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Through the process of "reconsolidation," reminders can temporarily destabilize memories and render them vulnerable to change. Recent rodent research has proposed that prediction error, or the element of surprise, is a key component of this process; yet, this hypothesis has never before been extended to complex episodic memories in humans. In our novel paradigm, we used naturalistic stimuli to demonstrate that prediction error enables adaptive updating of episodic memories. In Study 1, participants ( = 48) viewed 18 videos, each depicting an action-outcome event. The next day, we reactivated these memories by presenting the videos again. We found that incomplete reminders, which interrupted videos before the outcome, made memories vulnerable to subsequent interference from a new set of videos, producing false memories. In Study 2 ( = 408), an independent sample rated qualities of the stimuli. We found that videos that were more surprising when interrupted produced more false memories. Last, in Study 3 ( = 24), we tested competing predictions of reconsolidation theory and the Temporal Context Model, an alternative account of source confusion. Consistent with the mechanistic time-course of reconsolidation, our effects were crucially time-dependent. Overall, we synthesize prior animal and human research to present compelling evidence that prediction error destabilizes episodic memories and drives dynamic updating in the face of new information.

The COVID-19 pandemic reached staggering new peaks during an ongoing global resurgence at the end of 2020. Although public health guidelines initially helped to slow the spread of disease, widespread pandemic fatigue and prolonged harm to financial stability and mental wellbeing have contributed to this resurgence. In this late stage of the pandemic, it is clear that new interventions are needed to support long-term behavior change. Here, we examined subjective perceived risk about COVID-19, and the relationship between perceived risk and engagement in risky behaviors. In Study 1 (N = 303), we found that subjective perceived risk is inaccurate but predicts compliance with public health guidelines. In Study 2 (N = 760), we developed a multi-faceted intervention designed to realign perceived risk with actual risk. Participants completed one of three variants of an episodic simulation task; we expected that imagining a COVID-related scenario would increase the salience of risk information and enhance behavior change. Immediately following the episodic simulation, participants completed a risk estimation task with personalized feedback about local risk levels. We found that information prediction error, a measure of surprise, drove beneficial change in perceived risk and willingness to engage in risky activities. Imagining a COVID-related scenario beforehand enhanced the effect of prediction error on learning. Importantly, our intervention produced lasting effects that persisted after a 1-3 week delay. Overall, we describe a fast and feasible online intervention that effectively changed beliefs and intentions about risky behaviors.

The COVID-19 pandemic reached staggering new peaks during a global resurgence more than a year after the crisis began. Although public health guidelines initially helped to slow the spread of disease, widespread pandemic fatigue and prolonged harm to financial stability and mental well-being contributed to this resurgence. In the late stage of the pandemic, it became clear that new interventions were needed to support long-term behavior change. Here, we examined subjective perceived risk about COVID-19 and the relationship between perceived risk and engagement in risky behaviors. In study 1 (n = 303), we found that subjective perceived risk was likely inaccurate but predicted compliance with public health guidelines. In study 2 (n = 735), we developed a multifaceted intervention designed to realign perceived risk with actual risk. Participants completed an episodic simulation task; we expected that imagining a COVID-related scenario would increase the salience of risk information and enhance behavior change. Immediately following the episodic simulation, participants completed a risk estimation task with individualized feedback about local viral prevalence. We found that information prediction error, a measure of surprise, drove beneficial change in perceived risk and willingness to engage in risky activities. Imagining a COVID-related scenario beforehand enhanced the effect of prediction error on learning. Importantly, our intervention produced lasting effects that persisted after a 1- to 3-wk delay. Overall, we describe a fast and feasible online intervention that effectively changed beliefs and intentions about risky behaviors.

Objective: Intellectual humility (IH) refers to the recognition that personal beliefs might be wrong. We investigate possible interpersonal implications of IH for how people perceive the intellectual capabilities and moral character of their sociopolitical opponents and for their willingness to associate with those opponents. Method: In four initial studies (N = 1,926, M age = 38, 880 females, 1,035 males), we measured IH, intellectual and moral derogation of opponents, and willingness to befriend opponents. In two additional studies (N = 568, M age = 40, 252 females, 314 males), we presented participants with a specific opponent on certain sociopolitical issues and several social media posts from that opponent in which he expressed his views on the issue. We then measured IH, intellectual, and moral derogation of the opponent, participants' willingness to befriend the opponent, participants' willingness to "friend" the opponent on social media, and participants' willingness to "follow" the opponent on social media. Results: Low-IH relative to high-IH participants were more likely to derogate the intellectual capabilities and moral character of their opponents, less willing to befriend their opponents, and less willing to "friend" and "follow" an opponent on social media. Conclusions: IH may have important interpersonal implications for person perception, and for understanding social extremism and polarization.

The brain supports adaptive behavior by generating predictions, learning from errors, and updating memories to incorporate new information. Prediction error, or surprise, triggers learning when reality contradicts expectations. Prior studies have shown that the hippocampus signals prediction errors, but the hypothesized link to memory updating has not been demonstrated. In a human functional MRI study, we elicited mnemonic prediction errors by interrupting familiar narrative videos immediately before the expected endings. We found that prediction errors reversed the relationship between univariate hippocampal activation and memory: greater hippocampal activation predicted memory preservation after expected endings, but memory updating after surprising endings. In contrast to previous studies, we show that univariate activation was insufficient for understanding hippocampal prediction error signals. We explain this surprising finding by tracking both the evolution of hippocampal activation patterns and the connectivity between the hippocampus and neuromodulatory regions. We found that hippocampal activation patterns stabilized as each narrative episode unfolded, suggesting sustained episodic representations. Prediction errors disrupted these sustained representations and the degree of disruption predicted memory updating. The relationship between hippocampal activation and subsequent memory depended on concurrent basal forebrain activation, supporting the idea that cholinergic modulation regulates attention and memory. We conclude that prediction errors create conditions that favor memory updating, prompting the hippocampus to abandon ongoing predictions and make memories malleable.

When confronted with information that challenges our beliefs, we must often learn from error in order to successfully navigate the world. Past studies in reinforcement learning and educational psychology have linked prediction error, a measure of surprise, to successful learning from feedback. However, there are substantial individual differences in belief-updating success, and the psychological factors that influence belief updating remain unclear. Here, we identify a novel factor that may predict belief updating: right-wing authoritarianism (RWA), which is characterized by a desire for order, structure, and preservation of social norms. We hypothesized that because people who score high on RWA are motivated to preserve entrenched beliefs, they may often fail to successfully update their beliefs when confronted with new information. Using a novel paradigm, we challenged participants' false beliefs and misconceptions to elicit prediction error. In two studies, we found consistent evidence that high-RWA individuals were less successful at correcting their false beliefs. Relative to low-RWA individuals, high-RWA individuals were less likely to revise beliefs in response to prediction error. We argue that RWA is associated with a relatively closed-minded cognitive style that negatively influences belief updating.

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