Understanding Image Memorability

Visual free recall and recognition in art students and laypeople

Artists and laypeople differ in their ability to create drawings. Previous research has shown that artists have improved memory performance during drawing; however, it is unclear whether they have better visual memory after the drawing is finished. In this paper, we focused on the question of differences in visual memory between art students and the general population in two studies. In Study 1, both groups studied a set of images and later drew them in a surprise visual recall test. In Study 2, the drawings from Study 1 were evaluated by a different set of raters based on their drawing quality and similarity to the original image to link drawing evaluations with memory performance for both groups. We found that both groups showed comparable visual recognition memory performance; however, the artist group showed increased recall memory performance. Moreover, they produced drawings that were both better quality and more similar to the original image. Individually, participants whose drawings were rated as better showed higher recognition accuracy. Results from Study 2 also have practical implications for the usage of drawing as a tool for measuring free recall - the majority of the drawings were recognizable, and raters showed a high level of consistency during their evaluation of the drawings. Taken together, we found that artists have better visual recall memory than laypeople.

Perceptual encoding benefit of visual memorability on visual memory formation

Human observers often exhibit remarkable consistency in remembering specific visual details, such as certain face images. This phenomenon is commonly attributed to visual memorability, a collection of stimulus attributes that enhance the long-term retention of visual information. However, the exact contributions of visual memorability to visual memory formation remain elusive as these effects could emerge anywhere from early perceptual encoding to post-perceptual memory consolidation processes. To clarify this, we tested three key predictions from the hypothesis that visual memorability facilitates early perceptual encoding that supports the formation of visual short-term memory (VSTM) and the retention of visual long-term memory (VLTM). First, we examined whether memorability benefits in VSTM encoding manifest early, even within the constraints of a brief stimulus presentation (100-200 ms; Experiment 1). We achieved this by manipulating stimulus presentation duration in a VSTM change detection task using face images with high- or low-memorability while ensuring they were equally familiar to the participants. Second, we assessed whether this early memorability benefit increases the likelihood of VSTM retention, even with post-stimulus masking designed to interrupt post-perceptual VSTM consolidation processes (Experiment 2). Last, we investigated the durability of memorability benefits by manipulating memory retention intervals from seconds to 24 h (Experiment 3). Across experiments, our data suggest that visual memorability has an early impact on VSTM formation, persisting across variable retention intervals and predicting subsequent VLTM overnight. Combined, these findings highlight that visual memorability enhances visual memory within 100-200 ms following stimulus onset, resulting in robust memory traces resistant to post-perceptual interruption and long-term forgetting.

Memorability shapes perceived time (and vice versa)

Visual stimuli are known to vary in their perceived duration. Some visual stimuli are also known to linger for longer in memory. Yet, whether these two features of visual processing are linked is unknown. Despite early assumptions that time is an extracted or higher-order feature of perception, more recent work over the past two decades has demonstrated that timing may be instantiated within sensory modality circuits. A primary location for many of these studies is the visual system, where duration-sensitive responses have been demonstrated. Furthermore, visual stimulus features have been observed to shift perceived duration. These findings suggest that visual circuits mediate or construct perceived time. Here we present evidence across a series of experiments that perceived time is affected by the image properties of scene size, clutter and memorability. More specifically, we observe that scene size and memorability dilate time, whereas clutter contracts it. Furthermore, the durations of more memorable images are also perceived more precisely. Conversely, the longer the perceived duration of an image, the more memorable it is. To explain these findings, we applied a recurrent convolutional neural network model of the ventral visual system, in which images are progressively processed over time. We find that more memorable images are processed faster, and that this increase in processing speed predicts both the lengthening and the increased precision of perceived durations. These findings provide evidence for a link between image features, time perception and memory that can be further explored with models of visual processing.

Higher-contrast images are better remembered during naturalistic encoding

It is unclear whether memory for images of poorer visibility (as low contrast or small size) will be lower due to weak signals elicited in early visual processing stages, or perhaps better since their processing may entail top-down processes (as effort and attention) associated with deeper encoding. We have recently shown that during naturalistic encoding (free viewing without task-related modulations), for image sizes between 3°-24°, bigger images stimulating more visual system processing resources at early processing stages are better remembered. Similar to size, higher contrast leads to higher activity in early visual processing. Therefore, here we hypothesized that during naturalistic encoding, at critical visibility ranges, higher contrast images will lead to higher signal-to-noise ratio and better signal quality flowing downstream and will thus be better remembered. Indeed, we found that during naturalistic encoding higher contrast images were remembered better than lower contrast ones (~ 15% higher accuracy, ~ 1.58 times better) for images at 7.5-60 RMS contrast range. Although image contrast and size modulate early visual processing very differently, our results further substantiate that at poor visibility ranges, during naturalistic non-instructed visual behavior, physical image dimensions (contributing to image visibility) impact image memory.

