Memorability: A stimulus-driven perceptual neural signature distinctive from memory

Gaze dynamics during natural scene memorization and recognition

Humans can rapidly memorize numerous images, which is surprising considering the limited visual sampling of each image. To enhance the probability of recognition, it is crucial to focus on previously sampled locations most likely to support memory. How does the visuomotor system achieve this? To study this, we analyzed the eye movements of a group of neurotypical observers while they performed a natural scene memorization task. Using comprehensive gaze analysis and computational modeling, we show that observers traded off visual exploration for exploiting information at the most memorable scene locations with repeated viewing. Furthermore, both the explore-exploit trade-off and gaze consistency predicted accurate recognition memory. Finally, false alarms were predicted by confusion of the incoming visual information at fixated locations with previously sampled information from other images. Together, our findings shed light on the symbiotic relationship between attention and memory in facilitating accurate natural scene memory.

Trial-level Representational Similarity Analysis

Neural representation refers to the brain activity that stands in for one's cognitive experience, and in cognitive neuroscience, the principal method to studying neural representations is representational similarity analysis (RSA). The classic RSA (cRSA) approach examines the overall quality of representations across numerous items by assessing the correspondence between two representational similarity matrices (RSMs): one based on a theoretical model of stimulus similarity and the other based on similarity in measured neural data. However, because cRSA cannot model representation at the level of individual trials, it is fundamentally limited in its ability to assess subject-, stimulus-, and trial-level variances that all influence representation. Here, we formally introduce trial-level RSA (tRSA), an analytical framework that estimates the strength of neural representation for singular experimental trials and evaluates hypotheses using multi-level models. First, we verified the correspondence between tRSA and cRSA in quantifying the overall representation strength across all trials. Second, we compared the statistical inferences drawn from both approaches using simulated data that reflected a wide range of scenarios. Compared to cRSA, the multi-level framework of tRSA was both more theoretically appropriate and significantly sensitive to true effects. Third, using real fMRI datasets, we further demonstrated several issues with cRSA, to which tRSA was more robust. Finally, we presented some novel findings of neural representations that could only be assessed with tRSA and not cRSA. In summary, tRSA proves to be a robust and versatile analytical approach for cognitive neuroscience and beyond.

Memorability of novel words correlates with anterior fusiform activity during reading

Our memory for the words we already know is best predicted by their associated meanings. However, the factors that influence whether we will remember a new word after we see it for the first time are unclear. We record memory performance for 2100 novel pseudowords across 1804 participants during a continuous recognition task. Participants show significant agreement across individuals for which novel words were memorable or forgettable, suggesting an intrinsic memorability for individual pseudowords. Pseudowords that are similar to low-frequency known words, with sparse orthographic neighbourhoods and rarely occurring letter pairs, are more memorable. Further, using intracranial recordings in 36 epilepsy patients we show a region in the anterior fusiform cortex that shows sensitivity to the memorability of these pseudowords. These results suggest that known words in our lexicon act as a scaffold for remembering novel word forms, with rare and unique known words providing the best support for novel word learning.

Visual homogeneity computations in the brain enable solving property-based visual tasks

Most visual tasks involve looking for specific object features. But we also often perform property-based tasks where we look for specific property in an image, such as finding an odd item, deciding if two items are same, or if an object has symmetry. How do we solve such tasks? These tasks do not fit into standard models of decision making because their underlying feature space and decision process is unclear. Using well-known principles governing multiple object representations, we show that displays with repeating elements can be distinguished from heterogeneous displays using a property we define as visual homogeneity. In behavior, visual homogeneity predicted response times on visual search, same-different and symmetry tasks. Brain imaging during visual search and symmetry tasks revealed that visual homogeneity was localized to a region in the object-selective cortex. Thus, property-based visual tasks are solved in a localized region in the brain by computing visual homogeneity.

Pupillary Responses Reflect Image Memorability

This study examined whether pupil size varies as a function of the memorability of natural scene images. In Experiment 1, participants were asked to memorize, recognize, and passively view high- and low-memorability images from an established dataset. The baseline-corrected pupil sizes were larger for high-memorability images, but only during old trials in the recognition phase. However, after implementing stricter controls for image luminance and arousal, pupil dilation for high-memorability images was observed across all phases: memorization, recognition, and passive viewing (Experiments 2 and 3). The effect of image memorability was further validated through item-based analysis. Both the pupil old/new effect and the subsequent memory effect were replicated, and these effects are probably separable from the effect of image memorability. The results of this study suggest that pupil size is sensitive to image memorability regardless of the behavioral task, supporting the view that image memorability is an intrinsic, higher-order property of the image.

