/Computational_Psychiatry_online_Journal_Club

计算精神病学在线文献报告讨论会(Computational psychiatry online journal club(CPoJC))

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计算精神病学在线文献报告讨论会(Computational psychiatry online journal club(CPoJC))

报告讨论会目的：

  1. 加强领域内同行的讨论和交流。
  2. 促进基础研究领域和临床领域的合作。

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CPoJC 2.0日程安排

期号 文献 报告人 日期 主持人
29 Hearne, L. J., Mill, R. D., Keane, B. P., Repovš, G., Anticevic, A., & Cole, M. W. (n.d.). Activity flow underlying abnormalities in brain activations and cognition in schizophrenia. Science Advances, 7(29), eabf2513. https://doi.org/10.1126/sciadv.abf2513 谢珂 2022年3月17日
30 Sharp, P. B., Russek, E. M., Huys, Q. J., Dolan, R. J., & Eldar, E. (2022). Humans perseverate on punishment avoidance goals in multigoal reinforcement learning. ELife, 11, e74402. https://doi.org/10.7554/eLife.74402 陆春雷，徐深 2022年3月24日 谢涵博
31 Pike, A. C., & Robinson, O. J. (2022). Reinforcement Learning in Patients With Mood and Anxiety Disorders vs Control Individuals: A Systematic Review and Meta-analysis. JAMA Psychiatry. https://doi.org/10.1001/jamapsychiatry.2022.0051 黄丽芹 2022年3月31日
32 Gillan, C. M., & Rutledge, R. B. (2021). Smartphones and the Neuroscience of Mental Health. Annual Review of Neuroscience, 44(1), 129–151. https://doi.org/10.1146/annurev-neuro-101220-014053 温秀娟 2022年4月21日

