标题： 人类判断中离散、循环和可扩展的模式是情感图片评分的基础 显示英文标题

标题： Discrete, recurrent, and scalable patterns in human judgement underlie affective picture ratings

摘要： 操作按键任务，其中每个行动都有后果，已被类比为“想要”这一概念，并在人类中产生了量化接近和回避行为偏好的合法关系。 尚不清楚没有操作框架的评分任务，这可以类比为“喜欢”，是否表现出类似的合法关系。 我们研究了三个独立的参与者队列（N = 501，506 和 4,019 名参与者），由两个不同的组织收集，使用相同的 7 点李克特量表对国际情感图片集中的图片进行从负面到正面的偏好评分。 没有操作框架的图片评分产生了与文献中报告的操作按键任务相似的价值函数、极限函数和权衡函数，所有拟合度均高于 0.75。 这些价值、极限和权衡函数在数学公式上是离散的，在所有三个独立队列中反复出现，并展示了个体和群体曲线之间的缩放关系。 在所有三个实验中，损失厌恶的计算显示 95% 的置信区间低于 2 的值，这与之前在按键任务或校准不确定性的赌博游戏中报告的损失相对于收益的强烈加权相矛盾。 三个队列的图形特征相似，并表明偏好评估满足四个合法性标准中的三个，提供了一种简单、简短且低成本的方法，用于无强制选择决策、赌博游戏或操作按键的偏好定量评估。 这种方法可以轻松地在任何有屏幕的数字设备（例如手机）上实现。 显示英文摘要

摘要： Operant keypress tasks, where each action has a consequence, have been analogized to the construct of "wanting" and produce lawful relationships in humans that quantify preferences for approach and avoidance behavior. It is unknown if rating tasks without an operant framework, which can be analogized to "liking", show similar lawful relationships. We studied three independent cohorts of participants (N = 501, 506, and 4,019 participants) collected by two distinct organizations, using the same 7-point Likert scale to rate negative to positive preferences for pictures from the International Affective Picture Set. Picture ratings without an operant framework produced similar value functions, limit functions, and trade-off functions to those reported in the literature for operant keypress tasks, all with goodness of fits above 0.75. These value, limit, and trade-off functions were discrete in their mathematical formulation, recurrent across all three independent cohorts, and demonstrated scaling between individual and group curves. In all three experiments, the computation of loss aversion showed 95% confidence intervals below the value of 2, arguing against a strong overweighting of losses relative to gains, as has previously been reported for keypress tasks or games of chance with calibrated uncertainty. Graphed features from the three cohorts were similar and argue that preference assessments meet three of four criteria for lawfulness, providing a simple, short, and low-cost method for the quantitative assessment of preference without forced choice decisions, games of chance, or operant keypressing. This approach can easily be implemented on any digital device with a screen (e.g., cellphones).