Coordinated representations for naturalistic memory encoding and retrieval in hippocampal neural subspaces

Our naturalistic experiences are organized into memories through multiple processes, including novelty encoding, memory formation, and retrieval. However, the neural mechanisms coordinating these processes remain elusive. Using fMRI data acquired during movie viewing and subsequent narrative recall, we examine hippocampal neural subspaces associated with distinct memory processes and characterized their relationships. We quantify novelty in character co-occurrences and the valence of relationships and estimate event memorability. Within the hippocampus, the novelty subspaces encoding each type exhibit partial overlap, and these overlapping novelty subspaces align with the subspace involved in memorability. Notably, following event boundaries, hippocampal states within these subspaces align inversely along a shared coding axis, predicting subsequent recall performance. This novelty-memorability alignment is selectively observed during encoding but not during retrieval. Finally, the identified functional subspaces reflect the intrinsic functional organization of the hippocampus. Our findings offer insights into how the hippocampus dynamically coordinates representations underlying memory encoding and retrieval at the population level to transform ongoing experiences into enduring memories.

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.

Positive affect amplifies integration within episodic memories in the laboratory and the real world

Emotional events hold a privileged place in our memories, differing in accuracy and structure from memories for neutral experiences. Although much work has focused on the pronounced differences in memory for negative experiences, there is growing evidence that positive events may lead to more holistic, or integrated, memories. However, it is unclear whether these affect-driven changes in memory structure, which have been found in highly controlled laboratory environments, extend to real-world episodic memories. We ran experiments that assessed memory for experiences created in the laboratory (Experiment 1) and, using smartphones, memories for everyday experiences (Experiment 2). We complement these design innovations with a novel analysis approach to model memory accuracy and integration in both settings. Consistent with past findings, emotional events were subjectively remembered more strongly. These studies also revealed that features of more positive events were indeed more integrated within memory, both in the laboratory and the real world. These effects were specific to participants' emotional responses to the events during encoding rather than general emotional states at the time of retrieval, and reflected a general increase in integration between multiple memory features. Together, these results demonstrate robust differences in memory for positive events, introduce a novel measure of memory integration, and highlight the importance of assessing the impact of emotion on memory beyond the laboratory.

Navigating Memorability Landscapes: Hyperbolic Geometry Reveals Hierarchical Structures in Object Concept Memory

Why are some object concepts (e.g., birds, cars, vegetables, etc.) more memorable than others? Prior studies have suggested that features (e.g., color, animacy, etc.) and typicality (e.g., robin vs. penguin) of object images influences the likelihood of being remembered. However, a complete understanding of object memorability remains elusive. In this study, we examine whether the geometric relationship between object concepts explains differences in their memorability. Specifically, we hypothesize that image concepts will be geometrically arranged in hierarchical structures and that memorability will be explained by a concept's depth in these hierarchical trees. To test this hypothesis, we construct a Hyperbolic representation space of object concepts (N=1,854) from the THINGS database (Hebart et al., 2019), which consists of naturalistic images of concrete objects, and a space of 49 feature dimensions derived from data-driven models. Using ALBATROSS (Stier, A. J., Giusti, C., & Berman, M. G., In prep), a stochastic topological data analysis technique that detects underlying structures of data, we demonstrate that Hyperbolic geometry efficiently captures the hierarchical organization of object concepts above and beyond a traditional Euclidean geometry and that hierarchical organization is related to memorability. We find that concepts closer to the center of the representational space are more prototypical and also more memorable. Importantly, Hyperbolic distances are more predictive of memorability and prototypicality than Euclidean distances, suggesting that concept memorability and typicality are organized hierarchically. Taken together, our work presents a novel hierarchical representational structure of object concepts that explains memorability and typicality.

Modeling short visual events through the BOLD moments video fMRI dataset and metadata

Studying the neural basis of human dynamic visual perception requires extensive experimental data to evaluate the large swathes of functionally diverse brain neural networks driven by perceiving visual events. Here, we introduce the BOLD Moments Dataset (BMD), a repository of whole-brain fMRI responses to over 1000 short (3 s) naturalistic video clips of visual events across ten human subjects. We use the videos' extensive metadata to show how the brain represents word- and sentence-level descriptions of visual events and identify correlates of video memorability scores extending into the parietal cortex. Furthermore, we reveal a match in hierarchical processing between cortical regions of interest and video-computable deep neural networks, and we showcase that BMD successfully captures temporal dynamics of visual events at second resolution. With its rich metadata, BMD offers new perspectives and accelerates research on the human brain basis of visual event perception.

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.

Positive affect modulates memory by regulating the influence of reward prediction errors

How our decisions impact our memories is not well understood. Reward prediction errors (RPEs), the difference between expected and obtained reward, help us learn to make optimal decisions-providing a signal that may influence subsequent memory. To measure this influence and how it might go awry in mood disorders, we recruited a large cohort of human participants to perform a decision-making task in which perceptually memorable stimuli were associated with probabilistic rewards, followed by a recognition test for those stimuli. Computational modeling revealed that positive RPEs enhanced both the accuracy of memory and the temporal efficiency of memory search, beyond the contribution of perceptual information. Critically, positive affect upregulated the beneficial effect of RPEs on memory. These findings demonstrate how affect selectively regulates the impact of RPEs on memory, providing a computational mechanism for biased memory in mood disorders.

