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Much of the information people encounter in everyday life is not factual; it originates from fictional sources, such as movies, novels, and video games, and from direct experience such as pretense, role-playing, and everyday conversation. Despite the recent increase in research on fiction, there is no theoretical account of how memory of fictional information is related to other types of memory or of which mechanisms allow people to separate fact and fiction in memory. We present a theoretical framework that places memory of fiction in relation to other cognitive phenomena as a distinct construct and argue that it is an essential component for any general theory of human memory. We show how fictionality can be integrated in an existing memory model by extending Rubin's dimensional conceptual memory model. By this means, our model can account for explicit and implicit memory of fictional information of events, places, characters, and objects. Further, we propose a set of mechanisms involving various degrees of complexity and levels of conscious processing that mostly keep fact and fiction separated but also allow information from fiction to influence real-world attitudes and beliefs: content-based reasoning, source monitoring, and an associative link from the memory to the concept of fiction.

Fictionality and fictional experiences are ubiquitous in people's everyday lives in the forms of movies, novels, video games, pretense and role playing, and digital technology use. Despite this ubiquity, though, the field of cognitive science has traditionally been dominated by a focus on the real world. Based on the limited understanding from previous research on questions regarding fictional information and the cognitive processes for distinguishing reality from fiction, we argue for the need for a comprehensive and systematic account that reflects on related phenomena, such as narrative comprehension or imagination embedded into general theories of cognition. This is important as incorporating cognitive processing of fictional events into memory theory reshapes the conceptual map of human memory. In this paper, we highlight future challenges for the cognitive studies of fictionality on conceptual, neurological, and computational levels. Taking on these challenges requires an interdisciplinary approach between fields like developmental psychology, philosophy, and the study of narrative comprehension. Our aim is to build on such interdisciplinarity and provide conclusions on the ways in which new theoretical frameworks of fiction cognition can aid understanding human behaviors in a wide range of aspects of people's daily lives, media consumption habits, and digital encounters. Our account also has the potential to inform technological innovations related to training intelligent digital systems to distinguish fact and fiction in the source material., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Gander, Szita, Falck and Thompson.)

It has long been known that one of the most effective study techniques is to be tested on the to-be-remembered material, a phenomenon known as the testing effect. Recent research has also shown that testing of previous materials promotes the learning of new materials, a phenomenon known as the forward testing effect. In this paper, as of yet unexplored aspects of the forward testing effect related to face-name learning are examined; continuous and initial testing are compared to restudying, the effects of an initial test on subsequent learning, and whether an initial change of domain (change from one topic to another) regarding study material affects the robustness of the effect. An experiment (N = 94) was performed according to a 2 (Material: word pairs/face-name pairs in Block 1) × 3 (Test occasions: Blocks 1-4/Blocks 1 and 4/Block 4) complex between-groups design. The results showed that no difference between testing and repetition could be observed regarding the recall of faces and names. The restudy groups incorrectly recalled more names from previous lists in the last interim test compared to the tested groups, which supports the theory that interim tests reduce proactive interference. The results also suggest that the number of test occasions correlates with the number of incorrect recalls from previous lists. These results, in contrast to previous studies, highlight a potential uncertainty about the forward testing effect linked to the robustness of the phenomenon, the specificity in execution, and generalizability.

This article adapts an existing experimental protocol for assessing individuals' ability to transfer knowledge across instrumental and pavlovian learning stages. The protocol ( Transfer of Control using differential outcomes learning) is adapted to fit social contexts wherein the pavlovian learning phase is modulated so that individuals are able to observe, and potentially learn from, the stimulus associated with reinforcing outcomes presented to another (observable) individual. Transfer of Control concerns participants combining knowledge of learned instrumental and pavlovian (stimulus, response, outcome) associations in order to ground the learning of new associations. The article describes the theoretical and procedural underpinnings of a novel Social Transfer of Control methodology. The use of such a methodology is two-fold: i) to serve as a guide to researchers interested in evaluating how individuals can learn from others in a partially observable setting, i.e. when behavioural and reinforcing outcome information is hidden, and bring to bear this knowledge on their own instrumental decision making; ii), to facilitate investigation of the routes of cognitive and emotional empathy, with potential applications for educational and clinical settings.•Three stage Transfer of Control behavioural methodology is adapted to include a social (pavlovian) learning stage.•Hypotheses can be tested that concern learning rewarding instrumental responses achieved by observation of others' emotionally expressive reactions to differentially rewarding outcomes.•Methodological and validation considerations for evaluating the above are presented., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2021 The Authors.)

This article contains performance data, questionnaire ratings, and EEG data from a differential outcomes learning task from two experiments. In both experiments, the standard differential outcomes learning task was extended to involve a social dimension, in order to capture how people can learn from others by observation. In Experiment 1 ( N  = 20), using a within-subjects design, participants learned pairings of image stimuli in four conditions: 1) individual-differential outcomes, 2) individual-non-differential outcomes, 3) social-differential outcomes, and 4) social-non-differential outcomes. The social condition had a screen-captured video recording of the outcomes (but not the actions themselves) of another person performing the task. During the task, the performance of the participants was measured. After the task, participants rated their experience in a questionnaire. The procedure for Experiment 2 ( N  = 33) was similar to Experiment 1, but with a stronger social manipulation using a video of another person's face showing facial expressions reflecting the outcomes. In addition, EEG was measured while performing the task. For more insight, please see Vicarious value learning: Knowledge transfer through affective processing on a social differential outcomes task (Rittmo et al., 2020)., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships which have, or could be perceived to have, influenced the work reported in this article., (© 2020 The Author(s).)

The findings of differential outcomes training procedures in controlled stimulus-response learning settings have been explained through theorizing two processes of response control. These processes concern: i) a stimulus-response route, and, ii) an outcome expectancy route through which valuations of stimuli (typically auditory or visual) may be represented. Critically, under certain contingencies of learning, the interaction of these two processes enables a transfer of knowledge. Transfer is hypothesized to occur via implicit inference for response selection given novel stimulus-response pairings. In this article, we test this transfer of knowledge, previously only examined in individual settings, in novel social settings. We find that participants are able to achieve transfer of knowledge and suggest they achieve this through vicariously learning the differential valuations of stimuli made by the (confederate) 'other' involved in the task. We test this effect under two experimental conditions through manipulation of the information made available to participants observing the confederate other's choices. The results of EEG recordings are, additionally, evaluated and discussed in the context of social signalling and emotional and cognitive empathy. We also consider implications for clinical and technological social learning settings., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Joint Action is typically described as social interaction that requires coordination among two or more co-actors in order to achieve a common goal. In this article, we put forward a hypothesis for the existence of a neural-computational mechanism of affective valuation that may be critically exploited in Joint Action. Such a mechanism would serve to facilitate coordination between co-actors permitting a reduction of required information. Our hypothesized affective mechanism provides a value function based implementation of Associative Two-Process (ATP) theory that entails the classification of external stimuli according to outcome expectancies. This approach has been used to describe animal and human action that concerns differential outcome expectancies. Until now it has not been applied to social interaction. We describe our Affective ATP model as applied to social learning consistent with an "extended common currency" perspective in the social neuroscience literature. We contrast this to an alternative mechanism that provides an example implementation of the so-called social-specific value perspective. In brief, our Social-Affective ATP mechanism builds upon established formalisms for reinforcement learning (temporal difference learning models) nuanced to accommodate expectations (consistent with ATP theory) and extended to integrate non-social and social cues for use in Joint Action.