Actions are characterized by 'canonical moments' in a sequence of movements

Understanding what others are doing is an essential aspect of social cognition that depends on our ability to quickly recognize and categorize their actions. To effectively study action recognition we need to understand how actions are bounded, where they start and where they end. Here we borrow a conceptual approach - the notion of 'canonicality' - introduced by Palmer and colleagues in their study of object recognition and apply it to the study of action recognition. Using a set of 50 video clips sourced from stock photography sites, we show that many everyday actions - transitive and intransitive, social and non-social, communicative - are characterized by 'canonical moments' in a sequence of movements that are agreed by participants to 'best represent' a named action, as indicated in a forced choice (Exp 1, n = 142) and a free choice (Exp 2, n = 125) paradigm. In Exp 3 (n = 102) we confirm that canonical moments from action sequences are more readily named as depicting specific actions and, mirroring research in object recognition, that such canonical moments are privileged in memory (Exp 4, n = 95). We suggest that 'canonical moments', being those that convey maximal information about human actions, are integral to the representation of human action.1.

Memoir study: Investigating image memorability across developmental stages

Images have been shown to consistently differ in terms of their memorability in healthy adults: some images stick in one's mind while others are forgotten quickly. Studies have suggested that memorability is an intrinsic, continuous property of a visual stimulus that can be both measured and manipulated. Memory literature suggests that important developmental changes occur throughout adolescence that have an impact on recognition memory, yet the effect that these changes have on image memorability has not yet been investigated. In the current study, we recruited adolescents ages 11-18 (n = 273, mean = 16) to an online visual memory experiment to explore the effects of developmental changes throughout adolescence on image memorability, and determine if memorability findings in adults can be generalized to the adolescent age group. We used the online experiment to calculate adolescent memorability scores for 1,000 natural images, and compared the results to the MemCat dataset-a memorability dataset that is annotated with adult memorability scores (ages 19-27). Our study finds that memorability scores in adolescents and adults are strongly and significantly correlated (Spearman's rank correlation, r = 0.76, p < 0.001). This correlation persists even when comparing adults with developmentally different sub-groups of adolescents (ages 11-14: r = 0.67, p < 0.001; ages 15-18: r = 0.60, p < 0.001). Moreover, the rankings of image categories by mean memorability scores were identical in both adolescents and adults (including the adolescent sub-groups), indicating that broadly, certain image categories are more memorable for both adolescents and adults. Interestingly, however, adolescents experienced significantly higher false alarm rates than adults, supporting studies that show increased impulsivity and reward-seeking behaviour in adolescents. Our results reveal that the memorability of images remains consistent across individuals at different stages of development. This consistency aligns with and strengthens prior research, indicating that memorability is an intrinsic property of images. Our findings open new pathways for applying memorability studies in adolescent populations, with profound implications in fields such as education, marketing, and psychology. Our work paves the way for innovative approaches in these domains, leveraging the consistent nature of image memorability across age groups.

Perceived image size modulates visual memory

Previous studies have demonstrated that visual memory is improved when stimuli are processed by larger cortical regions. For example, a physically large stimulus that recruits larger areas of the retinotopic cortex is better remembered. However, the spatial extent of neural responses in the visual cortex is not only modulated by the retinal size of a stimulus, but also by the perceived size of the stimulus. In this online study, we modulated the perceived size of the visual stimuli using the Ebbinghaus illusion and asked participants to remember the stimuli. The results showed that perceptually larger images were remembered better than perceptually smaller but physically same-sized images. Our finding supports the idea that visual memory is modulated by top-down feedback from higher visual regions to the early visual cortex.

