参考教材

1. 《神经信息学基础》，尧德中、夏阳主编，电子科技大学出版社，2015

其它经典参考书

1. 《神经生物学原理》，L.Q. Luo著，李沉简等译，高等教育出版社，2018
2. 《脑与意识—破解人类思维之迷》，S. Dehaene著，章熠译，浙江教育出版社，2018
3. 《认知、大脑与意识—认知神经科学导论》，B.J. Baars、N.M. Gage主编，王兆新等译，上海人民出版社，2015
4. 《神经信息学与计算神经科学》，唐孝威等主编，浙江科学技术出版社，2012
5. 《Neuroscience: Exploring the Brain》，M.F. Bear等编, 王建军主译，高等教育出版社，2004
6. 《神经信息处理》，顾凡及、梁培基著，北京工业大学出版社，2007
7. 《神经科学基础》，茹立强编著，清华大学出版社，2004
8. 《神经生物学》（第2版），寿天德编著，高等教育出版社，2006
9. 《脑功能探测的电学理论与方法》，尧德中编著，科学出版社，2003
10. 《神经信息学—神经系统的理论和模型》，汪云九等著，高等教育出版社，2006
11. 《视觉信息处理的脑机制》（第2版），寿天德著，中国科学技术大学出版社，2010
12. 《Priniciple of Neural Science》, E.Kandel 等编著, McGraw-Hill出版社，2000
13. 《神经生物学—从神经元到脑》，J.G. 尼克尔斯编，杨雄里译，科学出版社 2003
14. 《神经科学基础》，李继硕编著，高等教育出版社，2002
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相关的顶级期刊

1. Nature Reviews Neuroscience
2. Annual Review of Physiology
3. Annual Review of Neuroscience
4. Nature Neuroscience
5. Neuron
6. PNAS
7. Human Brain Mapping
8. NeuroImage
9. ......

相关的代表性参考文献

1. Eliasmith, C., Stewart, T. C., Choo, X., et al. (2012). A large-scale model of the functioning brain. Science, 338(6111), 1202-1205.
2. Hassabis, D., Kumaran, D., Summerfield, C., et al. (2017). Neuroscience-inspired artificial intelligence. Neuron, 95(2), 245-258.
3. Wolfe, J. M. (2020). Visual search: How do we find what we are looking for? Annual Review of Vision Science, 6, 539-562.
4. Wolfe, J. M. (2021). Guided Search 6.0: An updated model of visual search. Psychonomic Bulletin & Review, 28(4), 1060-1092.
5. Kaiser, D., Quek, G. L., Cichy, et al. (2019). Object vision in a structured world. Trends in Cognitive Sciences, 23(8), 672-685.
6. Mejias, J. F., Wang, X. J. (2022). Mechanisms of distributed working memory in a large-scale network of macaque neocortex. eLife, 11, e72136.
7. Li, S., Wang, X. J. (2022). Hierarchical timescales in the neocortex: Mathematical mechanism and biological insights. PNAS, 119(6), e2110274119.
8. Orsolic, I., Rio, M., Mrsic-Flogel, T. D., et al. (2021). Mesoscale cortical dynamics reflect the interaction of sensory evidence and temporal expectation during perceptual decision-making. Neuron, 109(11), 1861-1875.
9. Spitmaan, M., Seo, H., Lee, D., et al. (2020). Multiple timescales of neural dynamics and integration of task-relevant signals across cortex. PNAS, 117(36), 22522-22531.
10. Gilbert, C. D., Li, W. (2013). Top-down influences on visual processing. Nature Reviews Neuroscience. 14(5), 350-63.
11. Pasupathy, A., Kim, T., Popovkina, D. V. (2019). Object shape and surface properties are jointly encoded in mid-level ventral visual cortex. Current Opinion in Neurobiology, 58, 199-208.
12. Yang, G. R., Joglekar, M. R., Song, H. F., et al. (2019). Task representations in neural networks trained to perform many cognitive tasks. Nature Neuroscience, 22(2), 297-306.
13. Luczak, A., Mc Naughton, B. L., Kubo, Y. (2022). Neurons learn by predicting future activity. Nature Machine Intelligence, 4, 62–72.
14. Lillicrap, T. P., Santoro, A., Marris, L., Akerman, C. J. & Hinton, G. (2020). Backpropagation and the brain. Nat. Rev. Neurosci., 21, 335–346
15. Bertolero, M. A., Thomas, Y., Bassett, D. S., et al. (2018). A mechanistic model of connector hubs, modularity, and cognition. Nature Human Behaviour, 2, 765-777.
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