Mountains of memory in a sea of uncertainty: Sampling the external world despite useful information in visual working memory

工作记忆 心理学 认知心理学 重采样 网格 采样(信号处理) 计算机科学 人工智能 认知 计算机视觉 地理 神经科学 大地测量学 滤波器(信号处理)
作者
Andre Sahakian,Surya Gayet,Chris Paffen,Stefan Van der Stigchel
出处
期刊:Cognition [Elsevier]
卷期号:234: 105381-105381 被引量:12
标识
DOI:10.1016/j.cognition.2023.105381
摘要

A large part of research on visual working memory (VWM) has traditionally focused on estimating its maximum capacity. Yet, humans rarely need to load up their VWM maximally during natural behavior, since visual information often remains accessible in the external world. Recent work, using paradigms that take into account the accessibility of information in the outside world, has indeed shown that observers utilize only one or two items in VWM before sampling from the external world again. One straightforward interpretation of this finding is that, in daily behavior, much fewer items are memorized than the typically reported capacity limits. Here, we first investigate whether this lower reliance on VWM when information is externally accessible might instead reflect resampling before VWM is actually depleted. To this aim we devised an online task, in which participants copied a model (six items in a 4x4 grid; always accessible) in an adjacent empty 4x4 grid. A key aspect of our paradigm is that we (unpredictably) interrupted participants just before inspection of the model with a 2-alternative-forced-choice (2-AFC) question, probing their VWM content. Critically, we observed above-chance performance on probes appearing just before model inspection. This finding shows that the external world was resampled, despite VWM still containing relevant information. We then asked whether increasing the cost of sampling causes participants to load up more information in VWM or, alternatively, to squeeze out more information from VWM (at the cost of making more errors). To manipulate the cost of resampling, we made it more difficult (specifically, more time-consuming) to access the model. We show that with increased cost of accessing the model (which lead to fewer, but longer model inspections), participants could place more items correctly immediately after sampling, and they kept attempting to place items for longer after their first error. These findings demonstrate that participants both encoded more information in VWM and made attempts to squeeze out more information from VWM when sampling became more costly. We argue that human observers constantly evaluate how certain they are of their VWM contents, and only use that VWM content of which their certainty exceeds a context-dependent "action threshold". This threshold, in turn, depends on the trade-off between the cost of resampling and the benefits of making an action. We argue that considering the interplay between the available VWM contents and a context-dependent action threshold, is key for reconciling the traditional VWM literature with VWM use in our day-to-day behavior.

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