Memorability of line drawings of scenes: the role of contour properties

Why are some images more likely to be remembered than others? Previous work focused on the influence of global, low-level visual features as well as image content on memorability. To better understand the role of local, shape-based contours, we here investigate the memorability of photographs and line drawings of scenes. We find that the memorability of photographs and line drawings of the same scenes is correlated. We quantitatively measure the role of contour properties and their spatial relationships for scene memorability using a Random Forest analysis. To determine whether this relationship is merely correlational or if manipulating these contour properties causes images to be remembered better or worse, we split each line drawing into two half-images, one with high and the other with low predicted memorability according to the trained Random Forest model. In a new memorability experiment, we find that the half-images predicted to be more memorable were indeed remembered better, confirming a causal role of shape-based contour features, and, in particular, T junctions in scene memorability. We performed a categorization experiment on half-images to test for differential access to scene content. We found that half-images predicted to be more memorable were categorized more accurately. However, categorization accuracy for individual images was not correlated with their memorability. These results demonstrate that we can measure the contributions of individual contour properties to scene memorability and verify their causal involvement with targeted image manipulations, thereby bridging the gap between low-level features and scene semantics in our understanding of memorability.

Neurofunctional underpinnings of individual differences in visual episodic memory performance

Episodic memory, the ability to consciously recollect information and its context, varies substantially among individuals. While prior fMRI studies have identified certain brain regions linked to successful memory encoding at a group level, their role in explaining individual memory differences remains largely unexplored. Here, we analyze fMRI data of 1,498 adults participating in a picture encoding task in a single MRI scanner. We find that individual differences in responsivity of the hippocampus, orbitofrontal cortex, and posterior cingulate cortex account for individual variability in episodic memory performance. While these regions also emerge in our group-level analysis, other regions, predominantly within the lateral occipital cortex, are related to successful memory encoding but not to individual memory variation. Furthermore, our network-based approach reveals a link between the responsivity of nine functional connectivity networks and individual memory variability. Our work provides insights into the neurofunctional correlates of individual differences in visual episodic memory performance.

Tracing the emergence of the memorability benefit

Some visual stimuli are consistently better remembered than others across individuals, due to variations in memorability (the stimulus-intrinsic property that determines ease of encoding into visual long-term memory (VLTM)). However, it remains unclear what cognitive processes give rise to this mnemonic benefit. One possibility is that this benefit is imbued within the capacity-limited bottleneck of VLTM encoding, namely visual working memory (VWM). More precisely, memorable stimuli may be preferentially encoded into VLTM because fewer cognitive resources are required to store them in VWM (efficiency hypothesis). Alternatively, memorable stimuli may be more competitive in obtaining cognitive resources than forgettable stimuli, leading to more successful storage in VWM (competitiveness hypothesis). Additionally, the memorability benefit might emerge post-VWM, specifically, if memorable stimuli are less prone to be forgotten (i.e., are "stickier") than forgettable stimuli after they pass through the encoding bottleneck (stickiness hypothesis). To test this, we conducted two experiments to examine how memorability benefits emerge by manipulating the stimulus memorability, set size, and degree of competition among stimuli as participants encoded them in the context of a working memory task. Subsequently, their memory for the encoded stimuli was tested in a VLTM task. In the VWM task, performance was better for memorable stimuli compared to forgettable stimuli, supporting the efficiency hypothesis. In addition, we found that when in direct competition, memorable stimuli were also better at attracting limited VWM resources than forgettable stimuli, supporting the competitiveness hypothesis. However, only the efficiency advantage translated to a performance benefit in VLTM. Lastly, we found that memorable stimuli were less likely to be forgotten after they passed through the encoding bottleneck imposed by VWM, supporting the "stickiness" hypothesis. Thus, our results demonstrate that the memorability benefit develops across multiple cognitive processes.

Cross-cultural consistency of image memorability

Memorability refers to the intrinsic property of an image that determines how well it is remembered or forgotten. Recent studies have found that memorability is highly consistent across individuals. However, most studies on memorability were conducted with participants from Western cultures, and the images used in memorability studies were culturally biased. Previous studies implicitly assumed that memorability would be held constant across different cultural groups; however, to the best of our knowledge, this has not yet been empirically investigated. In the current study, we recruited participants from South Korea and the US and examined whether image memorability was consistent across these two cultures. We found that South Korean participants showed greater memory performance for images rated highly memorable by US participants. The current findings provide converging evidence that image memorability is not fully accounted for by individual differences, and suggest the possibility of cross-cultural consistency in image memorability.

