Memory Bias Research Articles

Partisan bias in false memories for misinformation about the 2021 U.S. Capitol riot

ABSTRACT Memory for events can be biased. For example, people tend to recall more events that support than oppose their current worldview. The present study examined partisan bias in memory for events related to the January 6, 2021, Capitol riot in the United States. Participants rated their memory for true and false events that were either favourable to their political party or the other major political party in the United States. For both true and false events, participants remembered more events that favoured their political party. Regression analyses showed that the number of false memories that participants reported was positively associated with their tendency to support conspiracy beliefs and with their self-reported engagement with the Capitol riot. These results suggest that Democrats and Republicans remember the Capitol Riot differently and that certain individual difference factors can predict the formation of false memories in this context. Misinformation played an influential role in the Capitol riot and understanding differences in memory for this event is beneficial to avoiding similar tragedies in the future.

The role of progesterone in memory bias during spatial navigation in females.

Rats can use several memory systems to navigate a maze toward a reward. Two of these are place memory and response memory and female rats can be biased to predominantly use one over another. Both progesterone and estrogens have been shown to alter memory bias. Although the effects of estrogens have been well documented, the effects of progesterone remain somewhat unexplored. Mechanisms through which progesterone may be acting to exert its effects are reviewed here. Converging evidence suggests that the actions of progesterone differ depending on the presence of estrogens, frequently acting in opposition to estrogens when administered together. The hippocampus, dorsal striatum, and prefrontal cortex are likely involved, as is the progesterone metabolite, allopregnanolone. There is a need for more research on progesterone and memory bias, especially considering current formulations of hormonal contraceptives include progestins.

The relation between children's attention bias to pain and children's pain-related memory biases is moderated by parental narrative style

Children's heightened attention to pain and parental narrative style have been linked to the development of negatively-biased pain memories in children (i.e., recalling higher levels of pain and fear than initially reported, which robustly predicts maladaptive pain outcomes). However, the interplay between child attention bias and parental narrative style remains to be assessed. This study aims to fill this gap using enhanced paradigms assessing children's cognitive biases for cues signaling actual pain. Healthy school children (N = 63; 9–15 years old) received painful heat stimuli while performing a spatial cueing task measuring attention bias to cues signaling actual pain. Parent-child interaction upon completion of the painful task, was coded for parental narrative style (i.e., elaboration, repetition and evaluation). Children's pain-related memories were elicited two weeks later. Findings indicated that children showed an attention bias to cues signaling pain. Furthermore, children who were hypervigilant to pain cues benefitted from parents elaborating more about the pain experience, while children who avoided pain cues developed more negatively-biased pain memories if parents had a more elaborative style compared to a more evaluative parental style. In conclusion, this study suggests that optimal ways to talk about children's pain depend upon child characteristics (i.e., children's attention bias to pain).

Smartphone use and daily cognitive failures: A critical examination using a daily diary approach with objective smartphone measures.

While smartphones have brought many benefits and conveniences to users, there is continuing debate regarding their potential negative consequences on everyday cognition such as daily cognitive failures. A few cross-sectional studies have found positive associations between smartphone use and cognitive failures. However, several research gaps remain, such as the use of cross-sectional designs, confounds related to stable individual differences, the lack of validity in self-report measures of smartphone use, memory biases in retrospective self-reports, and the lack of differentiation between smartphone checking and smartphone screen time. To simultaneously address the aforementioned shortcomings, the current study examined the within-person associations between various objective indicators of smartphone use and daily cognitive failures using a 7-day daily diary study. Multilevel modelling revealed that smartphone checking, but not total smartphone screen time, predicted a greater occurrence of daily cognitive failures at the within-person level. Surprisingly, we also found negative within-person associations between smartphone screen time for social- and tools-related applications and daily cognitive failures, suggesting that some types of smartphone use may temporarily benefit one's cognitive functioning. This finding demonstrates the importance of studying the specific functions of smartphone use and their differential cognitive consequences, as well as highlights the complex relations between smartphone use and cognition.

How state anxiety influences retrospective time perception: the moderated mediation of perceived control and memory bias

ABSTRACT This study aims to explore how individuals retrospectively perceive time when they are anxious. In Experiment 1, state anxiety (high and low) was induced by a standardised induction procedure, and retrospective time perception was measured using a visual analogue mood scale. In Experiment 2, memory bias and perceived control were tested as the underlying mechanisms of the effect of state anxiety on retrospective time perception. The results suggest that (1) individuals with high state anxiety retrospectively perceive the duration to be longer than individuals with low state anxiety; (2) memory bias mediates the effect of state anxiety on retrospective time perception; and (3) perceived control moderates the mediating effect of memory bias on the relationship between state anxiety and retrospective time perception. Our findings provide a comprehensive model for the mechanisms underlying time inaccuracy in individuals with anxiety and illustrate the important role of perceived control in the process.

