Peng Yuan-INSTITUTE FOR TRANSLATIONAL BRAIN RESEARCH

Peng Yuan

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Peng Yuan Junior Principal Investigator

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Laboratory for neural code in normal cognition and disease

Peng (Paul) Yuan, a group leader and dean assistant in the Institute for translational brain research (ITBR). Paul graduated from Wuhan University for his baccalaureate in Biology in 2010; and in 2015, he completed his Ph.D. training in neurobiology at Yale University. Paul then worked as a postdoctoral associate at Stanford University. Paul joined ITBR at Fudan University in 2021. The primary focus of his group is aiming at understanding the representation of cognitive processes by populational neural activities, and how these representations become abnormal under brain disorders. His previous work has published on Science, Nature, Nature Methods, Nature Communications, Neuron, and other academic journals.

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Neural activities are the basis of information representation and computation in the brain. While conventional tools in neuroscience can be effective in dissecting the brain circuits and neuronal subtypes involved in specific cognitive process, they provide limited insights in understanding the populational activities within a circuit. Therefore, a more refined set of tools in observing and manipulating neural activities can allow the investigation of principles of representation and computation of information in the brain. In my group, we combine the state-of-the-art in vivo microscopy, two-photon mediated single-cell gene editing/optogenetic technologies, and AI-based data-constraint neural network reconstruction, in order to study the causal relationship of neural activity patterns and information coding during cognitive processes, and to establish and evaluate neural computation models at cellular level, thus advancing our understanding of brain functions.

Understanding the neural coding of cognitive variables and its abnormal state in brain disorders can provide invaluable insights in developing treatments against these conditions. In many brain disorders, the cognitive dysfunctions are not caused by neuronal death, but abnormalities in their firing patterns. Unfortunately, the link between the brain pathology and abnormal neural code is often poorly understood. Thus, rectifying neural code abnormalities remain to be an untapped opportunity for developing novel treatments, particularly for conditions that have been challenging due to the lack of obvious brain damage, such as autistic spectrum disorder, obsessive compulsive disorder and post-traumatic stress disorder. Recent advances in brain machine interface hardware begin to realize the communication between brain and computers that was only possible in science fiction. Deciphering the basic principles of neuron coding would be invaluable for establishing the theoretical infrastructure that allows bi-directional interaction.

Current projects in my group:

1. Neuron activity sequences supporting the encoding and expression of long-term and short-term memory;

2. Pathogenesis of neurodegenerative diseases (Alzheimer’s disease, Parkinson’s disease, frontotemporal lobar dementia, and more) and mechanism-inspired novel treatment strategies;

3. Further development of neuro-AI algorithm for causal, data-constraint network modeling.