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OpenWMB:适用于 OpenSesame 的开源、自动化工作记忆任务库。

OpenWMB: An open-source and automated working memory task battery for OpenSesame.

机构信息

CINEICC - Center for Research in Neuropsychology and Cognitive Behavioral Intervention, Faculty of Psychology and Educational Sciences, University of Coimbra, Coimbra, Portugal.

ChronoCog - Laboratory for Chronopsychology and Cognitive Systems, Faculty of Psychology and Educational Sciences, University of Coimbra, Coimbra, Portugal.

出版信息

Behav Res Methods. 2024 Oct;56(7):6880-6903. doi: 10.3758/s13428-024-02397-1. Epub 2024 Apr 4.

Abstract

Working memory capacity (WMC) has been measured with a plethora of cognitive tasks. Several preeminent automated batteries of working memory (WM) tasks have been developed recently. However, despite all their advantages, most batteries were programmed in paid platforms and/or only included a single WM paradigm. To address these issues, we developed the OpenWMB, an automated battery comprising seven tasks from three distinct paradigms (complex spans, updating tasks, and binding tasks) that tap into several functional aspects of WM (simultaneous storage and processing, updating, and binding). The battery runs on open-source software (OpenSesame) and is freely available online in a ready-to-download format. The OpenWMB possesses flexible features and includes a data processing script (that converts data into a format ready for statistical analysis). The instrument is available in Portuguese and English. However, we only assessed the psychometric properties of the former version. The Portuguese version presented good internal consistency and considerable internal and predictive validity: all tasks loaded into a single factor. Additionally, the WMC estimate was strongly correlated with a fluid intelligence factor. This study also tried to contribute to the ongoing debate regarding the best method to assess WMC. We computed a permutation analysis to compare the amount of variance shared between a fluid intelligence factor and (1) each WM task, (2) homogenous WMC factors (based on multiple tasks from the same paradigm), and (3) heterogeneous WMC factors (derived from triplets of tasks from different paradigms). Our results suggested that heterogeneous factors provided the best estimates of WMC.

摘要

工作记忆容量(WMC)已经通过大量认知任务进行了测量。最近已经开发出了几个杰出的自动工作记忆(WM)任务电池。然而,尽管它们有很多优点,但大多数电池都是在付费平台上编程的,或者只包含单个 WM 范式。为了解决这些问题,我们开发了 OpenWMB,这是一个由七个来自三个不同范式(复杂跨度、更新任务和绑定任务)的任务组成的自动电池,涉及 WM 的几个功能方面(同时存储和处理、更新和绑定)。该电池在开源软件(OpenSesame)上运行,并且以可下载的格式免费在线提供。OpenWMB 具有灵活的功能,并包括一个数据处理脚本(将数据转换为准备进行统计分析的格式)。该仪器有葡萄牙语和英语两种版本。然而,我们只评估了前一个版本的心理测量特性。葡萄牙语版本表现出良好的内部一致性和相当大的内部和预测有效性:所有任务都加载到一个单一的因素中。此外,WMC 估计值与流体智力因素高度相关。本研究还试图为评估 WMC 的最佳方法的持续争论做出贡献。我们进行了置换分析,以比较流体智力因素与(1)每个 WM 任务、(2)同质 WMC 因素(基于来自同一范式的多个任务)和(3)异质 WMC 因素(源自不同范式的三个任务对)之间共享的方差量。我们的结果表明,异质因素提供了 WMC 的最佳估计。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d1c/11362385/f343a1783669/13428_2024_2397_Fig1_HTML.jpg

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