{"id":51514,"date":"2024-07-17T19:22:57","date_gmt":"2024-07-17T11:22:57","guid":{"rendered":"https:\/\/swarma.org\/?p=51514"},"modified":"2024-07-17T19:22:57","modified_gmt":"2024-07-17T11:22:57","slug":"%e4%bb%8e%e8%84%91%e9%a2%86%e5%9f%9f%e5%85%a5%e9%97%a8%e5%9b%a0%e6%9e%9c%e6%b6%8c%e7%8e%b0%ef%bc%9a%e4%bf%a1%e6%81%af%e5%88%86%e8%a7%a3%e5%a6%82%e4%bd%95%e5%90%af%e5%8f%91%e5%9b%a0%e6%9e%9c%e6%b6%8c","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=51514","title":{"rendered":"\u4ece\u8111\u9886\u57df\u5165\u95e8\u56e0\u679c\u6d8c\u73b0\uff1a\u4fe1\u606f\u5206\u89e3\u5982\u4f55\u542f\u53d1\u56e0\u679c\u6d8c\u73b0\u7406\u8bba\u5728\u8111\u7f51\u7edc\u7684\u5e94\u7528\uff1f\uff5c\u5468\u4e94\u76f4\u64ad\u00b7\u56e0\u679c\u6d8c\u73b0\u7b2c\u4e94\u5b63"},"content":{"rendered":"
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\u56e0\u679c\u6d8c\u73b0\u8bfb\u4e66\u4f1a\u5df2\u7ecf\u8fdb\u5c55\u5230\u7b2c5\u5b63\u672b\u5c3e\uff0c\u6765\u81ea\u4e0d\u540c\u9886\u57df\u80cc\u666f\u7684\u8001\u5e08\u540c\u5b66\u5df2\u7ecf\u6709\u8bb8\u591a\u6df1\u5165\u7684\u8ba8\u8bba\u548c\u4ea7\u51fa\u3002\u4e0d\u5c11\u5173\u952e\u6587\u732e\u4e5f\u5df2\u7ecf\u7ecf\u8fc7\u4e86\u53cd\u590d\u8ba8\u8bba\u3001\u9605\u8bfb\u548c\u63a8\u6572\uff0c\u5176\u4e2d\u6bd4\u8f83\u5177\u6709\u4ee3\u8868\u6027\u7684\u5206\u522b\u662f\uff1aErik Hoel \u53ca\u5176\u540c\u4e8b\u7ed3\u5408\u5e72\u9884\u4e3b\u4e49\u56e0\u679c\uff08interventionist causality\uff09\u548c\u6709\u6548\u4fe1\u606f\u63d0\u51fa\u56e0\u679c\u6d8c\u73b0\u6846\u67b6[1-2]\uff0c\u548c Fernando Rosas \u53ca\u5176\u540c\u4e8b\u7ed3\u5408\u8f6c\u79fb\u71b5\u548c\u4fe1\u606f\u5206\u89e3\u5bf9\u56e0\u679c\u6d8c\u73b0\u8fdb\u884c\u4e86\u518d\u5b9a\u4e49[3-4]\u3002<\/span><\/section>\n

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\u5176\u4e2d Luppi \u53ca\u5176\u540c\u4e8b\u4e3b\u8981\u662f\u5e0c\u671b\u501f\u52a9\u4fe1\u606f\u5206\u89e3\u5de5\u5177\u8fdb\u4e00\u6b65\u8ba4\u8bc6\u610f\u8bc6\u7684\u673a\u7406\uff0c\u76ee\u524d\u7814\u7a76\u8f83\u4e3a\u95ee\u9898\u5bfc\u5411[5-6], \uff1b\u800cVarley\u53ca\u5176\u540c\u4e8b\u7684\u7814\u7a76\u96c6\u4e2d\u4e8e\u4fe1\u606f\u5206\u89e3\u6846\u67b6\u672c\u8eab\u7684\u6269\u5c55\uff0c\u76ee\u524d\u7814\u7a76\u8f83\u4e3a\u5de5\u5177\u76d2\u5bfc\u5411[10,12]\u3002\u6240\u4ee5\uff0c\u524d\u8005\u8fd1\u671f\u53d1\u8868\u7684\u7efc\u8ff0\u53ef\u80fd\u4f1a\u5728\u5927\u7684\u5e94\u7528\u573a\u666f\u4e0a\u6709\u66f4\u6e05\u6670\u7684\u9610\u8ff0\uff0c\u800c\u540e\u8005\u4f1a\u5728\u5177\u4f53\u7684\u4fe1\u606f\u8bba\u6307\u6807\u4e0a\u6709\u6240\u53d1\u5c55\u3002<\/span><\/section>\n

