对精神疾病的计算理解方面的进展
Advances in the computational understanding of mental
illness
Quentin J. M. Huys1,2,
Michael Browning3,4, Martin P. Paulus5 and Michael J. Frank 6,7
1Division of Psychiatry and Max Planck UCL Centre for
Computational Psychiatry and Ageing Research,
University College London,
London, UK;
2Camden and Islington NHS Trust, London, UK;
3Computational Psychiatry Lab, Department of Psychiatry, University of Oxford, Oxford, UK;
4Oxford Health NHS Trust, Oxford, UK;
5Laureate Institute For Brain Research (LIBR), Tulsa, OK,
USA;
6Cognitive, Linguistic & Psychological Sciences,
Neuroscience Graduate Program,
Brown University, Providence, RI, USA and
7Carney Center for Computational Brain Science, Carney
Institute for Brain Science Psychiatry and Human Behavior,
Brown University,
Providence, RI, USA
Correspondence:
Quentin J. M. Huys (q.huys@ucl.ac.uk)
Accepted:
15 June 2020 by NEUROPSYCHOPHARMACOLOGY
摘要:这个特刊证明了计算精神病学引起的波动。这种波动反映了计算精神病学解决三项重要挑战的潜力。首先,精神疾病涉及从亚细胞到社会的多个抽象层次上现象之间的复杂相互作用。计算技术非常适合表征这种相互作用(2-4)。第二,精神病学处理非常复杂的现象。计算方法增强了对这种现象的理解,测量和预测,包括(对于治疗发展至关重要)对操纵变量影响的预测(3)。第三,数据积累的步伐不断提高,需要新颖,功能更强大的计算工具。前两个方面属于基于理论的计算精神病学的范畴,并在本期中得到了很好的说明。第三方面属于数据驱动方法的范围,而不是理论驱动的方法,因此尽管它也很重要,但本期未解决。
翻译稿件:对精神疾病的计算理解方面的进展
翻译原文:Advances in the computational understanding of mental
illness