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The directed forgetting paradigm has long been used to test whether humans can voluntarily choose to forget learned information. However, to date, nearly all directed forgetting paradigms have involved a forced-choice paradigm, in which the participants are instructed about which learned information they should forget. While studies have repeatedly shown that this directed forgetting does lead to a decreased ability to later remember the information, it is still unclear whether these effects would be present if participants were allowed to, of their own accord, choose which information they wanted to forget. In two experiments here, we introduce a free-choice variety of the item method directed forgetting paradigm and show that directed forgetting effects are robust, both for instructed and voluntary forgetting. We discuss the implications of our findings for notions of voluntary forgetting and for the self-choice effect in memory.

It is commonly assumed that the rate of forgetting depends on initial degree of learning. Hence, comparison of forgetting across groups is usually carried out equating initial performance. However, these matching procedures add confounding variables. In four experiments, following Slamecka and McElree ( 1983 , Exp 3), we challenge this assumption through manipulating initial acquisition by varying the number of presentations of the material and studying the effect on rate of subsequent forgetting. A set of 36 sentences was presented either visually or auditorily. Different participants were exposed to the material two, four or six times. Forgetting was measured by means of a cued recall test at three time-intervals (30 s, 1 day and 1 week in experiments 1 and 2 ; 30 s, 1 day, and 3 days in experiments 3 and 4 ). A different subset of 12 sentences was tested at each delay. The outcome of these experiments showed that the initial acquisition depends on number of learning trials. However, the rate of forgetting proved to be independent of initial acquisition. This pattern remains constant across modalities of presentation and of the number of learning trials. The conclusion is that forgetting does not depend on initial acquisition.

As a special case of machine learning, incremental learning can acquire useful knowledge from incoming data continuously while it does not need to access the original data. It is expected to have the ability of memorization and it is regarded as one of the ultimate goals of artificial intelligence technology. However, incremental learning remains a long term challenge. Modern deep neural network models achieve outstanding performance on stationary data distributions with batch training. This restriction leads to catastrophic forgetting for incremental learning scenarios since the distribution of incoming data is unknown and has a highly different probability from the old data. Therefore, a model must be both plastic to acquire new knowledge and stable to consolidate existing knowledge. This review aims to draw a systematic review of the state of the art of incremental learning methods. Published reports are selected from Web of Science, IEEEXplore, and DBLP databases up to May 2020. Each paper is reviewed according to the types: architectural strategy, regularization strategy and rehearsal and pseudo-rehearsal strategy. We compare and discuss different methods. Moreover, the development trend and research focus are given. It is concluded that incremental learning is still a hot research area and will be for a long period. More attention should be paid to the exploration of both biological systems and computational models.

INTRODUCTION Accelerated long‐term forgetting (LTF) might be an early marker of subtle memory changes in older adults at risk for Alzheimer's disease (AD). We leveraged remote, multi‐day digital testing to characterize LTF in older adults and investigated its association with initial learning and AD imaging biomarkers. METHODS One hundred four cognitively unimpaired older adults completed a face–name memory task for seven consecutive days and were asked to recognize face–name pairs 1 week later. LTF was computed as the number of correctly identified stimuli divided by a participant's maximum performance during learning. RESULTS Better learning was associated with less LTF (β = 0.52, 95% confidence interval [CI]:0.34–0.71, p < 0.001). Accelerated LTF was associated with cortical thinning in AD‐signature regions (β = 0.33, 95% CI: 0.13–0.52, p = 0.001), but associations with regional tau were more subtle. DISCUSSION Remote, multi‐day testing may facilitate the assessment of LTF as an early cognitive marker of preclinical AD, but further replication is needed. Highlights Using digital, remote assessments, we evaluated long‐term forgetting in cognitively unimpaired older adults. We found a potential association between long‐term forgetting and tau in Alzheimer's disease (AD)–related regions. Assessing long‐term forgetting may facilitate early detection of AD‐related cognitive decline.