Representational formats of human memory traces

Neural representations are internal brain states that constitute the brain's model of the external world or some of its features. In the presence of sensory input, a representation may reflect various properties of this input. When perceptual information is no longer available, the brain can still activate representations of previously experienced episodes due to the formation of memory traces. In this review, we aim at characterizing the nature of neural memory representations and how they can be assessed with cognitive neuroscience methods, mainly focusing on neuroimaging. We discuss how multivariate analysis techniques such as representational similarity analysis (RSA) and deep neural networks (DNNs) can be leveraged to gain insights into the structure of neural representations and their different representational formats. We provide several examples of recent studies which demonstrate that we are able to not only measure memory representations using RSA but are also able to investigate their multiple formats using DNNs. We demonstrate that in addition to slow generalization during consolidation, memory representations are subject to semantization already during short-term memory, by revealing a shift from visual to semantic format. In addition to perceptual and conceptual formats, we describe the impact of affective evaluations as an additional dimension of episodic memories. Overall, these studies illustrate how the analysis of neural representations may help us gain a deeper understanding of the nature of human memory.

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.

Emotional modulation of memorability in mnemonic discrimination

Although elements such as emotion may serve to enhance or impair memory for images, some images are consistently remembered or forgotten by most people, an intrinsic characteristic of images known as memorability. Memorability explains some of the variability in memory performance, however, the underlying mechanisms of memorability remain unclear. It is known that emotional valence can increase the memorability of an experience, but how these two elements interact is still unknown. Hippocampal pattern separation, a computation that orthogonalizes overlapping experiences as distinct from one another, may be a candidate mechanism underlying memorability. However, these two literatures have remained largely separate. To explore the interaction between image memorability and emotion on pattern separation, we examined performance on an emotional mnemonic discrimination task, a putative behavioral correlate of hippocampal pattern separation, by splitting stimuli into memorable and forgettable categories as determined by a convolutional neural network as well as by emotion, lure similarity, and time of testing (immediately and 24-hour delay). We measured target recognition, which is typically used to determine memorability scores, as well as lure discrimination, which taxes hippocampal pattern separation and has not yet been examined within a memorability framework. Here, we show that more memorable images were better remembered across both target recognition and lure discrimination measures. However, for target recognition, this was only true upon immediate testing, not after a 24-hour delay. For lure discrimination, we found that memorability interacts with lure similarity, but depends on the time of testing, where memorability primarily impacts high similarity lure discrimination when tested immediately but impacts low similarity lure discrimination after a 24-hour delay. Furthermore, only lure discrimination showed an interaction between emotion and memorability, in which forgettable neutral images showed better lure discrimination compared to more memorable images. These results suggest that careful consideration is required of what makes an image memorable and may depend on what aspects of the image are more memorable (e.g., gist vs. detail, emotional vs. neutral).

Novel Approaches to Studying SLC13A5 Disease

The role of the sodium citrate transporter (NaCT) SLC13A5 is multifaceted and context-dependent. While aberrant dysfunction leads to neonatal epilepsy, its therapeutic inhibition protects against metabolic disease. Notably, insights regarding the cellular and molecular mechanisms underlying these phenomena are limited due to the intricacy and complexity of the latent human physiology, which is poorly captured by existing animal models. This review explores innovative technologies aimed at bridging such a knowledge gap. First, I provide an overview of SLC13A5 variants in the context of human disease and the specific cell types where the expression of the transporter has been observed. Next, I discuss current technologies for generating patient-specific induced pluripotent stem cells (iPSCs) and their inherent advantages and limitations, followed by a summary of the methods for differentiating iPSCs into neurons, hepatocytes, and organoids. Finally, I explore the relevance of these cellular models as platforms for delving into the intricate molecular and cellular mechanisms underlying SLC13A5-related disorders.

Memory benefits when actively, rather than passively, viewing images

Serial visual presentations of images exist both in the laboratory and increasingly on virtual platforms such as social media feeds. However, the way we interact with information differs between these. In many laboratory experiments participants view stimuli passively, whereas on social media people tend to interact with information actively. This difference could influence the way information is remembered, which carries practical and theoretical implications. In the current study, 821 participants viewed streams containing seven landscape images that were presented at either a self-paced (active) or an automatic (passive) rate. Critically, the presentation speed in each automatic trial was matched to the speed of a self-paced trial for each participant. Both memory accuracy and memory confidence were greater on self-paced compared to automatic trials. These results indicate that active, self-paced progression through images increases the likelihood of them being remembered, relative to when participants have no control over presentation speed and duration.

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.