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3. \u5927\u8111\u4e2d\u7684\u4fe1\u606f\u7ed3\u6784\uff08Luppi et al.)<\/span><\/p>\n

4. \u7f51\u7edc\u6c9f\u901a\u7406\u8bba\u5bf9\u56e0\u679c\u6d8c\u73b0\u7406\u8bba\u7684\u53ef\u80fd\u8865\u5145<\/span><\/p>\n

5. \u5206\u89e3\u8111\u7f51\u7edc\uff0c\u610f\u8bc6\u4f5c\u4e3a\u4e00\u4e2a\u95ee\u9898\uff08Luppi et al.)<\/span><\/p>\n

6. \u4fe1\u606f\u5206\u89e3\u4e0e\u66f4\u7b80\u8981\u7684\u4fe1\u606f\u8bba\u6307\u6807\uff08Varley et al.)<\/span><\/p>\n

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\u8111\u7f51\u7edc Brain Network<\/span><\/p>\n

\u4fe1\u606f\u5206\u89e3 Information Decomposition <\/span><\/p>\n

\u56e0\u679c\u6d8c\u73b0 Causal emergence<\/span><\/p>\n

\u534f\u540c\u6838 Synergistic core<\/span><\/p>\n

\u5c40\u90e8\u4fe1\u606f\u5206\u89e3 Partial information decomposition, PID<\/span><\/p>\n

\u5c40\u90e8\u71b5\u5206\u89e3 Partial entropy decomposition, PED<\/span><\/p>\n

\u7f51\u7edc\u6c9f\u901a\u6a21\u578b Network communication models<\/span><\/section>\n

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\u65f6\u95f4\uff1a2024\u5e747\u670819\u65e5\uff08\u672c\u5468\u4e94\uff09\u665a20:00-22:00<\/span><\/p>\n

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\u62a5\u540d\u53c2\u4e0e\u8bfb\u4e66\u4f1a\uff1a<\/span><\/strong><\/section>\n
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\u6591\u56fe\u94fe\u63a5\uff1ahttps:\/\/pattern.swarma.org\/study_group_issue\/693<\/span><\/p>\n


