Visual Memorability Research Articles

The visual memorability of natural warning patterns: insights from humans and machines

The visual memorability of natural warning patterns: insights from humans and machines

Comparing artificial neural network models with varied objectives to probe the role of sensory representation in primate visual memorability

Comparing artificial neural network models with varied objectives to probe the role of sensory representation in primate visual memorability

Visual perception of highly memorable images is mediated by a distributed network of ventral visual regions that enable a late memorability response.

Behavioral and neuroscience studies in humans and primates have shown that memorability is an intrinsic property of an image that predicts its strength of encoding into and retrieval from memory. While previous work has independently probed when or where this memorability effect may occur in the human brain, a description of its spatiotemporal dynamics is missing. Here, we used representational similarity analysis (RSA) to combine functional magnetic resonance imaging (fMRI) with source-estimated magnetoencephalography (MEG) to simultaneously measure when and where the human cortex is sensitive to differences in image memorability. Results reveal that visual perception of High Memorable images, compared to Low Memorable images, recruits a set of regions of interest (ROIs) distributed throughout the ventral visual cortex: a late memorability response (from around 300 ms) in early visual cortex (EVC), inferior temporal cortex, lateral occipital cortex, fusiform gyrus, and banks of the superior temporal sulcus. Image memorability magnitude results are represented after high-level feature processing in visual regions and reflected in classical memory regions in the medial temporal lobe (MTL). Our results present, to our knowledge, the first unified spatiotemporal account of visual memorability effect across the human cortex, further supporting the levels-of-processing theory of perception and memory.

Learning the visual memorability of images with feedback-based training

Learning the visual memorability of images with feedback-based training

Revealing the Relative Contributions of Conceptual and Perceptual Information to Visual Memorability

Revealing the Relative Contributions of Conceptual and Perceptual Information to Visual Memorability

Visual memorability in the absence of semantic content

What determines how well people remember images? Most past research has explored properties of the people doing the remembering — such as their age, emotional state, or individual capacity. However, recent work has also characterized memorability — the likelihood of an image being remembered across observers. But what makes some images more memorable than others? Part of the answer must surely involve the meanings of the images, but here we ask whether this is the entire story: is there also purely visual memorability, driven not by semantic content but by perceptual features per se? We isolated visual memorability in an especially direct manner — by eliminating semantic content while retaining many visual properties. We did so by transforming a set of natural scene images using phase scrambling, and then testing memorability for both intact and scrambled images in independent samples. Across several experiments, observers saw sequences of images and responded anytime they saw a repeated image. We found reliable purely visual memorability at the temporal scales of both short-term memory (2–15 s) and longer-term memory (several minutes), and this could not be explained by the extent to which people could generate semantic labels for some scrambled images. Collectively, these results suggest that the memorability of images is a function not only of what they mean, but also of how they look in the first place.

Prediction of Visual Memorability with EEG Signals: A Comparative Study

Visual memorability is a method to measure how easily media contents can be memorized. Predicting the visual memorability of media contents has recently become more important because it can affect the design principles of multimedia visualization, advertisement, etc. Previous studies on the prediction of the visual memorability of images generally exploited visual features (e.g., color intensity and contrast) or semantic information (e.g., class labels) that can be extracted from images. Some other works tried to exploit electroencephalography (EEG) signals of human subjects to predict the memorability of text (e.g., word pairs). Compared to previous works, we focus on predicting the visual memorability of images based on human biological feedback (i.e., EEG signals). For this, we design a visual memory task where each subject is asked to answer whether they correctly remember a particular image 30 min after glancing at a set of images sampled from the LaMemdataset. During the visual memory task, EEG signals are recorded from subjects as human biological feedback. The collected EEG signals are then used to train various classification models for prediction of image memorability. Finally, we evaluate and compare the performance of classification models, including deep convolutional neural networks and classical methods, such as support vector machines, decision trees, and k-nearest neighbors. The experimental results validate that the EEG-based prediction of memorability is still challenging, but a promising approach with various opportunities and potentials.