Memorable beginnings, but forgettable endings: Intrinsic memorability alters our subjective experience of time

Time is the fabric of experience - yet it is incredibly malleable in the mind of the observer: seeming to drag on, or fly right by at different moments. One of the most influential drivers of temporal distortions is attention, where heightened attention dilates subjective time. But an equally important feature of subjective experience involves not just the objects of attention, but also what information will naturally be remembered or forgotten, independent of attention (i.e. intrinsic image memorability). Here we test how memorability influences time perception. Observers viewed scenes in an oddball paradigm, where the last scene could be a forgettable "oddball" amidst memorable ones, or vice versa. Subjective time dilation occurred only for forgettable oddballs, but not memorable ones - demonstrating an oddball effect where the oddball did not differ in low-level visual features, image category, or even subjective memorability. But more importantly, these results emphasize how memory can interact with temporal experience: forgettable endings amidst memorable sequences dilate our experience of time.

Hippocampal Mechanisms Support Cortisol-Induced Memory Enhancements

Stress can powerfully influence episodic memory, often enhancing memory encoding for emotionally salient information. These stress-induced memory enhancements stand at odds with demonstrations that stress and the stress-related hormone cortisol can negatively affect the hippocampus, a brain region important for episodic memory encoding. To resolve this apparent conflict and determine whether and how the hippocampus supports memory encoding under cortisol, we combined behavioral assays of associative memory, high-resolution fMRI, and pharmacological manipulation of cortisol in a within-participant, double-blinded procedure (in both sexes). Behaviorally, hydrocortisone promoted the encoding of subjectively arousing, positive associative memories. Neurally, hydrocortisone led to enhanced functional connectivity between hippocampal subregions, which predicted subsequent memory enhancements for emotional associations. Cortisol also modified the relationship between hippocampal representations and associative memory: whereas hippocampal signatures of distinctiveness predicted memory under placebo, relative integration predicted memory under cortisol. Together, these data provide novel evidence that the human hippocampus contains the necessary machinery to support emotional associative memory enhancements under cortisol.SIGNIFICANCE STATEMENT Our daily lives are filled with stressful events, which powerfully shape the way we form episodic memories. For example, stress and stress-related hormones can enhance our memory for emotional events. However, the mechanisms underlying these memory benefits are unclear. In the current study, we combined functional neuroimaging, behavioral tests of memory, and double-blind, placebo-controlled hydrocortisone administration to uncover the effects of the stress-related hormone cortisol on the function of the human hippocampus, a brain region important for episodic memory. We identified novel ways in which cortisol can enhance hippocampal function to promote emotional memories, highlighting the adaptive role of cortisol in shaping memory formation.

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.

Symbol superiority: Why $ is better remembered than 'dollar'

Memory typically is better for information presented in picture format than in word format. Dual-coding theory (Paivio, 1969) proposes that this is because pictures are spontaneously labelled, leading to the creation of two representational codes-image and verbal-whereas words often lead to only a single (verbal) code. With this perspective as motivation, the present investigation asked whether common graphic symbols (e.g.,!@#$%&) are afforded primarily verbal coding, akin to words, or whether they also invoke visual imagery, as do pictures. Across four experiments, participants were presented at study with graphic symbols or words (e.g., $ or 'dollar'). In Experiment 1, memory was assessed using free recall; in Experiment 2, memory was assessed using old-new recognition. In Experiment 3, the word set was restricted to a single category. In Experiment 4, memory for graphic symbols, pictures, and words was directly compared. All four experiments demonstrated a memory benefit for symbols relative to words. In a fifth experiment, machine learning estimations of inherent stimulus memorability were found to predict memory performance in the earlier experiments. This study is the first to present evidence that, like pictures, graphic symbols are better remembered than words, in line with dual-coding theory and with a distinctiveness account. We reason that symbols offer a visual referent for abstract concepts that are otherwise unlikely to be spontaneously imaged.

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.

Memory for artwork is predictable

Viewing art is often seen as a highly personal and subjective experience. However, are there universal factors that make a work of art memorable? We conducted three experiments, where we recorded online memory performance for 4,021 paintings from the Art Institute of Chicago, tested in-person memory after an unconstrained visit to the Art Institute, and obtained abstract attribute measures such as beauty and emotional valence for these pieces. Participants showed significant agreement in their memories both online and in-person, suggesting that pieces have an intrinsic "memorability" based solely on their visual properties that is predictive of memory in a naturalistic museum setting. Importantly, ResMem, a deep learning neural network designed to estimate image memorability, could significantly predict memory both online and in-person based on the images alone, and these predictions could not be explained by other low- or high-level attributes like color, content type, aesthetics, and emotion. A regression comprising ResMem and other stimulus factors could predict as much as half of the variance of in-person memory performance. Further, ResMem could predict the fame of a piece, despite having no cultural or historical knowledge. These results suggest that perceptual features of a painting play a major role in influencing its success, both in memory for a museum visit and in cultural memory over generations.