Representations in human primary visual cortex drift over time

Primary sensory regions are believed to instantiate stable neural representations, yet a number of recent rodent studies suggest instead that representations drift over time. To test whether sensory representations are stable in human visual cortex, we analyzed a large longitudinal dataset of fMRI responses to images of natural scenes. We fit the fMRI responses using an image-computable encoding model and tested how well the model generalized across sessions. We found systematic changes in model fits that exhibited cumulative drift over many months. Convergent analyses pinpoint changes in neural responsivity as the source of the drift, while population-level representational dissimilarities between visual stimuli were unchanged. These observations suggest that downstream cortical areas may read-out a stable representation, even as representations within V1 exhibit drift.

The graded novelty encoding task: Novelty gradually improves recognition of visual stimuli under incidental learning conditions

It has been argued that novel compared to familiar stimuli are preferentially encoded into memory. Nevertheless, treating novelty as a categorical variable in experimental research is considered simplistic. We highlight the dimensional aspect of novelty and propose an experimental design that manipulates novelty continuously. We created the Graded Novelty Encoding Task (GNET), in which the difference between stimuli (i.e. novelty) is parametrically manipulated, paving the way for quantitative models of novelty processing. We designed an algorithm which generates visual stimuli by placing colored shapes in a grid. During the familiarization phase of the task, we repeatedly presented five pictures to the participants. In a subsequent incidental learning phase, participants were asked to differentiate between the "familiars" and novel images that varied in the degree of difference to the familiarized pictures (i.e. novelty). Finally, participants completed a surprise recognition memory test, where the novel stimuli from the previous phase were interspersed with distractors with similar difference characteristics. We numerically expressed the differences between the stimuli to compute a dimensional indicator of novelty and assessed whether it predicted recognition memory performance. Based on previous studies showing the beneficial effect of novelty on memory formation, we hypothesized that the more novel a given picture was, the better subsequent recognition performance participants would demonstrate. Our hypothesis was confirmed: recognition performance was higher for more novel stimuli. The GNET captures the continuous nature of novelty, and it may be useful in future studies that examine the behavioral and neurocognitive aspects of novelty processing.

Dissociating the Impact of Memorability on Electrophysiological Correlates of Memory Encoding Success

Despite its unlimited capacity, not all visual information we encounter is encoded into visual long-term memory. Traditionally, variability in encoding success has been ascribed to variability in the types and efficacy of an individual's cognitive processes during encoding. Accordingly, past studies have identified several neural correlates of variability in encoding success, namely, frontal positivity, occipital alpha amplitude, and frontal theta amplitude, by contrasting the electrophysiological signals recorded during successful and failed encoding processes (i.e., subsequent memory). However, recent research demonstrated individuals remember and forget consistent sets of stimuli, thereby elucidating stimulus-intrinsic factors (i.e., memorability) that determine the ease of memory encoding independent of individual-specific variability in encoding processes. The existence of memorability raises the possibility that canonical EEG correlates of subsequent memory may reflect variability in stimulus-intrinsic factors rather than individual-specific encoding processes. To test this, we recorded the EEG correlates of subsequent memory while participants encoded 600 images of real-world objects and assessed the unique contribution of individual-specific and stimulus-intrinsic factors on each EEG correlate. Here, we found that frontal theta amplitude and occipital alpha amplitude were only influenced by individual-specific encoding success, whereas frontal positivity was influenced by stimulus-intrinsic and individual-specific encoding success. Overall, our results offer novel interpretations of canonical EEG correlates of subsequent memory by demonstrating a dissociable impact of stimulus-intrinsic and individual-specific factors of memory encoding success.

Negative emotion reduces visual working memory recall variability: A meta-analytical review

Negative emotion is often hypothesized to trigger a more deliberate processing mode. This effect can manifest as increased precision of information maintained in working memory (WM) captured by reduced WM recall variability under an induced negative emotional state. However, some recent evidence shows that WM representations are immune to any emotional influences. Here, we meta-analyze existing evidence based on data from 13 experiments across 491 participants who performed a delay-estimation WM task under negative and neutral emotional states. We find that induced negative emotional state modestly reduces WM recall variability and increases recall failures relative to the neutral condition. These effects are moderated by participants' self-report negative experiences during emotion induction. Collectively, these data suggest that negative emotion influences how much and how well one can remember in WM. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Repetition enhances the effects of activated long-term memory