CPoJC 往期报告

期号 文献 报告人 日期 相关材料 主持人
1 Pavlovian conditioning–induced hallucinations result from overweighting of perceptual priors. Science, 357(6351), 596–600. https://doi.org/10.1126/science.aan3458 耿海洋 2020年12月24日
2 An integrative framework for perceptual disturbances in psychosis. Nature Reviews Neuroscience, 20(12), 763–778. https://doi.org/10.1038/s41583-019-0234-1 李瑛 2020年12月31日
3 Anxious individuals have difficulty learning the causal statistics of aversive environments. Nature Neuroscience, 18(4), 590–596. https://doi.org/10.1038/nn.3961 全湘 张洳源 2021年1月28日
4 Identifying and validating subtypes within major psychiatric disorders based on frontal–posterior functional imbalance via deep learning. Molecular Psychiatry. https://doi.org/10.1038/s41380-020-00892-3 黎超 2021年2月4日
5 Identification of neurobehavioural symptom groups based on shared brain mechanisms. Nature Human Behaviour, 3(12), 1306–1318. https://doi.org/10.1038/s41562-019-0738-8 刘威 2021年2月25日
6 Gagne, C., Zika, O., Dayan, P., & Bishop, S. J. (2020). Impaired adaptation of learning to contingency volatility in internalizing psychopathology. ELife, 9, e61387. https://doi.org/10.7554/eLife.61387 王志豪 2021年3月11日
7 Computational psychiatry Intro 张磊 2021年3月25日 视频, PPT
8 Hein, T. P., de Fockert, J., & Ruiz, M. H. (2021). State anxiety biases estimates of uncertainty and impairs reward learning in volatile environments. NeuroImage, 224, 117424. https://doi.org/10.1016/j.neuroimage.2020.117424 窦皓然 2021年4月8日 视频, PPT
9 Shin, Y. S., & Niv, Y. (2021). Biased evaluations emerge from inferring hidden causes. Nature Human Behaviour, 1–10. https://doi.org/10.1038/s41562-021-01065-0 潘晚坷 2021年4月29日 视频,PPT
10 Lei, H., Mochizuki, Y., Chen, C., Hagiwara, K., Hirotsu, M., Matsubara, T., & Nakagawa, S. (2021). Sex difference in the weighting of expected uncertainty under chronic stress. Scientific Reports, 11(1), 8700. https://doi.org/10.1038/s41598-021-88155-1 雷慧洁 2021年5月13日 PPT
11 van Baar, J. M., Chang, L. J., & Sanfey, A. G. (2019). The computational and neural substrates of moral strategies in social decision-making. Nature Communications, 10(1), 1483. https://doi.org/10.1038/s41467-019-09161-6 金悦宁 2021年5月27 日 视频, PPT
12 van de Schoot, R., Depaoli, S., King, R., Kramer, B., Märtens, K., Tadesse, M. G., Vannucci, M., Gelman, A., Veen, D., Willemsen, J., & Yau, C. (2021). Bayesian statistics and modelling. Nature Reviews Methods Primers, 1(1), 1–26. https://doi.org/10.1038/s43586-020-00001-2 谭敬斌 2021年6月24日
CPoJC 2.0
13 Dwyer, D. B., Falkai, P., & Koutsouleris, N. (2018). Machine Learning Approaches for Clinical Psychology and Psychiatry. Annual Review of Clinical Psychology, 14(1), 91–118. https://doi.org/10.1146/annurev-clinpsy-032816-045037 吕婷婷 2021年10月21日 视频 耿海洋
14 Suthaharan, P., Reed, E. J., Leptourgos, P., Kenney, J. G., Uddenberg, S., Mathys, C. D., Litman, L., Robinson, J., Moss, A. J., Taylor, J. R., Groman, S. M., & Corlett, P. R. (2021). Paranoia and belief updating during the COVID-19 crisis. Nature Human Behaviour, 5(9), 1190–1202. https://doi.org/10.1038/s41562-021-01176-8 黄丽芹 2021年10月28日 视频 祝小喜
15 Lake, B. M., Ullman, T. D., Tenenbaum, J. B., & Gershman, S. J. (2017). Building machines that learn and think like people. Behavioral and Brain Sciences, 40. https://doi.org/10.1017/S0140525X16001837 谢涵博，方泽鸣 2021年11月4日 视频 祝小喜
16 Brown, V. M., Zhu, L., Solway, A., Wang, J. M., McCurry, K. L., King-Casas, B., & Chiu, P. H. (2021). Reinforcement Learning Disruptions in Individuals With Depression and Sensitivity to Symptom Change Following Cognitive Behavioral Therapy. JAMA Psychiatry, 78(10), 1113–1122. https://doi.org/10.1001/jamapsychiatry.2021.1844 雷慧洁 2021年11月11日 视频 吕婷婷
17 Wilson, R. C., & Collins, A. G. (2019). Ten simple rules for the computational modeling of behavioral data. ELife, 8, e49547. https://doi.org/10.7554/eLife.49547 王鑫, 刘花卷 2021年11月18日 视频, script 谢涵博
18 Kang Huang, Yaning Han, Ke Chen, Hongli Pan, Gaoyang Zhao, Wenling Yi, Xiaoxi Li, Siyuan Liu, Pengfei Wei & Liping Wang（2021）.A hierarchical 3D-motion learning framework for animal spontaneous behavior mapping. Nature Communications 蔡盛源 2021年11月25日 视频 吕婷婷
Ten Tips for Scientific Journal Club 耿海洋 2021年11月25日 视频 吕婷婷
19 Peterson, Joshua C., David D. Bourgin, Mayank Agrawal, Daniel Reichman, and Thomas L. Griffiths. 2021. “Using Large-Scale Experiments and Machine Learning to Discover Theories of Human Decision-Making Deborah 2021年12月2日 [视频]（xx） 谢涵博
20 Kotov, R., Krueger, R. F., Watson, D., Cicero, D. C., Conway, C. C., DeYoung, C. G., Eaton, N. R., Forbes, M. K., Hallquist, M. N., Latzman, R. D., Mullins-Sweatt, S. N., Ruggero, C. J., Simms, L. J., Waldman, I. D., Waszczuk, M. A., & Wright, A. G. C. (2021). The Hierarchical Taxonomy of Psychopathology (HiTOP): A Quantitative Nosology Based on Consensus of Evidence. Annual Review of Clinical Psychology, 17(1), 83–108. https://doi.org/10.1146/annurev-clinpsy-081219-093304 温秀娟 2021年12月9日 视频 祝小喜
21 Gershman, S. J., & Lai, L. (2021). The Reward-Complexity Trade-off in Schizophrenia. Computational Psychiatry, 5(1), 38–53. https://doi.org/10.5334/cpsy.71 谭敬斌 2021年12月16日 视频 谢涵博
22 Weiss, Aurélien, Valérian Chambon, Junseok K. Lee, Jan Drugowitsch, and Valentin Wyart. 2021. “Interacting with Volatile Environments Stabilizes Hidden-State Inference and Its Brain Signatures.” Nature Communications 12(1):2228. doi: 10.1038/s41467-021-22396-6. 陈明明，李冰洁 2021年12月23日 谢涵博
23 Stephan, Klaas E., Dominik R. Bach, Paul C. Fletcher, Jonathan Flint, Michael J. Frank, Karl J. Friston, Andreas Heinz, Quentin J. M. Huys, Michael J. Owen, Elisabeth B. Binder, Peter Dayan, Eve C. Johnstone, Andreas Meyer-Lindenberg, P. Read Montague, Ulrich Schnyder, Xiao-Jing Wang, and Michael Breakspear. 2016. “Charting the Landscape of Priority Problems in Psychiatry, Part 1: Classification and Diagnosis.” The Lancet Psychiatry 3(1):77–83. doi: 10.1016/S2215-0366(15)00361-2. 吴雪冰 2021年12月30日 吕婷婷
24 Mini-Workshop of Cognitive Modeling(MWoCM) MCMC sampling for dummies, Not a tutorial of a Bayesian implementation of a reinforcement learning model,Fitting a simple Reinforcement Learning model to behavioral data with PyMC3,Ref1,Ask me anything about cognitive modelling! 李宇航，徐深，马若璠，郭鸣谦，聂其阳，张磊 2022年1月6日 耿海洋
25 Stephan, K. E., F. Schlagenhauf, Q. J. M. Huys, S. Raman, E. A. Aponte, K. H. Brodersen, L. Rigoux, R. J. Moran, J. Daunizeau, R. J. Dolan, K. J. Friston, and A. Heinz. 2017. “Computational Neuroimaging Strategies for Single Patient Predictions.” NeuroImage 145:180–99. doi: 10.1016/j.neuroimage.2016.06.038. 吕婷婷 2022年1月13日 吕婷婷
26 Hunter, Lindsay E., Elana A. Meer, Claire M. Gillan, Ming Hsu, and Nathaniel D. Daw. 2022. “Increased and Biased Deliberation in Social Anxiety.” Nature Human Behaviour 6(1):146–54. doi: 10.1038/s41562-021-01180-y. 陆春雷 2022年2月10日 谢涵博
27 De Miguel, Zurine, Nathalie Khoury, Michael J. Betley, Benoit Lehallier, Drew Willoughby, Niclas Olsson, Andrew C. Yang, Oliver Hahn, Nannan Lu, Ryan T. Vest, Liana N. Bonanno, Lakshmi Yerra, Lichao Zhang, Nay Lui Saw, J. Kaci Fairchild, Davis Lee, Hui Zhang, Patrick L. McAlpine, Kévin Contrepois, Mehrdad Shamloo, Joshua E. Elias, Thomas A. Rando, and Tony Wyss-Coray. 2021. “Exercise Plasma Boosts Memory and Dampens Brain Inflammation via Clusterin.” Nature 1–6. doi: 10.1038/s41586-021-04183-x. 宋刚 2022年2月24日 吕婷婷
28 Kanter, Benjamin R., Christine M. Lykken, Edvard I. Moser, and May-Britt Moser. 2022. “Neuroscience in the 21st Century: Circuits, Computation, and Behaviour.” The Lancet Neurology 21(1):19–21. doi: 10.1016/S1474-4422(21)00427-0. 陆春雷 2022年3月3日 谢涵博