Cortico-ocular Coupling in the Service of Episodic Memory Formation

Encoding of visual information is a necessary requirement for most types of episodic memories. In search for a neural signature of memory formation, amplitude modulation of neural activity has been repeatedly shown to correlate with and suggested to be functionally involved in successful memory encoding. We here report a complementary view on why and how brain activity relates to memory, indicating a functional role of cortico-ocular interactions for episodic memory formation. Recording simultaneous magnetoencephalography and eye tracking in 35 human participants, we demonstrate that gaze variability and amplitude modulations of alpha/beta oscillations (10-20Hz) in visual cortex covary and predict subsequent memory performance between and within participants. Amplitude variation during pre-stimulus baseline was associated with gaze direction variability, echoing the co-variation observed during scene encoding. We conclude that encoding of visual information engages unison coupling between oculomotor and visual areas in the service of memory formation.

Category-specific and category-general neural codes of recognition memory in the ventral visual pathway

Researchers have identified category-specific brain regions, such as the fusiform face area (FFA) and parahippocampal place area (PPA) in the ventral visual pathway, which respond preferentially to one particular category of visual objects. In addition to their category-specific role in visual object identification and categorization, regions in the ventral visual pathway play critical roles in recognition memory. Nevertheless, it is not clear whether the contributions of those brain regions to recognition memory are category-specific or category-general. To address this question, the present study adopted a subsequent memory paradigm and multivariate pattern analysis (MVPA) to explore category-specific and category-general neural codes of recognition memory in the visual pathway. The results revealed that the right FFA and the bilateral PPA showed category-specific neural patterns supporting recognition memory of faces and scenes, respectively. In contrast, the lateral occipital cortex seemed to carry category-general neural codes of recognition memory. These results provide neuroimaging evidence for category-specific and category-general neural mechanisms of recognition memory in the ventral visual pathway.

The features underlying the memorability of objects

What makes certain images more memorable than others? While much of memory research has focused on participant effects, recent studies using a stimulus-centric perspective have sparked debate on the determinants of memory, including the roles of semantic and visual features and whether the most prototypical or atypical items are best remembered. Prior studies have typically relied on constrained stimulus sets, limiting a generalized view of the features underlying what we remember. Here, we collected more than 1 million memory ratings for a naturalistic dataset of 26,107 object images designed to comprehensively sample concrete objects. We establish a model of object features that is predictive of image memorability and examined whether memorability could be accounted for by the typicality of the objects. We find that semantic features exert a stronger influence than perceptual features on what we remember and that the relationship between memorability and typicality is more complex than a simple positive or negative association alone.

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.

Identifying causal subsequent memory effects

Over 40 y of accumulated research has detailed associations between neuroimaging signals measured during a memory encoding task and later memory performance, across a variety of brain regions, measurement tools, statistical approaches, and behavioral tasks. But the interpretation of these subsequent memory effects (SMEs) remains unclear: if the identified signals reflect cognitive and neural mechanisms of memory encoding, then the underlying neural activity must be causally related to future memory. However, almost all previous SME analyses do not control for potential confounders of this causal interpretation, such as serial position and item effects. We collect a large fMRI dataset and use an experimental design and analysis approach that allows us to statistically adjust for nearly all known exogenous confounding variables. We find that, using standard approaches without adjustment, we replicate several univariate and multivariate subsequent memory effects and are able to predict memory performance across people. However, we are unable to identify any signal that reliably predicts subsequent memory after adjusting for confounding variables, bringing into doubt the causal status of these effects. We apply the same approach to subjects' judgments of learning collected following an encoding period and show that these behavioral measures of mnemonic status do predict memory after adjustments, suggesting that it is possible to measure signals near the time of encoding that reflect causal mechanisms but that existing neuroimaging measures, at least in our data, may not have the precision and specificity to do so.

Hippocampal mechanisms support cortisol-induced memory enhancements

Stress can powerfully influence episodic memory, often enhancing memory encoding for emotionally salient information. These stress-induced memory enhancements stand at odds with demonstrations that stress and the stress-related hormone cortisol can negatively affect the hippocampus, a brain region important for episodic memory encoding. To resolve this apparent conflict and determine whether and how the hippocampus supports memory encoding under cortisol, we combined behavioral assays of associative memory, high-resolution functional magnetic resonance imaging (fMRI), and pharmacological manipulation of cortisol in a within-participant, double-blinded procedure. Hydrocortisone led to enhanced functional connectivity between hippocampal subregions, which predicted subsequent memory enhancements for emotional information. Cortisol also modified the relationship between hippocampal representations and memory: whereas hippocampal signatures of distinctiveness predicted memory under placebo, relative integration predicted memory under cortisol. Together, these data provide novel evidence that the human hippocampus contains the necessary machinery to support emotional memory enhancements under stress.