Perceptual comparisons modulate memory biases induced by new visual inputs.

It is well-established that stimulus-specific information in visual working memory (VWM) can be systematically biased by new perceptual inputs. These memory biases are commonly attributed to interference that arises when perceptual inputs are physically similar to VWM contents. However, recent work has suggested that explicitly comparing the similarity between VWM contents and new perceptual inputs modulates the size of memory biases above and beyond stimulus-driven effects. Here, we sought to directly investigate this modulation hypothesis by comparing the size of memory biases following explicit comparisons to those induced when new perceptual inputs are ignored (Experiment 1) or maintained in VWM alongside target information (Experiment 2). We found that VWM reports showed larger attraction biases following explicit perceptual comparisons than when new perceptual inputs were ignored or maintained in VWM. An analysis of participants' perceptual comparisons revealed that memory biases were amplified after perceptual inputs were endorsed as similar-but not dissimilar-to one's VWM representation. These patterns were found to persist even after accounting for variability in the physical similarity between the target and perceptual stimuli across trials, as well as the baseline memory precision between the distinct task demands. Together, these findings illustrate a causal role of perceptual comparisons in modulating naturally-occurring memory biases.

The Role of Working Memory in Age-Related Emotional Memory Bias

Aging is accompanied by deterioration in both working memory (WM) and long-term memory (LTM), yet whether these changes are related is not understood. Sleep plays a role in the formation of LTM in young adults, but the findings in older adults are not as clear. The types of memories we store also shift with age as young adults preserve a higher proportion of negative experiences when compared to older adults. The reason for this age-related change in emotional memory bias is also not clear; however, some studies have suggested that WM changes across aging may be an important factor. In the current study, we examined performance in WM and emotional LTM in younger and older adults. We added a daytime nap in half the subjects to examine a possible role of sleep on emotional LTM. In the morning, 93 younger (18–39) and 121 older (60–85) adults completed a WM task. Subjects also encoded neutral or negative word pairs and provided valence and arousal ratings for each pair. After half the subjects took a daytime nap, LTM was examined, and valence and arousal ratings were reassessed. Results indicate that older adults showed worse recognition for negative word pairs compared with neutral, as well as decreased negative valence ratings in the afternoon. This decrease in emotional reactivity was correlated with better LTM performance. In contrast, younger adults performed better on the negative compared to neutral word pairs, with no change in emotional reactivity and no association between emotional reactivity and LTM. In addition, WM was positively related to LTM in younger, but not in older adults. Lastly, no differences were shown across sleep, regardless of age. Our findings suggest that the emotional memory bias may be associated with the emotional saliency of the information in older adults, and with WM capacity in younger adults.

Analyzing the critical factors for innovation sustainability in the public sector: evidence from Indonesia

PurposeThis study examines the critical factors contributing to the different conditions of innovation sustainability after a change in local political leadership.Design/methodology/approachThis study used a multiple case study approach and applied the critical incident technique (CIT) to collect and analyze data from four innovation cases in the two local governments of Indonesia.FindingsThe results highlight that the sustainability condition of each innovation after the political regime change is determined by multiple critical factors.Research limitations/implicationsFirst, the data collected through interviews may contain a memory bias. Second, this study was limited to local governments and did not consider innovation taxonomies.Practical implicationsThe study implies that in order to sustain innovation, public leaders must support innovation legitimacy as a new organizational structure; thus, it can be more durable in the long term. In addition, public leaders need to minimize innovation politicization by authorizing bureaucrats to autonomously manage innovation operationalization.Social implicationsPublic leaders need to pay careful attention to their innovation sustainability because a non-sustained policy can disappoint the individuals working for it, losing their trust and enthusiasm. This dissatisfaction could become a barrier to mobilizing support for the following policies.Originality/valueInnovation sustainability is a new theme that is overlooked in the public sector innovation literature. Therefore, investigations using different methods and contexts are required, as this study offers. This study also demonstrated the value of CIT in identifying critical factors affecting innovation sustainability in the context of political leadership change.

Disentangling Aging and Mood Effects on Emotional Memory.

Older adults tend to be in a more positive mood than young adults, and tend to remember positive information more often than negative information, yet the link between their positive mood and their positive memory bias has not often been explored. In this study, we manipulated young and older adults’ moods prior to their completing an emotional memory task. For mood manipulation, young (n = 147) and older (n = 111) adults viewed a positive, negative, or neutral video lasting 3 min. To validate the mood induction, we collected self-reported ratings of valence and arousal (affective slider; Betella and Verschure, 2016) at baseline, after the video, and after the memory task. The memory task consisted of incidental encoding of 30 intermixed pictures (10 positive, 10 negative, 10 neutral valence), followed by free recall. The mood manipulation changed people’s self-reported valence, yet it did not influence self-reported arousal. The memory task revealed a consistent negativity bias in young adults. Older adults recalled negative and positive pictures equally well in all conditions. After viewing a negative video, they recalled positive pictures more often than neutral pictures, but did not show the same advantage for negative pictures over neutral pictures. This positive memory advantage was weaker in the positive mood condition. Therefore, mood manipulation influenced in part older adults’ emotional memory bias, showing some signs of mood incongruence which we discuss in terms of emotion regulation. This shows the importance of accounting for mood differences in studies on aging and memory. The robust age group differences support the view that the positivity effect in aging is the result of a negativity bias that fades with age.

