Institute for Systems and Robotics, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal.
School of Psychology, University of East London, London, UK.
Cogn Process. 2024 Feb;25(1):173-187. doi: 10.1007/s10339-023-01164-y. Epub 2023 Oct 13.
Humans display remarkable long-term visual memory (LTVM) processes. Even though images may be intrinsically memorable, the fidelity of their visual representations, and consequently the likelihood of successfully retrieving them, hinges on their similarity when concurrently held in LTVM. In this debate, it is still unclear whether intrinsic features of images (perceptual and semantic) may be mediated by mechanisms of interference generated at encoding, or during retrieval, and how these factors impinge on recognition processes. In the current study, participants (32) studied a stream of 120 natural scenes from 8 semantic categories, which varied in frequencies (4, 8, 16 or 32 exemplars per category) to generate different levels of category interference, in preparation for a recognition test. Then they were asked to indicate which of two images, presented side by side (i.e. two-alternative forced-choice), they remembered. The two images belonged to the same semantic category but varied in their perceptual similarity (similar or dissimilar). Participants also expressed their confidence (sure/not sure) about their recognition response, enabling us to tap into their metacognitive efficacy (meta-d'). Additionally, we extracted the activation of perceptual and semantic features in images (i.e. their informational richness) through deep neural network modelling and examined their impact on recognition processes. Corroborating previous literature, we found that category interference and perceptual similarity negatively impact recognition processes, as well as response times and metacognitive efficacy. Moreover, images semantically rich were less likely remembered, an effect that trumped a positive memorability boost coming from perceptual information. Critically, we did not observe any significant interaction between intrinsic features of images and interference generated either at encoding or during retrieval. All in all, our study calls for a more integrative understanding of the representational dynamics during encoding and recognition enabling us to form, maintain and access visual information.
人类表现出显著的长期视觉记忆 (LTVM) 过程。即使图像本身具有记忆性,但其视觉表示的保真度,以及成功检索它们的可能性,都取决于它们在 LTVM 中同时保持的相似性。在这场辩论中,仍然不清楚图像的内在特征(感知和语义)是否可以通过在编码或检索期间产生的干扰机制来介导,以及这些因素如何影响识别过程。在当前的研究中,参与者 (32) 研究了来自 8 个语义类别的 120 个自然场景的流,这些场景的频率不同(每个类别 4、8、16 或 32 个示例),以产生不同水平的类别干扰,为识别测试做准备。然后,他们被要求指出并排呈现的两个图像(即二选一强制选择)中他们记住了哪个。这两个图像属于相同的语义类别,但在感知相似性上有所不同(相似或不相似)。参与者还表达了他们对识别反应的信心(确定/不确定),使我们能够深入了解他们的元认知效能(元 d')。此外,我们通过深度神经网络建模提取了图像中感知和语义特征的激活(即信息丰富度),并研究了它们对识别过程的影响。与之前的文献一致,我们发现类别干扰和感知相似性会对识别过程产生负面影响,包括反应时间和元认知效能。此外,语义上丰富的图像不太可能被记住,这种效果超过了来自感知信息的积极记忆提升。重要的是,我们没有观察到图像内在特征与编码或检索期间产生的干扰之间存在任何显著的相互作用。总的来说,我们的研究呼吁对编码和识别过程中的表示动态进行更综合的理解,使我们能够形成、保持和访问视觉信息。