Recent research indicates that visual long-term memory (vLTM) representations directly interface with perception and guide attention. This may be accomplished through a state known as activated LTM, however, little is known about the nature of activated LTM. Is it possible to enhance the attentional effects of these activated representations? And furthermore, is activated LTM discrete (i.e., a representation is either active or not active, but only active representations interact with perception) or continuous (i.e., there are different levels within the active state that all interact with perception)? To answer these questions, in the present study, we measured intrusion effects during a modified Sternberg task. Participants saw two lists of three complex visual objects, were cued that only one list was relevant for the current trial (the other list was, thus, irrelevant), and then their memory for the cued list was probed. Critically, half of the trials contained repeat objects (shown 10 times each), and half of the trials contained non-repeat objects (shown only once each). Results indicated that repetition enhanced activated LTM, as the intrusion effect (i.e., longer reaction times to irrelevant list objects than novel objects) was larger for repeat trials compared with non-repeat trials. These initial findings provide preliminary support that LTM activation is continuous, as the intrusion effect was not the same size for repeat and non-repeat trials. We conclude that researchers should repeat stimuli to increase the size of their effects and enhance how LTM representations interact with perception.

The fate of visual long term memories for images across weeks in adults and children

What is the content and the format of visual memories in Long Term Memory (LTM)? Is it similar in adults and children? To address these issues, we investigated, in both adults and 9-year-old children, how visual LTM is affected over time and whether visual vs semantic features are affected differentially. In a learning phase, participants were exposed to hundreds of meaningless and meaningful images presented once or twice for either 120 ms or 1920 ms. Memory was assessed using a recognition task either immediately after learning or after a delay of three or six weeks. The results suggest that multiple and extended exposures are crucial for retaining an image for several weeks. Although a benefit was observed in the meaningful condition when memory was assessed immediately after learning, this benefit tended to disappear over weeks, especially when the images were presented twice for 1920 ms. This pattern was observed for both adults and children. Together, the results call into question the dominant models of LTM for images: although semantic information enhances the encoding & maintaining of images in LTM when assessed immediately, this seems not critical for LTM over weeks.

Identifying Objects and Remembering Images: Insights From Deep Neural Networks

People have a remarkable ability to identify the objects that they are looking at, as well as remember the images that they have seen. Researchers know that high-level visual cortex contributes in important ways to supporting both of these functions, but developing models that describe how processing in high-level visual cortex supports these behaviors has been challenging. Recent breakthroughs in this modeling effort have arrived by way of the illustration that deep artificial neural networks trained to categorize objects, developed for computer vision purposes, reflect brainlike patterns of activity. Here we summarize how deep artificial neural networks have been used to gain important insights into the contributions of high-level visual cortex to object identification, as well as one characteristic of visual memory behavior: image memorability, the systematic variation with which some images are remembered better than others.

Tracking induced forgetting across both strong and weak memory representations to test competing theories of forgetting

Here we employ a novel analysis to address the question: what causes induced forgetting of pictures? We use baseline memorability as a measure of initial memory strength to ask whether induced forgetting is due to (1) recognition practice damaging the association between the memory representation and the category cue used to activate the representation, (2) the updating of a memory trace by incorporating information about a memory probe presented during recognition practice to the stored trace, (3) inhibitory mechanisms used to resolve the conflict created when correctly selecting the practiced item activates competing exemplars, (4) a global matching model in which repeating some items will hurt memory for other items, or (5) falling into the zone of destruction, where a moderate amount of activation leads to the highest degree of forgetting. None of the accounts of forgetting tested here can comprehensively account for both the novel analyses reported here and previous data using the induced forgetting paradigm. We discuss aspects of forgetting theories that are consistent with the novel analyses and existing data, a potential solution for existing models, proposals for future directions, and considerations when incorporating memorability into models of memory.

Visual prototypes in the ventral stream are attuned to complexity and gaze behavior

Early theories of efficient coding suggested the visual system could compress the world by learning to represent features where information was concentrated, such as contours. This view was validated by the discovery that neurons in posterior visual cortex respond to edges and curvature. Still, it remains unclear what other information-rich features are encoded by neurons in more anterior cortical regions (e.g., inferotemporal cortex). Here, we use a generative deep neural network to synthesize images guided by neuronal responses from across the visuocortical hierarchy, using floating microelectrode arrays in areas V1, V4 and inferotemporal cortex of two macaque monkeys. We hypothesize these images ("prototypes") represent such predicted information-rich features. Prototypes vary across areas, show moderate complexity, and resemble salient visual attributes and semantic content of natural images, as indicated by the animals' gaze behavior. This suggests the code for object recognition represents compressed features of behavioral relevance, an underexplored aspect of efficient coding.