推荐阅读

序号 文献 等级（5为最高）
1 Baribault, Beth, and Anne Collins. 2021. “Troubleshooting Bayesian Cognitive Models: A Tutorial with Matstanlib.
2 Grossman, Cooper D., Bilal A. Bari, and Jeremiah Y. Cohen. 2021. “Serotonin Neurons Modulate Learning Rate through Uncertainty.” Current Biology. doi: 10.1016/j.cub.2021.12.006.
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国际认知计算神经科学前沿研讨会

名字 简介 时间
MAPs: Methods And Primers for Computational Psychiatry and Neuroeconomics 由耶鲁大学医学院Al Powers等人组织，计算精神病学方法入门，领域中的大牛深入浅出讲解CP的方法和理论 Monthly Thursdays 4:00 – 5:00 pm ET
Transcontinental Computational Psychiatry Workgroup (TCPW) 由Quentin Huys组织，计算精神病学领域大牛，每月一次的seminar Monthly
Computational Cognitive Science Colloquium 2020/2021 Technische Universität Darmstadt组织，认知计算神经科学seminar Weekly Wednesday 3:20-5:00 pm GMT+1
World Wide Neuro 认知计算神经科学全球seminar信息集散地 Daily
Brain Imaging Research Center Seminars UNIVERSITY OF CONNECTICUT举办，认知神经科学 Monthly Tuesday 12-1：30 pm ET
The Learning Salon A weekly forum in which we explore bridges and contentions in biological and artificial learning. 由 Ida Momennejad等人组织，注重对领域基本问题的深刻讨论。 Weekly Friday, 4:00 pm EST
BRAIN INSPIRED 由Paul Middlebrooks主持，一个讨论AI和brain science交叉的prodcast，主持人与业界大牛的对谈，主持人的问题很专业。