Ahn Woo-Young, Busemeyer Jerome R
Department of Psychology, The Ohio State University, Columbus, OH 43210.
Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405.
Curr Opin Behav Sci. 2016 Oct 1;11:1-7. doi: 10.1016/j.cobeha.2016.02.001.
Computational modeling and associated methods have greatly advanced our understanding of cognition and neurobiology underlying complex behaviors and psychiatric conditions. Yet, no computational methods have been successfully translated into clinical settings. This review discusses three major methodological and practical challenges (A. precise characterization of latent neurocognitive processes, B. developing optimal assays, C. developing large-scale longitudinal studies and generating predictions from multi-modal data) and potential promises and tools that have been developed in various fields including mathematical psychology, computational neuroscience, computer science, and statistics. We conclude by highlighting a strong need to communicate and collaborate across multiple disciplines.
计算建模及相关方法极大地推动了我们对复杂行为和精神疾病背后的认知及神经生物学的理解。然而,尚无计算方法成功转化应用于临床环境。本综述讨论了三个主要的方法学和实践挑战(A. 潜在神经认知过程的精确表征,B. 开发最优检测方法,C. 开展大规模纵向研究并从多模态数据生成预测)以及在数学心理学、计算神经科学、计算机科学和统计学等各个领域已开发出的潜在前景和工具。我们强调跨多学科进行交流与合作的迫切需求作为总结。