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发展环境中神经认知机制测量的挑战与解决方案。

Challenges and Solutions to the Measurement of Neurocognitive Mechanisms in Developmental Settings.

机构信息

Division of Psychology and Language Sciences, University College London, London, United Kingdom.

Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, the Netherlands.

出版信息

Biol Psychiatry Cogn Neurosci Neuroimaging. 2023 Aug;8(8):815-821. doi: 10.1016/j.bpsc.2023.03.011. Epub 2023 Mar 30.

Abstract

Identifying early neurocognitive mechanisms that confer risk for mental health problems is one important avenue as we seek to develop successful early interventions. Currently, however, we have limited understanding of the neurocognitive mechanisms involved in shaping mental health trajectories from childhood through young adulthood, and this constrains our ability to develop effective clinical interventions. In particular, there is an urgent need to develop more sensitive, reliable, and scalable measures of individual differences for use in developmental settings. In this review, we outline methodological shortcomings that explain why widely used task-based measures of neurocognition currently tell us little about mental health risk. We discuss specific challenges that arise when studying neurocognitive mechanisms in developmental settings, and we share suggestions for overcoming them. We also propose a novel experimental approach-which we refer to as "cognitive microscopy"-that involves adaptive design optimization, temporally sensitive task administration, and multilevel modeling. This approach addresses some of the methodological shortcomings outlined above and provides measures of stability, variability, and developmental change in neurocognitive mechanisms within a multivariate framework.

摘要

确定导致心理健康问题风险的早期神经认知机制是我们寻求成功早期干预的一个重要途径。然而,目前我们对塑造从儿童期到青年期的心理健康轨迹的神经认知机制的了解有限,这限制了我们开发有效临床干预措施的能力。特别是,迫切需要开发更敏感、可靠和可扩展的个体差异衡量标准,用于发展环境。在这篇综述中,我们概述了方法学上的缺陷,这些缺陷解释了为什么目前广泛使用的基于任务的神经认知测量方法对心理健康风险知之甚少。我们讨论了在发展环境中研究神经认知机制时出现的具体挑战,并分享了克服这些挑战的建议。我们还提出了一种新的实验方法——我们称之为“认知显微镜”——它涉及自适应设计优化、时间敏感的任务管理和多层次建模。这种方法解决了上述方法学上的一些缺陷,并提供了在多元框架内神经认知机制的稳定性、可变性和发展变化的衡量标准。

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