai. Then, Dr. Chen continued to work as an assistant investigator in the lab in 2008-2009. After that, Dr. Chen did motion perception researches as a postdoc with Dr. Dora E. Angelaki (Fellow of the American Academy of Sciences) and Dr. Gregory C. DeAngelis at Washington University in St. Louis, School of Medicine, U.S.A in 2009-2012, and at the Baylor College of Medicine in Houston, U.S.A in 2012-2014. Dr. Chen joined the Institute of Neurology and Cognitive Sciences, Qiushi Academy for Advanced Studies, Zhejiang University, in February 2014 as a Professor and Head of the Laboratory of Perception and Cognition. His main interests are the neural mechanisms underlying spatial perception, object recognition.

The application of modern brain science in the real world is beginning to become increasingly prominent, for example, artificial intelligence, brain computer interface, automatic driving, and so on. Our lab is devoted to two basic problems among them:

1. How do human beings achieve self-movement perception and motion control? It was found by researches that there are “place cells”, “grid cells” and “head direction cells” in the hippocampus and entorhinal cortex. It is an equivalent “built-in” GPS (Global Positioning System) installed in the brain by combining functions of these cells, which provides our real-time position information in the environment. Moreover, neurons in the posterior parietal cortex (sensorimotor associative cortex) and motor cortex percept real-time motion state of the body (position, direction, speed, acceleration, etc.) and make corresponding adjustment by integrating visual and vestibular input signals. However, how to decode motion control by analyzing the responses of signal or population neurons, and therefore to reveal the mechanism in the neuronal loop level, is still problems that need to be solved. 

2. How do humans recognize objects? Although compared with computer image recognition, the huge advantages in the accuracy and intelligence of human beings are still unmatched by the computers. However, we still do not know much about the neural mechanism of object recognition. It was found by researches that the visual information processing is hierarchical in the cortex. Primary visual cortical (V1, V2, V4) neurons respond only to the orientation, boundary and other simple image or graphic features. Temporal cortical neurons begin to respond specifically to face and other complex stimuli. But the underlying neural mechanism is still very unclear.

We will use multidisciplinary methods and techniques to study these problems from multiple perspectives and perspectives. To obtain whole brain functional features with behavior, fMRI and EEG experiments; to study the reaction characteristics of cortical neurons with multiple technologies of optical imaging, multichannel electrophysiological recording, local electrical stimulation, optical genetics, and inactivation of specific cortical areas; to establish the mathematical model to decode the specific function using the obtained data. Our lab will develop relevant software and hardware to assist the experiments, such as new microelectrode arrays, new data acquisition devices and software. We have now developed an experimental virtual reality platforms that can be used to study motion perception. We will develop novel facial stimuli for object recognition research. Through these studies, we hope to understand the neural mechanisms behind these functions, and the results can be used in areas such as artificial intelligence, brain computer interfaces, and the diagnosis and treatment of related neurological diseases. We welcome students and colleagues from various disciplines interested in brain science research to join us.


Lab members:


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