Noun-phrase production as a window to language selection: An ERP study

Characterising the time course of non-native language production is critical in understanding the mechanisms behind successful communication. Yet, little is known about the modulating role of cross-linguistic influence (CLI) on the temporal unfolding of non-native production and the locus of target language selection. In this study, we explored CLI effects on non-native noun phrase production with behavioural and neural methods. We were particularly interested in the modulation of the P300 as an index for inhibitory control, and the N400 as an index for co-activation and CLI. German late learners of Spanish overtly named pictures while their EEG was monitored. Our results indicate traceable CLI effects at the behavioural and neural level in both early and late production stages. This suggests that speakers faced competition between the target and non-target language until advanced production stages. Our findings add important behavioural and neural evidence to the underpinnings of non-native production processes, in particular for late learners.

ResMem-Net: memory based deep CNN for image memorability estimation

Image memorability is a very hard problem in image processing due to its subjective nature. But due to the introduction of Deep Learning and the large availability of data and GPUs, great strides have been made in predicting the memorability of an image. In this paper, we propose a novel deep learning architecture called ResMem-Net that is a hybrid of LSTM and CNN that uses information from the hidden layers of the CNN to compute the memorability score of an image. The intermediate layers are important for predicting the output because they contain information about the intrinsic properties of the image. The proposed architecture automatically learns visual emotions and saliency, shown by the heatmaps generated using the GradRAM technique. We have also used the heatmaps and results to analyze and answer one of the most important questions in image memorability: "What makes an image memorable?". The model is trained and evaluated using the publicly available Large-scale Image Memorability dataset (LaMem) from MIT. The results show that the model achieves a rank correlation of 0.679 and a mean squared error of 0.011, which is better than the current state-of-the-art models and is close to human consistency (p = 0.68). The proposed architecture also has a significantly low number of parameters compared to the state-of-the-art architecture, making it memory efficient and suitable for production.

Comparing Object Recognition in Humans and Deep Convolutional Neural Networks-An Eye Tracking Study

Deep convolutional neural networks (DCNNs) and the ventral visual pathway share vast architectural and functional similarities in visual challenges such as object recognition. Recent insights have demonstrated that both hierarchical cascades can be compared in terms of both exerted behavior and underlying activation. However, these approaches ignore key differences in spatial priorities of information processing. In this proof-of-concept study, we demonstrate a comparison of human observers (N = 45) and three feedforward DCNNs through eye tracking and saliency maps. The results reveal fundamentally different resolutions in both visualization methods that need to be considered for an insightful comparison. Moreover, we provide evidence that a DCNN with biologically plausible receptive field sizes called vNet reveals higher agreement with human viewing behavior as contrasted with a standard ResNet architecture. We find that image-specific factors such as category, animacy, arousal, and valence have a direct link to the agreement of spatial object recognition priorities in humans and DCNNs, while other measures such as difficulty and general image properties do not. With this approach, we try to open up new perspectives at the intersection of biological and computer vision research.

Cross-linguistic interference in late language learners: An ERP study

This study investigated cross-linguistic interference in German low-proficient late learners of Spanish. We examined the modulating influence of gender congruency and cognate status using a syntactic violation paradigm. Behavioural results demonstrated that participants were more sensitive to similarities at the syntactic level (gender congruency) than to phonological and orthographic overlap (cognate status). Electrophysiological data showed that they were sensitive to syntactic violations (P600 effect) already in early acquisition stages. However, P600 effect sizes were not modulated by gender congruency or cognate status. Therefore, our late learners of Spanish did not seem to be susceptible to influences from inherent noun properties when processing non-native noun phrases at the neural level. Our results contribute to the discussion about the neural correlates of grammatical gender processing and sensitivity to syntactic violations in early acquisition stages.

The Citation Diversity Statement: A Practice of Transparency, A Way of Life

Appending a Citation Diversity Statement to a paper is a simple and effective way to increase awareness about citation bias and help mitigate it. Here, we describe why reducing citation bias is important and how to include a Citation Diversity Statement in your next publication.

