• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

计算模型对精神病学有帮助吗?

Are computational models of any use to psychiatry?

机构信息

Wellcome Trust Centre for Neuroimaging, Gatsby Computational Neuroscience Unit and Medical School, UCL, United Kingdom.

出版信息

Neural Netw. 2011 Aug;24(6):544-51. doi: 10.1016/j.neunet.2011.03.001. Epub 2011 Mar 10.

DOI:10.1016/j.neunet.2011.03.001
PMID:21459554
Abstract

Mathematically rigorous descriptions of key hypotheses and theories are becoming more common in neuroscience and are beginning to be applied to psychiatry. In this article two fictional characters, Dr. Strong and Mr. Micawber, debate the use of such computational models (CMs) in psychiatry. We present four fundamental challenges to the use of CMs in psychiatry: (a) the applicability of mathematical approaches to core concepts in psychiatry such as subjective experiences, conflict and suffering; (b) whether psychiatry is mature enough to allow informative modelling; (c) whether theoretical techniques are powerful enough to approach psychiatric problems; and (d) the issue of communicating clinical concepts to theoreticians and vice versa. We argue that CMs have yet to influence psychiatric practice, but that they help psychiatric research in two fundamental ways: (a) to build better theories integrating psychiatry with neuroscience; and (b) to enforce explicit, global and efficient testing of hypotheses through more powerful analytical methods. CMs allow the complexity of a hypothesis to be rigorously weighed against the complexity of the data. The paper concludes with a discussion of the path ahead. It points to stumbling blocks, like the poor communication between theoretical and medical communities. But it also identifies areas in which the contributions of CMs will likely be pivotal, like an understanding of social influences in psychiatry, and of the co-morbidity structure of psychiatric diseases.

摘要

在神经科学领域,对关键假设和理论进行数学严谨描述的情况越来越普遍,并且开始应用于精神病学。在本文中,两位虚构的角色——斯特朗博士和密考伯先生——就精神病学中使用此类计算模型(CM)展开了辩论。我们提出了在精神病学中使用 CM 面临的四个基本挑战:(a)数学方法对精神病学中主观体验、冲突和痛苦等核心概念的适用性;(b)精神病学是否足够成熟,以允许进行有意义的建模;(c)理论技术是否足够强大,能够解决精神科问题;(d)将临床概念传达给理论家以及反之的问题。我们认为,CM 尚未影响精神病学实践,但它们以两种基本方式帮助精神病学研究:(a)构建更好的理论,将精神病学与神经科学相结合;(b)通过更强大的分析方法,对假设进行明确、全面和有效的测试。CM 允许严格权衡假设的复杂性与数据的复杂性。本文最后讨论了前进的道路。它指出了绊脚石,例如理论和医学社区之间沟通不畅。但它也确定了 CM 的贡献可能至关重要的领域,例如理解精神病学中的社会影响,以及精神疾病的共病结构。

相似文献

1
Are computational models of any use to psychiatry?计算模型对精神病学有帮助吗?
Neural Netw. 2011 Aug;24(6):544-51. doi: 10.1016/j.neunet.2011.03.001. Epub 2011 Mar 10.
2
Mental illness from the perspective of theoretical neuroscience.从理论神经科学角度看精神疾病。
Perspect Biol Med. 2008 Summer;51(3):335-52. doi: 10.1353/pbm.0.0030.
3
Systems biology and psychiatry - modeling molecular and cellular networks of mental disorders.系统生物学与精神病学——构建精神障碍的分子和细胞网络模型
Pharmacopsychiatry. 2008 Sep;41 Suppl 1:S2-S18. doi: 10.1055/s-2008-1081461.
4
SysBioMed report: advancing systems biology for medical applications.系统生物医学报告:推动系统生物学在医学应用中的发展。
IET Syst Biol. 2009 May;3(3):131-6. doi: 10.1049/iet-syb.2009.0005.
5
Emerging paradigms in medicine: implications for the future of psychiatry.医学中的新兴范式:对精神病学未来的影响。
Explore (NY). 2007 Sep-Oct;3(5):467-77. doi: 10.1016/j.explore.2007.06.003.
6
[Roles of brain science in psychiatry].[脑科学在精神病学中的作用]
Seishin Shinkeigaku Zasshi. 2002;104(11):1005-16.
7
Missing links in phenomenological clinical neuroscience: why we still are not there yet.现象学临床神经科学中的缺失环节:为何我们仍未达成目标。
Curr Opin Psychiatry. 2007 Nov;20(6):559-69. doi: 10.1097/YCO.0b013e3282f128b8.
8
[Significance of cross-cultural experience for young psychiatrists--learning from "The Joint Workshop for Psychiatric Residents of Korea and Japan"].跨文化经历对年轻精神科医生的意义——从“韩日精神科住院医师联合研讨会”中学习
Seishin Shinkeigaku Zasshi. 2006;108(11):1194-200.
9
Can the neuroeconomics revolution revolutionize psychiatry?神经经济学革命能否彻底改变精神病学?
Neurosci Biobehav Rev. 2012 Jan;36(1):64-78. doi: 10.1016/j.neubiorev.2011.04.011. Epub 2011 Apr 29.
10
From plasticity to complexity: a new diagnostic method for psychiatry.从可塑性到复杂性:一种新的精神病学诊断方法。
Med Hypotheses. 2004;63(1):110-4. doi: 10.1016/j.mehy.2004.02.010.