Judgments of learning reveal conscious access to stimulus memorability

Despite the massive capacity of visual long-term memory, individuals do not successfully encode all visual information they wish to remember. This variability in encoding success has been traditionally ascribed to fluctuations in individuals' cognitive states (e.g., sustained attention) and differences in memory encoding processes (e.g., depth of encoding). However, recent work has shown that a considerable amount of variability in encoding success stems from intrinsic stimulus properties that determine the ease of encoding across individuals. While researchers have identified several perceptual and semantic properties that contribute to stimulus memorability, much remains unknown, including whether individuals are aware of the memorability of stimuli they encounter. In the present study, we investigated whether individuals have conscious access to the memorability of real-world stimuli while forming self-referential judgments of learning (JOL) during explicit memory encoding (Experiments 1A-B) and when asked about the perceived memorability of a stimulus in the absence of attempted encoding (Experiments 2A-B). We found that JOLs and perceived memorability estimates (PME) were consistent across individuals and predictive of memorability, confirming that individuals can access memorability with or without stimulus encoding. At the same time, access to memorability was not comprehensive. We found that individuals unexpectedly remembered and forgot consistent sets of stimuli as well. When we compared access to memorability between JOLs and PMEs, we found that individuals had more access during JOLs. Thus, our findings demonstrate that individuals have partial access to stimulus memorability and that explicit encoding increases the amount of access that is available.

Radiogenomics of C9orf72 Expansion Carriers Reveals Global Transposable Element Derepression and Enables Prediction of Thalamic Atrophy and Clinical Impairment

Hexanucleotide repeat expansion (HRE) within C9orf72 is the most common genetic cause of frontotemporal dementia (FTD). Thalamic atrophy occurs in both sporadic and familial FTD but is thought to distinctly affect HRE carriers. Separately, emerging evidence suggests widespread derepression of transposable elements (TEs) in the brain in several neurodegenerative diseases, including C9orf72 HRE-mediated FTD (C9-FTD). Whether TE activation can be measured in peripheral blood and how the reduction in peripheral C9orf72 expression observed in HRE carriers relates to atrophy and clinical impairment remain unknown. We used FreeSurfer software to assess the effects of C9orf72 HRE and clinical diagnosis (n = 78 individuals, male and female) on atrophy of thalamic nuclei. We also generated a novel, human, whole-blood RNA-sequencing dataset to determine the relationships among peripheral C9orf72 expression, TE activation, thalamic atrophy, and clinical severity (n = 114 individuals, male and female). We confirmed global thalamic atrophy and reduced C9orf72 expression in HRE carriers. Moreover, we identified disproportionate atrophy of the right mediodorsal lateral nucleus in HRE carriers and showed that C9orf72 expression associated with clinical severity, independent of thalamic atrophy. Strikingly, we found global peripheral activation of TEs, including the human endogenous LINE-1 element L1HS L1HS levels were associated with atrophy of multiple pulvinar nuclei, a thalamic region implicated in C9-FTD. Integration of peripheral transcriptomic and neuroimaging data from human HRE carriers revealed atrophy of specific thalamic nuclei, demonstrated that C9orf72 levels relate to clinical severity, and identified marked derepression of TEs, including L1HS, which predicted atrophy of FTD-relevant thalamic nuclei.SIGNIFICANCE STATEMENT Pathogenic repeat expansion in C9orf72 is the most frequent genetic cause of FTD and amyotrophic lateral sclerosis (ALS; C9-FTD/ALS). The clinical, neuroimaging, and pathologic features of C9-FTD/ALS are well characterized, whereas the intersections of transcriptomic dysregulation and brain structure remain largely unexplored. Herein, we used a novel radiogenomic approach to examine the relationship between peripheral blood transcriptomics and thalamic atrophy, a neuroimaging feature disproportionately impacted in C9-FTD/ALS. We confirmed reduction of C9orf72 in blood and found broad dysregulation of transposable elements-genetic elements typically repressed in the human genome-in symptomatic C9orf72 expansion carriers, which associated with atrophy of thalamic nuclei relevant to FTD. C9orf72 expression was also associated with clinical severity, suggesting that peripheral C9orf72 levels capture disease-relevant information.

Item memorability has no influence on value-based decisions

While making decisions, we often rely on past experiences to guide our choices. However, not all experiences are remembered equally well, and some elements of an experience are more memorable than others. Thus, the intrinsic memorability of past experiences may bias our decisions. Here, we hypothesized that individuals would tend to choose more memorable options than less memorable ones. We investigated the effect of item memorability on choice in two experiments. First, using food images, we found that the same items were consistently remembered, and others consistently forgotten, across participants. However, contrary to our hypothesis, we found that participants did not prefer or choose the more memorable over the less memorable items when choice options were matched for the individuals' valuation of the items. Second, we replicated these findings in an alternate stimulus domain, using words that described the same food items. These findings suggest that stimulus memorability does not play a significant role in determining choice based on subjective value.

