The visual and semantic features that predict object memory: Concept property norms for 1,000 object images

Abstract

Humans have a remarkable fidelity for visual long-term memory, and yet the composition of these memories is a longstanding debate in cognitive psychology. While much of the work on long-term memory has focused on processes associated with successful encoding and retrieval, more recent work on visual object recognition has developed a focus on the memorability of specific visual stimuli. Such work is engendering a view of object representation as a hierarchical movement from low-level visual representations to higher level categorical organization of conceptual representations. However, studies on object recognition often fail to account for how these high- and low-level features interact to promote distinct forms of memory. Here, we use both visual and semantic factors to investigate their relative contributions to two different forms of memory of everyday objects. We first collected normative visual and semantic feature information on 1,000 object images. We then conducted a memory study where we presented these same images during encoding (picture target) on Day 1, and then either a Lexical (lexical cue) or Visual (picture cue) memory test on Day 2. Our findings indicate that: (1) higher level visual factors (via DNNs) and semantic factors (via feature-based statistics) make independent contributions to object memory, (2) semantic information contributes to both true and false memory performance, and (3) factors that predict object memory depend on the type of memory being tested. These findings help to provide a more complete picture of what factors influence object memorability. These data are available online upon publication as a public resource.

Effects of aging on successful object encoding: Enhanced semantic representations compensate for impaired visual representations

“…The visual model was created by feeding the object images through the DNN, extracting the activation values from layer 2, and correlating the values between the stimuli resulting in a 240 x 240 similarity matrix. This was then turned into a dissimilarity matrix by computing the pairwise dissimilarity values as 1 – Pearson’s correlation, resulting in the final visual model. Construction of the semantic feature RDM followed Clarke and Tyler (2014) but used updated property norms (Hovhannisyan et al, 2021). We first computed pairwise feature similarity between concepts from a semantic feature matrix in which each concept is represented by a binary vector indicating whether a given feature is associated with the concept or not.…”

Effects of item distinctiveness on the retrieval of objects and object-location bindings from visual working memory

“…Furthermore, Störmer (2020, 2021) demonstrated that the meaningfulness of to be remembered stimuli, that is, the ability of these stimuli to be recognized as everyday objects, human faces, etc., boosts VWM capacity and that this boost cannot be explained solely by perceptual differences between meaningful and meaningless stimuli (Asp et al, 2021). Based on these findings, we suggest that conceptual distinctiveness, along with perceptual similarity (Hovhannisyan et al, 2021;Hu, Liu, Song, Wang, & Zhao, 2020;Napsi et al, 2020;Otsuka, Nishiyama, Nakahara, & Kawaguchi, 2013;Xie & Zaghloul, 2021), can also be an important determinant of VWM for real-world objects.…”

The link between conceptual and perceptual information in memory

“…The organization of a CNN, in which internal "hidden" layers of nodes feed information forward to a final output layer, has parallels with the organization of the human visual system (Yamins & DiCarlo, 2016), in which representations shift from more basic visual features to higherlevel object categorization as one moves from posterior to anterior regions (Coutanche et al, 2016). Recently, studies of memorability have been extended to semantic features, finding that the interrelatedness of item features positively predicts hit rates on visual and lexical memory tests (Hovhannisyan et al, 2021). Interestingly, hit rates are correlated across tests, suggesting some similarity in the basis for perceptual and conceptual memory traces.…”