引用本文的文献

1
Forward Planning in a Population-Based Alcohol Use Disorder Sample.基于人群的酒精使用障碍样本中的前瞻性规划
Addict Biol. 2025 Aug;30(8):e70072. doi: 10.1111/adb.70072.
2
Does the reliability of computational models truly improve with hierarchical modeling? Some recommendations and considerations for the assessment of model parameter reliability : Reliability of computational model parameters.计算模型的可靠性真的会通过分层建模得到提高吗?关于评估模型参数可靠性的一些建议和考量:计算模型参数的可靠性。
Psychon Bull Rev. 2024 Dec;31(6):2465-2486. doi: 10.3758/s13423-024-02490-8. Epub 2024 May 8.
3
Active reinforcement learning versus action bias and hysteresis: control with a mixture of experts and nonexperts.
主动强化学习与动作偏差和滞后的比较:混合专家与非专家的控制。
PLoS Comput Biol. 2024 Mar 29;20(3):e1011950. doi: 10.1371/journal.pcbi.1011950. eCollection 2024 Mar.
4
Current status, challenges and future prospects in computational psychiatry: a narrative review.计算精神病学的现状、挑战与未来前景:一篇叙述性综述。
Consort Psychiatr. 2023 Sep 29;4(3):33-42. doi: 10.17816/CP11244.
5
A neural mechanism for conserved value computations integrating information and rewards.一种整合信息和奖励的保守价值计算的神经机制。
Nat Neurosci. 2024 Jan;27(1):159-175. doi: 10.1038/s41593-023-01511-4. Epub 2024 Jan 4.
6
Impaired social learning in patients with major depressive disorder revealed by a reinforcement learning model.强化学习模型揭示重度抑郁症患者社会学习受损
Int J Clin Health Psychol. 2023 Oct-Dec;23(4):100389. doi: 10.1016/j.ijchp.2023.100389. Epub 2023 May 11.
7
Test-retest reliability of reinforcement learning parameters.再测试学习参数的可靠性。
Behav Res Methods. 2024 Aug;56(5):4582-4599. doi: 10.3758/s13428-023-02203-4. Epub 2023 Sep 8.
8
Invasive Computational Psychiatry.侵入式计算精神病学。
Biol Psychiatry. 2023 Apr 15;93(8):661-670. doi: 10.1016/j.biopsych.2022.09.032. Epub 2022 Oct 8.
9
The effect of body image dissatisfaction on goal-directed decision making in a population marked by negative appearance beliefs and disordered eating.身体意象不满对具有负面外貌信念和饮食失调人群的目标导向决策的影响。
PLoS One. 2022 Nov 28;17(11):e0276750. doi: 10.1371/journal.pone.0276750. eCollection 2022.
10
Switching to online: Testing the validity of supervised remote testing for online reinforcement learning experiments.切换到线上:测试在线强化学习实验中监督远程测试的有效性。
Behav Res Methods. 2023 Oct;55(7):3645-3657. doi: 10.3758/s13428-022-01982-6. Epub 2022 Oct 11.