Computational Modeling in Pediatric Mental Health.
Computational Modeling in Pediatric Mental Health.
复制标题
儿科心理健康的计算模型。
DOI:
10.1016/j.jaac.2018.12.009
复制
发表时间:
2019
影响因子:
13.3
通讯作者:
Jones,Matt
中科院分区:
文献类型:
--
作者:
Stoddard,Joel;Jones,Matt
Computational modeling has recently become of great interest to mental health clinicians as a tool for discovering the nature of pathophysiology and for clinical assessment, prediction, and treatment. Computational psychiatry is a term used to describe the application of computational modeling to behavioral and mental health problems. The NIMH has taken an interest in computational modeling, suggesting applications of interest, such as understanding the neural basis of mental illness, discovering new treatments, and predicting treatment response. 1 In this brief overview, our goal is to touch on major themes that have emerged in computational psychiatry.To back up a bit, what exactly is a computational model? Most broadly, it is a set of mathematical expressions that represent a natural process or predict a natural state. The work required to evaluate these equations is usually so intensive that it requires a computer. A model may be a complex series of expressions or a single, simple equation. Perhaps the most famous within psychology is a simple subtraction between what actually occurs (outcome) and what a person expects (prediction). This difference influences how much a person learns from some experiences. It is called prediction error (often represented with the symbol δ) and is represented by the equation δ= Outcome–Prediction. Many computational models of learning build upon this basic equation to describe how prediction error influences behavior. Later in this review, we discuss how these have influenced new methods for conducting exposure therapy.