Sen Song, PhD
Associate Professor, Tsinghua University
Office: Medical Sciences Building, Room B208
PhD, Biology, Brandeis University (2002)
BA, University of Mississippi (1996)
My lab is interested in two questions: 1) Why can humans do intelligent things that computers cannot do? 2) What is a good life? I am glad that I found out that I can tackle these fundamental questions with the tools provided by modern neuroscience. We are working on brain-inspired artificial intelligence and solving the neural circuit basis for emotions and decision making. We are also interested in medical problems, like depression and anxiety disorders, which challenge us and makes life difficult for many people. On this front, we are developing brain-inspired AI for medical diagnosis. Students in the lab won the Kaggle 2017 Datasciencebowl competition for CT-based lung cancer diagnosis. We are also interested in neuro-feedback based methods and music therapy for mood disorders and improving quality of life in general.
- Computational Neuroscience, Neuroinformatics, Artificial Intelligence, Comparative Genomics and Bioinformatics
- Solving Circuitry for Emotions and Developing Drugs to Treat Emotional Disorders
- Connectomics and Functional Connectomics, Elucidating the Function of Neuronal Circuits and How they compute
- Optical Imaging and Optogenetics
- Solving Gene Circuits and Synthesizing Artificial Gene Circuits
Liao F, Chen X, Hu X*, Song S* (2017). Estimation of the volume of the left ventricle from MRI images using deep neural networks. IEEE Transactions on Cybernetics, 1–10 (co-corresponding)
Zhu C, Yao Y, Xiong Y, Cheng M, Chen J, Zhao R, Liao F, Shi R, Song S* (2017) Somatostatin Neurons in the Basal Forebrain Promote High-Calorie Food Intake , Cell Reports, 20(1): 112~123
Li X, Steffens David C, Potter GG, Guo H, Song S, Wang L* (2017). Decreased between-hemisphere connectivity strength and network efficiency in geriatric depression. Human Brain Mapping 38: 53-67
Wang Q, Zhang J, Song S*, Zhang Z*. (2014) Attentional Neural Network: Feature Selection Using Cognitive Feedback. Advances in Neural Information Processing Systems, 2033-2041 (co-corresponding author)
Song S, Miller K, Abbott LF* (2000) Competitive Hebbian learning through spike-timing-dependent synaptic plasticity. Nature Neuroscience, 3:919-926.