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.

Tuning intrinsic disorder predictors for virus proteins.

Many virus-encoded proteins have intrinsically disordered regions that lack a stable, folded three-dimensional structure. These disordered proteins often play important functional roles in virus replication, such as down-regulating host defense mechanisms. With the widespread availability of next-generation sequencing, the number of new virus genomes with predicted open reading frames is rapidly outpacing our capacity for directly characterizing protein structures through crystallography. Hence, computational methods for structural prediction play an important role. A large number of predictors focus on the problem of classifying residues into ordered and disordered regions, and these methods tend to be validated on a diverse training set of proteins from eukaryotes, prokaryotes, and viruses. In this study, we investigate whether some predictors outperform others in the context of virus proteins and compared our findings with data from non-viral proteins. We evaluate the prediction accuracy of 21 methods, many of which are only available as web applications, on a curated set of 126 proteins encoded by viruses. Furthermore, we apply a random forest classifier to these predictor outputs. Based on cross-validation experiments, this ensemble approach confers a substantial improvement in accuracy, e.g., a mean 36 per cent gain in Matthews correlation coefficient. Lastly, we apply the random forest predictor to severe acute respiratory syndrome coronavirus 2 ORF6, an accessory gene that encodes a short (61 AA) and moderately disordered protein that inhibits the host innate immune response. We show that disorder prediction methods perform differently for viral and non-viral proteins, and that an ensemble approach can yield more robust and accurate predictions.