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1. Hoel EP, Albantakis L, Tononi G. Quantifying causal emergence shows that macro can beat micro. Proc Natl Acad Sci U S A. 2013 Dec 3;110(49):19790-5. doi: 10.1073\/pnas.1314922110. Epub 2013 Nov 18. PMID: 24248356; PMCID: PMC3856819.<\/span><\/section>\n
2. Tononi, G., Sporns, O. Measuring information integration. BMC Neurosci 4, 31 (2003). https:\/\/doi.org\/10.1186\/1471-2202-4-31<\/span><\/section>\n
3.  Rosas, Fernando E., et al. “Reconciling emergence: An information-theoretic approach to identify causal emergence in multivariate data.” PLoS computational biology 16.12 (2020): e1008289.<\/span><\/section>\n
4. Mediano PAM, Rosas FE, Luppi AI, Jensen HJ, Seth AK, Barrett AB, Carhart-Harris RL, Bor D. 2022 Greater than the parts: a review of the information decomposition approach to causal emergence. Phil. Trans. R. Soc. A 380: 20210246.<\/span> https:\/\/doi.org\/10.1098\/rsta.2021.024<\/span><\/section>\n
5.  Luppi, A. I., Rosas, F. E., Mediano, P. A. M., Menon, D. K., & Stamatakis, E. A. (2024). Information decomposition and the informational architecture of the brain. Trends in Cognitive Sciences, 28(4), 352\u2013368.<\/span> https:\/\/doi.org\/10.1016\/j.tics.2023.11.005<\/span><\/section>\n
6. Luppi, A. I., Rosas, F. E., Mediano, P. A. M., Demertzi, A., Menon, D. K., & Stamatakis, E. A. (2024). Unravelling consciousness and brain function through the lens of time, space, and information. Trends in Neurosciences, 47(7), 551-568.<\/span> https:\/\/doi.org\/10.1016\/j.tins.2024.05.007<\/span><\/section>\n
7. Betzel, R. F., & Bassett, D. S. (2017). Multi-scale brain networks. NeuroImage, 160, 73\u201383.<\/span> https:\/\/doi.org\/10.1016\/j.neuroimage.2016.11.006<\/span><\/section>\n
8. P.A.M. Mediano, et al. Towards an extended taxonomy of information dynamics via integrated information decomposition. arXiv (2021).<\/span> http:\/\/doi.org\/10.48550\/arxiv.2109.13186<\/span><\/section>\n
9. Luppi, A. I., Mediano, P. A. M., Rosas, F. E., Allanson, J., Pickard, J. D., Carhart-Harris, R., Williams, G. B., Craig, M. M., Finoia, P., Owen, A. M., Naci, L., Menon, D. K., Bor, D., & Stamatakis, E. A. (2024). A synergistic workspace for human consciousness revealed by integrated information decomposition. *eLife, 88173.<\/span> https:\/\/doi.org\/10.7554\/eLife.88173<\/span><\/section>\n
10. Varley, T. F. (2024). Generalized decomposition of multivariate information. PLOS ONE, 19(2), e0297128.<\/span> https:\/\/doi.org\/10.1371\/journal.pone.0297128<\/span><\/section>\n
11. Yuan, B., Zhang, J., Lyu, A., Wu, J., Wang, Z., Yang, M., Liu, K., Mou, M., & Cui, P. (2024). Emergence and Causality in Complex Systems: A Survey of Causal Emergence and Related Quantitative Studies. Entropy, 26(1), 108.<\/span> https:\/\/doi.org\/10.3390\/e26020108<\/span><\/section>\n
12. Varley, T. F., Pope, M., Puxeddu, M. G., Faskowitz, J., & Sporns, O. (2023). Partial entropy decomposition reveals higher-order information structures in human brain activity. Proceedings of the National Academy of Sciences, 120(30), e2300888120.<\/span> https:\/\/doi.org\/10.1073\/pnas.2300888120<\/span><\/section>\n
13. A.M. Proca, et al. Synergistic information supports modality integration and flexible learning in neural networks solving multiple tasks. arXiv (2022) Published online October 6, 2022.<\/span> https:\/\/doi.org\/10.48550\/arXiv.2210.02996<\/span><\/section>\n
14. Amico, E., Abbas, K., Duong-Tran, D. A., Tipnis, U., Rajapandian, M., Chumin, E., Ventresca, M., Harezlak, J., & Go\u00f1i, J. (2021). Toward an information theoretical description of communication in brain networks. Network Neuroscience, 5(3), 646\u2013665.<\/span> https:\/\/doi.org\/10.1162\/netn_a_00185<\/span><\/section>\n
15. Huang, Z., Mashour, G. A., & Hudetz, A. G. (2023). Functional geometry of the cortex encodes dimensions of consciousness. Nature Communications, 14, 72.<\/span> https:\/\/doi.org\/10.1038\/s41467-022-35764-7<\/span><\/section>\n
16. Luppi, A. I., Vohryzek, J., Kringelbach, M. L., Mediano, P. A. M., Craig, M. M., Adapa, R., … & Stamatakis, E. A. (2023). Distributed harmonic patterns of structure-function dependence orchestrate human consciousness. Communications Biology, 6, 117.<\/span> https:\/\/doi.org\/10.1038\/s42003-023-04474-1<\/span><\/section>\n
17. Seth, A. K., Barrett, A. B., & Barnett, L. (2011). Causal density and integrated information as measures of conscious level. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 369(1942), 3748\u20133767.<\/span> https:\/\/doi.org\/10.1098\/rsta.2011.0079<\/span><\/section>\n
18. Zhang, Jiang & Liu, Kaiwei. (2022). Neural Information Squeezer for Causal Emergence. Entropy. 2023. 10.3390\/e25010026.<\/span><\/section>\n
19. Yang, Mingzhe, et al. “Finding emergence in data: causal emergence inspired dynamics learning.” arXiv preprint arXiv:2308.09952 (2023).<\/span><\/section>\n

20. Paul L. Williams,Randall D. Beer: Nonnegative Decomposition of Multivariate Information ,arXiv:1004.2515,2010<\/span><\/p>\n


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