Experience sampling reveals the role that covert goal states play in task-relevant behavior.

Anonymized Multidimensional Experience Sampling data and Gradient coordinates used in the analysis reported in Mckeown et al. (2023), "Experience sampling reveals the role that covert goal states play in task-relevant behavior". Summary: Cognitive neuroscience has gained insight into covert states using experience sampling. Traditionally, this approach has focused on off-task states. However, task-relevant states are also maintained via covert processes. Our study examined whether experience sampling can also provide insights into covert goal-relevant states that support task performance. To address this question, we developed a neural state space, using dimensions of brain function variation, that allows neural correlates of overt and covert states to be examined in a common analytic space. We use this to describe brain activity during task performance, its relation to covert states identified via experience sampling, and links between individual variation in overt and covert states and task performance. Our study established deliberate task focus was linked to faster target detection, and brain states underlying this experience—and target detection—were associated with activity patterns emphasizing the fronto-parietal network. In contrast, brain states underlying off-task experiences—and vigilance periods—were linked to activity patterns emphasizing the default mode network. Our study shows experience sampling can not only describe covert states that are unrelated to the task at hand, but can also be used to highlight the role fronto-parietal regions play in the maintenance of covert task-relevant states. 'n57_scanner_mdes_PCA_spearman_gradients_demographics_rt_movement_mendeley_anon.csv' contains all anonymized experience-sampling data, PCA scores, state space coordinates, demographics, and movement data for the 57 participants reported in the main analyses. 'n57_scanner_mdes_PCA_yeoNetworks_demographics_rt_movement_mendeley_anon.csv' contains all anonymized experience-sampling data, PCA scores, Yeo-7 network averages, demographics, and movement data for the same 57 participants. 'n46_lab_and_scanner_PCA_mendeley_anon.csv' contains all anonymized lab and scanner PCA scores for the 46 participants that participated in both behavioral and scanner sessions (supplementary analysis). Note: 3 scanner participants in this dataset were excluded from fMRI analyses (anon IDs: 58, 59, 60). Version 2 data includes coordinates for dimensions 1-5, calculated via Spearman rank correlation, as well as the network averages for each of the Yeo-7 networks.本数据集包含Mckeown等人2023年发表的论文《经验抽样揭示内隐目标状态在任务相关行为中的作用》（"Experience sampling reveals the role that covert goal states play in task-relevant behavior"）分析中所使用的经匿名化处理的多维经验抽样（Experience Sampling）数据与梯度坐标。 研究概述：认知神经科学领域借助经验抽样法已对内隐状态（covert states）取得了诸多研究进展。传统上该方法主要聚焦于任务脱离状态，但任务相关状态同样可通过内隐加工得以维持。本研究旨在探讨经验抽样法是否也能为支撑任务表现的目标相关内隐状态提供研究视角。为解答该问题，本研究基于脑功能变异维度构建了神经状态空间，可在统一分析框架下探究外显状态（overt states）与内隐状态的神经关联物。借助该空间，我们得以刻画任务执行过程中的脑活动模式，分析其与经验抽样法识别出的内隐状态之间的关联，以及外显与内隐状态的个体差异与任务表现之间的联系。本研究发现，刻意的任务专注度与更快的目标检测速度相关，而支撑该专注体验及目标检测的脑状态，与突显额顶网络（fronto-parietal network）的活动模式存在关联。与之相反，支撑任务脱离体验及警觉期的脑状态，则与突显默认模式网络（default mode network）的活动模式相关。本研究证实，经验抽样法不仅可用于刻画与当前任务无关的内隐状态，还能用以揭示额顶区域在维持任务相关内隐状态中所发挥的作用。 文件`n57_scanner_mdes_PCA_spearman_gradients_demographics_rt_movement_mendeley_anon.csv`包含主分析中纳入的57名被试的全部匿名化经验抽样数据、主成分分析（PCA）得分、状态空间坐标、人口统计学信息及运动数据。 文件`n57_scanner_mdes_PCA_yeoNetworks_demographics_rt_movement_mendeley_anon.csv`包含上述57名被试的全部匿名化经验抽样数据、PCA得分、Yeo-7脑网络平均激活值、人口统计学信息及运动数据。 文件`n46_lab_and_scanner_PCA_mendeley_anon.csv`包含同时参与行为实验与磁共振扫描实验的46名被试的匿名化实验室及扫描环境下的PCA得分，该部分数据用于补充分析。 注记：本数据集包含的3名扫描被试（匿名ID：58、59、60）被排除在功能磁共振成像（fMRI）分析之外。 版本2数据包含通过斯皮尔曼秩相关（Spearman rank correlation）计算得到的1-5维坐标，以及Yeo-7各脑网络的平均激活值。