Recognition Receiver Operating Characteristic Curves: The Complex Influence of Input Statistics, Memory, and Decision-making

Receiver operating characteristic (ROC) analysis is the standard tool for studying recognition memory. In particular, the curvilinearity and the y-offset of recognition ROC curves have been interpreted as indicative of either memory strength (single-process models) or different memory processes (dual-process model). The distinction between familiarity and recollection has been widely studied in cognitive neuroscience in a variety of conditions, including lesions of different brain regions. We develop a computational model that explicitly shows how performance in recognition memory is affected by a complex and, as yet, underappreciated interplay of various factors, such as stimulus statistics, memory processing, and decision-making. We demonstrate that (1) the factors in the model affect recognition ROC curves in unexpected ways, (2) fitting R and F parameters according to the dual-process model is not particularly useful for understanding the underlying processes, and (3) the variability of recognition ROC curves and the controversies they have caused might be due to the uncontrolled variability in the contributing factors. Although our model is abstract, its functional components can be mapped onto brain regions, which are involved in corresponding functions. This enables us to reproduce and interpret in a coherent framework the diverse effects on recognition memory that have been reported in patients with frontal and hippocampal lesions. To conclude, our work highlights the importance of the rich interplay of a variety of factors in driving recognition memory performance, which has to be taken into account when interpreting recognition ROC curves.

When Natural Behavior Engages Working Memory

Working memory (WM) enables temporary storage and manipulation of information,¹ supporting tasks that require bridging between perception and subsequent behavior. Its properties, such as its capacity, have been thoroughly investigated in highly controlled laboratory tasks.1, 2, 3, 4, 5, 6, 7, 8 Much less is known about the utilization and properties of WM in natural behavior,9, 10, 11 when reliance on WM emerges as a natural consequence of interactions with the environment. We measured the trade-off between reliance on WM and gathering information externally during immersive behavior in an adapted object-copying task.¹² By manipulating the locomotive demands required for task completion, we could investigate whether and how WM utilization changed as gathering information from the environment became more effortful. Reliance on WM was lower than WM capacity measures in typical laboratory tasks. A clear trade-off also occurred. As sampling information from the environment required increasing locomotion and time investment, participants relied more on their WM representations. This reliance on WM increased in a shallow and linear fashion and was associated with longer encoding durations. Participants’ avoidance of WM usage showcases a fundamental dependence on external information during ecological behavior, even if the potentially storable information is well within the capacity of the cognitive system. These foundational findings highlight the importance of using immersive tasks to understand how cognitive processes unfold within natural behavior. Our novel VR approach effectively combines the ecological validity, experimental rigor, and sensitive measures required to investigate the interplay between memory and perception in immersive behavior.

Video Abstract

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Gaze provides a measure of working-memory (WM) usage during natural behavior

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Natural reliance on WM is low even when searching for objects externally is effortful

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WM utilization increases linearly as searching for objects requires more locomotion

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The trade-off between using WM versus external sampling affects performance

The effect of intrinsic image memorability on recollection and familiarity

Many photographs of real-life scenes are very consistently remembered or forgotten by most people, making these images intrinsically memorable or forgettable. Although machine vision algorithms can predict a given image's memorability very well, nothing is known about the subjective quality of these memories: are memorable images recognized based on strong feelings of familiarity or on recollection of episodic details? We tested people's recognition memory for memorable and forgettable scenes selected from image memorability databases, which contain memorability scores for each image, based on large-scale recognition memory experiments. Specifically, we tested the effect of intrinsic memorability on recollection and familiarity using cognitive computational models based on receiver operating characteristics (ROCs; Experiment 1 and 2) and on remember/know (R/K) judgments (Experiment 2). The ROC data of Experiment 2 indicated that image memorability boosted memory strength, but did not find a specific effect on recollection or familiarity. By contrast, ROC data from Experiment 2, which was designed to facilitate encoding and, in turn, recollection, found evidence for a specific effect of image memorability on recollection. Moreover, R/K judgments showed that, on average, memorability boosts recollection rather than familiarity. However, we also found a large degree of variability in these judgments across individual images: some images actually achieved high recognition rates by exclusively boosting familiarity rather than recollection. Together, these results show that current machine vision algorithms that can predict an image's intrinsic memorability in terms of hit rates fall short of describing the subjective quality of human memories.