The Visual Mandela Effect as Evidence for Shared and Specific False Memories Across People

The Mandela effect is an Internet phenomenon describing shared and consistent false memories for specific icons in popular culture. The visual Mandela effect is a Mandela effect specific to visual icons (e.g., the Monopoly Man is falsely remembered as having a monocle) and has not yet been empirically quantified or tested. In Experiment 1 (N = 100 adults), we demonstrated that certain images from popular iconography elicit consistent, specific false memories. In Experiment 2 (N = 60 adults), using eye-tracking-like methods, we found no attentional or visual differences that drive this phenomenon. There is no clear difference in the natural visual experience of these images (Experiment 3), and these errors also occur spontaneously during recall (Experiment 4; N = 50 adults). These results demonstrate that there are certain images for which people consistently make the same false-memory error, despite the majority of visual experience being the canonical image.

Predicting visual memory across images and within individuals

We only remember a fraction of what we see-including images that are highly memorable and those that we encounter during highly attentive states. However, most models of human memory disregard both an image's memorability and an individual's fluctuating attentional states. Here, we build the first model of memory synthesizing these two disparate factors to predict subsequent image recognition. We combine memorability scores of 1100 images (Experiment 1, n = 706) and attentional state indexed by response time on a continuous performance task (Experiments 2 and 3, n = 57 total). Image memorability and sustained attentional state explained significant variance in image memory, and a joint model of memory including both factors outperformed models including either factor alone. Furthermore, models including both factors successfully predicted memory in an out-of-sample group. Thus, building models based on individual- and image-specific factors allows for directed forecasting of our memories. SIGNIFICANCE STATEMENT: Although memory is a fundamental cognitive process, much of the time memory failures cannot be predicted until it is too late. However, in this study, we show that much of memory is surprisingly pre-determined ahead of time, by factors shared across the population and highly specific to each individual. Specifically, we build a new multidimensional model that predicts memory based just on the images a person sees and when they see them. This research synthesizes findings from disparate domains ranging from computer vision, attention, and memory into a predictive model. These findings have resounding implications for domains such as education, business, and marketing, where it is a top priority to predict (and even manipulate) what information people will remember.

Attention- versus significance-driven memory formation: Taxonomy, neural substrates, and meta-analyses

Functional neuroimaging data on episodic memory formation have expanded rapidly over the last 30 years, which raises the need for an integrative framework. This study proposes a taxonomy of episodic memory formation to address this need. At the broadest level, the taxonomy distinguishes between attention-driven vs. significance-driven memory formation. The three subtypes of attention-driven memory formation are selection-, fluctuation-, and level-related. The three subtypes of significance-driven memory formation are novelty-, emotion-, and reward-related. Meta-analytic data indicated that attention-driven memory formation affects the functioning of the extra-medial temporal lobe more strongly than the medial temporal lobe (MTL) regions. In contrast, significance-driven memory formation affects the functioning of the MTL more strongly than the extra-MTL regions. This study proposed a model in which attention has a stronger impact on the formation of neocortical traces than hippocampus/MTL traces, whereas significance has a stronger impact on the formation of hippocampus/MTL traces than neocortical traces. Overall, the taxonomy and model provide an integrative framework in which to place diverse encoding-related findings into a proper perspective.

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.

Neural signatures associated with temporal compression in the verbal retelling of past events

When we retell our past experiences, we aim to reproduce some version of the original events; this reproduced version is often temporally compressed relative to the original. However, it is currently unclear how this compression manifests in brain activity. One possibility is that a compressed retrieved memory manifests as a neural pattern which is more dissimilar to the original, relative to a more detailed or vivid memory. However, we argue that measuring raw dissimilarity alone is insufficient, as it confuses a variety of interesting and uninteresting changes. To address this problem, we examine brain pattern changes that are consistent across people. We show that temporal compression in individuals’ retelling of past events predicts systematic encoding-to-recall transformations in several higher associative regions. These findings elucidate how neural representations are not simply reactivated, but can also be transformed due to temporal compression during a universal form of human memory expression: verbal retelling.

Brain patterns measured while participants first watched a movie in the fMRI scanner, then recalled the movie’s key narrative features, demonstrate that temporal compression in individuals’ retelling of past events predicts encoding-to-recall transformations.

False memories when viewing overlapping scenes

Humans can memorize and later recognize many objects and complex scenes. In this study, we prepared large photographs and presented participants with only partial views to test the fidelity of their memories. The unpresented parts of the photographs were used as a source of distractors with similar semantic and perceptual information. Additionally, we presented overlapping views to determine whether the second presentation provided a memory advantage for later recognition tests. Experiment 1 (N = 28) showed that while people were good at recognizing presented content and identifying new foils, they showed a remarkable level of uncertainty about foils selected from the unseen parts of presented photographs (false alarm, 59%). The recognition accuracy was higher for the parts that were shown twice, irrespective of whether the same identical photograph was viewed twice or whether two photographs with overlapping content were observed. In Experiment 2 (N = 28), the memorability of the large image was estimated by a pre-trained deep neural network. Neither the recognition accuracy for an image part nor the tendency for false alarms correlated with the memorability. Finally, in Experiment 3 (N = 21), we repeated the experiment while measuring eye movements. Fixations were biased toward the center of the original large photograph in the first presentation, and this bias was repeated during the second presentation in both identical and overlapping views. Altogether, our experiments show that people recognize parts of remembered photographs, but they find it difficult to reject foils from unseen parts, suggesting that their memory representation is not sufficiently detailed to rule them out as distractors.