Recognition-induced forgetting is a within-category forgetting effect that results from accessing memory representations. Advantages of this paradigm include the possibility of testing the memory of young children using visual objects before they can read, the testing of multiple types of stimuli, and use with animal models. Yet it is unknown whether just episodic memory tasks (Have you seen this before?) or also semantic memory tasks (Is this bigger than a loaf of bread?) will lead to this forgetting effect. This distinction will be critical in establishing a model of recognition-induced forgetting. Here, we implemented a design in which both these tasks were used in the same experiment to determine which was leading to recognition-induced forgetting. We found that episodic memory tasks, but not semantic memory tasks, created within-category forgetting. These results show that the difference-of-Gaussian forgetting function of recognition-induced forgetting is triggered by episodic memory tasks and is not driven by the same underlying memory signal as semantic memory.

The Think/No-Think (TNT) task has just celebrated 20 years since its inception, and its use has been growing as a tool to investigate the mechanisms underlying memory control and its neural underpinnings. Here, we present a theoretical and practical guide for designing, implementing, and running TNT studies. For this purpose, we provide a step-by-step description of the structure of the TNT task, methodological choices that can be made, parameters that can be chosen, instruments available, aspects to be aware of, systematic information about how to run a study and analyze the data. Importantly, we provide a TNT training package (as Supplementary Material), that is, a series of multimedia materials (e.g., tutorial videos, informative HTML pages, MATLAB code to run experiments, questionnaires, scoring sheets, etc.) to complement this method paper and facilitate a deeper understanding of the TNT task, its rationale, and how to set it up in practice. Given the recent discussion about the replication crisis in the behavioral sciences, we hope that this contribution will increase standardization, reliability, and replicability across laboratories.

Humans are constantly acquiring new information and skills. However, forgetting is also a common phenomenon in our lives. Understanding the lability of memories is critical to appreciate how they are formed as well as forgotten. Here we investigate the lability of chimpanzees' short-term memories and assess what factors cause forgetting in our closest relatives. In two experiments, chimpanzees were presented with a target task, which involved remembering a reward location, followed by the presentation of an interference task-requiring the recollection of a different reward location. The interference task could take place soon after the presentation of the target task or soon before the retrieval of the food locations. The results show that chimpanzees' memories for the location of a reward in a target task were compromised by the presentation of a different food location in an interference task. Critically, the temporal location of the interference task did not significantly affect chimpanzees' performance. These pattern of results were found for both Experiment 1-when the retention interval between the encoding and retrieval of the target task was 60 seconds- and Experiment 2-when the retention interval between the encoding and retrieval of the target task was 30 seconds. We argue that the temporal proximity of the to-be-remembered information and the interference item during encoding is the factor driving chimpanzees' performance in the present studies.

The world of literature. Memory - Forgetting - Reminiscence

Intentional forgetting is significantly effective for forgetting unwanted non-emotional material. However, whether the suppressive effect of unaided suppression differs from that of substitution forgetting when applied to negative materials by remitted depressed individuals is unclear. A modified think/no-think (TNT) emotional paradigm including specific strategies (unaided suppression, positive-word substitution, and positive-picture substitution) was used with 84 remitted depressed individuals and 80 controls. The participants in both groups forgot more negative words in the substitution condition than in the unaided condition. The remitted participants forgot more with positive-picture substitution than with positive-word substitution, while the controls showed no difference. Moreover, the participants in both groups forgot more with 0 cue presentations (incidental forgetting) than under any other experimental condition. These results indicate that unaided suppression of negative material in the TNT paradigm shows little suppressive effect. Incidental forgetting and positive-picture substitution forgetting may be better strategies for remitted depressed individuals to forget negative materials.

The memory of our brain, stored in soft matter, is dynamic, and it forgets spontaneously to filter unimportant information. By contrast, the existing manmade memory, made from hard materials, is static, and it does not forget without external stimuli. Here we propose a principle for developing dynamic memory from soft hydrogels with temperature-sensitive dynamic bonds. The memorizing–forgetting behavior is achieved based on fast water uptake and slow water release upon thermal stimulus, as well as thermal-history-dependent transparency change of these gels. The forgetting time is proportional to the thermal learning time, in analogy to the behavior of brain. The memory is stable against temperature fluctuation and large stretching; moreover, the forgetting process is programmable. This principle may inspire future research on dynamic memory based on the nonequilibrium process of soft matter.