Visual memorability in the absence of semantic content

Visual memorability in the absence of semantic content

Radiologists remember mountains better than radiographs, or do they?

Expertise with encoding material has been shown to aid long-term memory for that material. It is not clear how relevant this expertise is for image memorability (e.g., radiologists' memory for radiographs), and how robust over time. In two studies, we tested scene memory using a standard long-term memory paradigm. One compared the performance of radiologists to naïve observers on two image sets, chest radiographs and everyday scenes, and the other radiologists' memory with immediate as opposed to delayed recognition tests using musculoskeletal radiographs and forest scenes. Radiologists' memory was better than novices for images of expertise but no different for everyday scenes. With the heterogeneity of image sets equated, radiologists' expertise with radiographs afforded them better memory for the musculoskeletal radiographs than forest scenes. Enhanced memory for images of expertise disappeared over time, resulting in chance level performance for both image sets after weeks of delay. Expertise with the material is important for visual memorability but not to the same extent as idiosyncratic detail and variability of the image set. Similar memory decline with time for images of expertise as for everyday scenes further suggests that extended familiarity with an image is not a robust factor for visual memorability.

Neural Signatures of Visual Memorability: Memory in the First Perception of an Image

Neural Signatures of Visual Memorability: Memory in the First Perception of an Image

What makes a picture memorable?

‘Mental sports’ have become a new trend in self-improvement, with video games designed to improve mental fitness. At the World Memory Championships, athletes compete to recall massive amounts of information; contestants must memorize and recall sequences of abstract images and the names of people whose faces are shown in photographs. While these tasks might seem challenging, our research suggests that images that possess certain properties are memorable. Our findings can explain why we have all had some images stuck in our minds, but ignored or quickly forgotten others. Although image memorability seems subjective and hard to quantify, our recent work1–5 shows that it is not an inexplicable phenomenon. We found that visual memorability is largely intrinsic to the image and reproducible across a diverse population. This means that despite varied experiences, individuals tend to remember and forget the same images. Using experimental data detailing the types of images people remember or quickly forget, we developed an algorithm that automatically predicts whether an image will be memorable. To determine the intrinsic features that make an image memorable, we first asked 665 individuals to participate in a computer memory game. During each level of the game, for up to 30 levels, participants viewed a stream of images and then pressed the space bar whenever they saw one of those images repeated in a subsequent sequence. In total, the image database contained 2222 repeated images and 8220 unrepeated images that included faces, interior-design photos, nature scenes, streetscapes, and others. We found that photographs with people or central objects were memorable, whereas landscapes—that one might expect to be memorable—were among the most forgettable (see Figure 1).1 Next, we assigned a ‘memorability score’ to each image, which was defined as the percent of correct detections by participants in the study. On average, 78 participants scored each Figure 1. A sample of the photos used to develop an algorithm that predicts image memorability.1 The photos are scaled according to their experimentally measured memorability, with the most memorable photos appearing larger and in the center.

Topia: Landscape before Linear Perspective

Landscape is commonly deemed to be a western European Renaissance invention linked to the theorization of linear perspective as a distinctively “modern” way of looking at the world. Prompted by a resurging interest in premodern geographies, this article takes a step back and interrogates nonlinear perceptions and graphic representations of the environment in Roman antiquity (the so-called topia) and their development in the Byzantine world. Since the times of Alexander von Humboldt, these representations have been generally dismissed as “artificial” and “disregardful of perspective.” I propose a rereading of this perceived “lack of technique,” or “disinterest in nature” as a different “way of seeing” and making sense of the world, emphasizing the visual energheia and memorability of singular elements (or places) over their modern linear integration. Tracing the complex etymological and visual history of topia sheds light not only on “ways of seeing” and geographical traditions understudied in our discipline but also on a further aspect of landscape: that of a container of symbolic memory places.