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.

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.

"Scene" from inside: The representation of Observer's space in high-level visual cortex

Human observers are remarkably adept at perceiving and interacting with visual stimuli around them. Compared to visual stimuli like objects or faces, scenes are unique in that they provide enclosures for observers. An observer looks at a scene by being physically inside the scene. The current research explored this unique observer-scene relationship by studying the neural representation of scenes' spatial boundaries. Previous studies hypothesized that scenes' boundaries were processed in sets of high-level visual cortices. Notably, the parahippocampal place area (PPA), exhibited neural sensitivity to scenes that had closed vs. open spatial boundaries (Kravitz et al., 2011; Park et al., 2011). We asked whether this sensitivity reflected the openness of landscape (e.g., forest vs. beach), or the openness of the environment immediately surrounding the observer (i.e., whether a scene was viewed from inside vs. outside a room). Across two human fMRI experiments, we found that the PPA, as well as another well-known navigation-processing area, the occipital place area (OPA), processed scenes' boundaries according to the observer's space rather than the landscape. Moreover, we found that the PPA's activation pattern was susceptible to manipulations involving mid-level perceptual properties of scenes (e.g., rectilinear pattern of window frames), while the OPA's response was not. Our results have important implications for research in visual scene processing and suggest an important role of an observer's location in representing the spatial boundary, beyond the low-level visual input of a landscape.

Content-specific vulnerability of recent episodic memories in Alzheimer's disease

Endel Tulving's episodic memory framework emphasizes the multifaceted re-experiencing of personal events. Indeed, decades of research focused on the experiential nature of episodic memories, usually treating recent episodic memory as a coherent experiential quality. However, recent insights into the functional architecture of the medial temporal lobe show that different types of mnemonic information are segregated into distinct neural pathways in brain circuits empirically associated with episodic memory. Moreover, recent memories do not fade as a whole under conditions of progressive neurodegeneration in these brain circuits, notably in Alzheimer's disease. Instead, certain memory content seem particularly vulnerable from the moment of their encoding while other content can remain memorable consistently across individuals and contexts. We propose that these observations are related to the content-specific functional architecture of the medial temporal lobe and consequently to a content-specific impairment of memory at different stages of the neurodegeneration. To develop Endel Tulving's inspirational legacy further and to advance our understanding of how memory function is affected by neurodegenerative conditions such as Alzheimer's disease, we postulate that it is compelling to focus on the representational content of recent episodic memories.

•

The functional anatomy of episodic memory segregates different memory content.

•

Alzheimer's disease may cause content-specific loss of recent memories

•

Content-specific memorability across individuals changes with Alzheimer's disease.

•

Content-specific assessment could provide new insights into episodic memory in health and disease

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

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.

Image memorability is predicted by discriminability and similarity in different stages of a convolutional neural network

The features of an image can be represented at multiple levels-from its low-level visual properties to high-level meaning. What drives some images to be memorable while others are forgettable? We address this question across two behavioral experiments. In the first, different layers of a convolutional neural network (CNN), which represent progressively higher levels of features, were used to select the images that would be shown to 100 participants through a form of prospective assignment. Here, the discriminability/similarity of an image with others, according to different CNN layers dictated the images presented to different groups, who made a simple indoor versus outdoor judgment for each scene. We found that participants remember more scene images that were selected based on their low-level discriminability or high-level similarity. A second experiment replicated these results in an independent sample of 50 participants, with a different order of postencoding tasks. Together, these experiments provide evidence that both discriminability and similarity, at different visual levels, predict image memorability.

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.

Memorability of words in arbitrary verbal associations modulates memory retrieval in the anterior temporal lobe

Despite large individual differences in memory performance, people remember certain stimuli with overwhelming consistency. This phenomenon is referred to as the memorability of an individual item. However, it remains unknown whether memorability also affects our ability to retrieve associations between items. Here, using a paired-associates verbal memory task, we combine behavioural data, computational modelling and direct recordings from the human brain to examine how memorability influences associative memory retrieval. We find that certain words are correctly retrieved across participants irrespective of the cues used to initiate memory retrieval. These words, which share greater semantic similarity with other words, are more readily available during retrieval and lead to more intrusions when retrieval fails. Successful retrieval of these memorable items, relative to less memorable ones, results in faster reinstatement of neural activity in the anterior temporal lobe. Collectively, our data reveal how the brain prioritizes certain information to facilitate memory retrieval.