Ni Long, Ma Wei Ji
Center for Neural Science, New York, USA.
Department of Psychology, New York University, New York, USA.
Sci Rep. 2024 Dec 4;14(1):30211. doi: 10.1038/s41598-024-80537-5.
The N-back task is one of the most popular paradigms for studying the cognitive mechanisms of working memory (WM). The task requires the observer to view a sequence of stimuli and judge whether the current stimulus (probe) matches the one presented N stimuli ago (target). A key phenomenon is that the intervening stimuli (distractors) interfere with task performance. Unfortunately, the classic N-back task uses complex categorical stimuli, making it unfit to quantify the effect of feature similarity on interference strength. Here, we introduce the "analog N-back task", which utilizes stimuli varying continuously in orientation or color. This task variant enables us to measure interference strength on a continuum, providing data suitable for identifying the sources of interference using computational models. In the analog 2-back task, we found that interference increased with feature similarity between the probe and both task-relevant (1-back) and task-irrelevant (3-back) distractors. We next developed and evaluated three main models that each incorporated a Bayesian decision step and differed from an optimal non-interference model in one component only: an early-pooling model, a late-pooling model, and a substitution model. Model comparison suggests that interference emerges late in processing, most likely due to confusion between stimuli during WM retrieval. Our work puts the study of interference in the N-back task on a firmer computational footing and provides a unified framework for examining the sources of interference across domains.
N -back 任务是研究工作记忆（WM）认知机制最常用的范式之一。该任务要求观察者查看一系列刺激，并判断当前刺激（探测刺激）是否与 N 个刺激之前呈现的那个刺激（目标刺激）匹配。一个关键现象是中间的刺激（干扰刺激）会干扰任务表现。不幸的是，经典的 N-back 任务使用复杂的分类刺激，使其不适用于量化特征相似性对干扰强度的影响。在此，我们引入“模拟 N-back 任务”，该任务使用在方向或颜色上连续变化的刺激。这种任务变体使我们能够在连续统一体上测量干扰强度，提供适合使用计算模型识别干扰源的数据。在模拟 2-back 任务中，我们发现干扰随着探测刺激与任务相关（1-back）和任务无关（3-back）干扰刺激之间的特征相似性增加而增加。接下来，我们开发并评估了三个主要模型，每个模型都包含一个贝叶斯决策步骤，并且仅在一个组件上与最优无干扰模型不同：早期合并模型、晚期合并模型和替换模型。模型比较表明，干扰在处理后期出现，最有可能是由于工作记忆检索期间刺激之间的混淆。我们的工作将 N-back 任务中的干扰研究置于更坚实的计算基础上，并为跨领域研究干扰源提供了一个统一的框架。
