Pei, J.#, Deng, L.#, Song, S.#, Zhao, M.#, Zhang, Y.#, Wu, S.#, Wang, G.#,…&Shi, L. *(2019).Towards artificial general intelligence with hybrid Tianjic chip architecture. Nature, 572, 106–111. https://doi.org/10.1038/s41586-019-1424-8

PDF

Download

Liao, F., Liang, M., Li, Z., Hu, X.*, & Song, S.* (2019). Evaluate the Malignancy of Pulmonary Nodules Using the 3-D Deep Leaky Noisy-or Network. IEEE transactions on neural networks and learning systems. https://doi.org/10.1109/tnnls.2019.2892409

PDF

Download

Chen, C., Cheng, M., Ito, T.*, & Song, S.* (2018). Neuronal organization in the inferior colliculus revisited with cell-type-dependent monosynaptic tracing. Journal of Neuroscience, 38(13), 3318-3332. https://doi.org/10.1523/JNEUROSCI.2173-17.2018

PDF

Download

Liu, X., Mou, L., Cui, H., Lu, Z.*, & Song, S.* (2018). Jumper: Learning when to make classification decisions in reading. arXiv preprint arXiv:1807.02314. IJCAI 2018 https://doi.org/10.24963/ijcai.2018/589

PDF

Download

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, 49(2), 495-504. https://doi.org/10.1109/TCYB.2017.2778799

PDF

Download

Zhu, C.#, Yao, Y.#, Xiong, Y., Cheng, M., Chen, J., Zhao, R., ... & Song, S.* (2017). Somatostatin neurons in the basal forebrain promote high-calorie food intake. Cell reports, 20(1), 112-123. https://doi.org/10.1016/j.celrep.2017.06.007

PDF

Download

Zhao, Z., Wang, L., Gao, W., Hu, F., Zhang, J., Ren, Y., Lin, R. Feng, Q., Cheng, M., Ju, D., Chi, Q., Wang, D., Song, S., Luo, M., Zhan, C.* (2017). A central catecholaminergic circuit controls blood glucose levels during stress. Neuron, 95(1), 138-152. https://doi.org/10.1016/j.neuron.2017.05.031

PDF

Download

Li, X., Steffens, D. C., Potter, G. G., Guo, H., Song, S., & Wang, L.* (2017). Decreased between‐hemisphere connectivity strength and network efficiency in geriatric depression. Human brain mapping, 38(1), 53-67. https://doi.org/10.1002/hbm.23343

PDF

Download

Wang, Q., Zhang, J., Song, S.*, & Zhang, Z.* (2014). Attentional neural network: Feature selection using cognitive feedback. In Advances in Neural Information Processing Systems (pp. 2033-2041).

PDF

Download

Sümbül, U. #, Song, S. #, McCulloch, K., Becker, M., Lin, B., Sanes, J. R., ... & Seung, H. S.* (2014). A genetic and computational approach to structurally classify neuronal types. Nature communications, 5, 3512. https://doi.org/10.1038/ncomms4512

PDF

Download

Grillo, F. W., Song, S.*, Ruivo, L. M. T. G., Huang, L., Gao, G., Knott, G. W., ... & De Paola, V.* (2013). Increased axonal bouton dynamics in the aging mouse cortex. Proceedings of the National Academy of Sciences, 110(16), E1514-E1523. https://doi.org/10.1073/pnas.1218731110

PDF

Download

Song, S.#, Liu, L.#, Edwards, S. V., & Wu, S.* (2012). Resolving conflict in eutherian mammal phylogeny using phylogenomics and the multispecies coalescent model. Proceedings of the National Academy of Sciences, 109(37), 14942-14947. https://doi.org/10.1073/pnas.1211733109

PDF

Download

Song, S., Sjöström, P. J., Reigl, M., Nelson, S., & Chklovskii, D. B.* (2005). Highly nonrandom features of synaptic connectivity in local cortical circuits. PLoS biology, 3(3), e68. https://doi.org/10.1371/journal.pbio.0030068

PDF

Download

Song, S., Miller, K. D., & Abbott, L. F.* (2000). Competitive Hebbian learning through spike-timing-dependent synaptic plasticity. Nature neuroscience, 3(9), 919. https://doi.org/10.1038/78829

PDF

Download