Offline memory replay in recurrent neuronal networks emerges from constraints on online dynamics.

During spatial exploration, neural circuits in the hippocampus store memories of sequences of sensory events encountered in the environment. When sensory information is absent during 'offline' resting periods, brief neuronal population bursts can 'replay' sequences of activity that resemble bouts of sensory experience. These sequences can occur in either forward or reverse order, and can even include spatial trajectories that have not been experienced, but are consistent with the topology of the environment. The neural circuit mechanisms underlying this variable and flexible sequence generation are unknown. Here we demonstrate in a recurrent spiking network model of hippocampal area CA3 that experimental constraints on network dynamics such as population sparsity, stimulus selectivity, rhythmicity and spike rate adaptation, as well as associative synaptic connectivity, enable additional emergent properties, including variable offline memory replay. In an online stimulus-driven state, we observed the emergence of neuronal sequences that swept from representations of past to future stimuli on the timescale of the theta rhythm. In an offline state driven only by noise, the network generated both forward and reverse neuronal sequences, and recapitulated the experimental observation that offline memory replay events tend to include salient locations like the site of a reward. These results demonstrate that biological constraints on the dynamics of recurrent neural circuits are sufficient to enable memories of sensory events stored in the strengths of synaptic connections to be flexibly read out during rest and sleep, which is thought to be important for memory consolidation and planning of future behaviour. KEY POINTS: A recurrent spiking network model of hippocampal area CA3 was optimized to recapitulate experimentally observed network dynamics during simulated spatial exploration. During simulated offline rest, the network exhibited the emergent property of generating flexible forward, reverse and mixed direction memory replay events. Network perturbations and analysis of model diversity and degeneracy identified associative synaptic connectivity and key features of network dynamics as important for offline sequence generation. Network simulations demonstrate that population over-representation of salient positions like the site of reward results in biased memory replay.

The antidepressant effect of cognitive reappraisal training on individuals cognitively vulnerable to depression: Could cognitive bias be modified through the prefrontal-amygdala circuits?

Cognitive reappraisal (CR) is one of the core treatment components of cognitive behavioral therapy (CBT) and is the gold standard treatment for major depressive disorders. Accumulating evidence indicates that cognitive reappraisal could function as a protective factor of cognitive vulnerability to depression. However, the neural mechanism by which CR training reduces cognitive vulnerability to depression is unclear. There is ample evidence that the prefrontal–amygdala circuit is involved in CR. This study proposes a novel cognitive bias model of CR training which hypothesizes that CR training may improve the generation ability of CR with altered prefrontal–amygdala functional activation/connectivity, thus reducing negative cognitive bias (negative attention bias, negative memory bias, negative interpretation bias, and/or negative rumination bias) and alleviating depressive symptoms. This study aims to (1) explore whether there is abnormal CR strategy generation ability in individuals who are cognitively vulnerable to depression; (2) test the hypothesis that CR training alleviates depressive symptoms through the mediators of cognitive bias (interpretation bias and/or rumination bias); (3) explore the neural mechanism by which CR training may enhance the ability of CR strategy generation; and (4) examine the short- and long-term effects of CR training on the reduction in depressive symptoms in individuals who are cognitively vulnerable to depression following intervention and 6 months later. The study is promising, providing theoretical and practical evidence for the early intervention of depression-vulnerable individuals.

Mindfulness based cognitive therapy (MBCT) reduces depression-related self-referential processing in patients with bipolar disorder: an exploratory task-based study

ABSTRACT Negative self-referential processing has fruitfully been studied in unipolar depressed patients, but remarkably less in patients with bipolar disorder (BD). This exploratory study examines the relation between task-based self-referential processing and depressive symptoms in BD and their possible importance to the working mechanism of mindfulness-based cognitive therapy (MBCT) for BD. The study population consisted of a subsample of patients with BD (n = 49) participating in an RCT of MBCT for BD, who were assigned to MBCT + TAU (n = 23) or treatment as usual (TAU) (n = 26). Patients performed the self-referential encoding task (SRET), which measures (1) positive and (2) negative attributions to oneself as well as (3) negative self-referential memory bias, before and after MBCT + TAU or TAU. At baseline, all three SRET measures were significantly related to depressive symptoms in patients with BD. Moreover, repeated measures analyses of variance revealed that negative self-referential memory bias diminished over time in the MBCT + TAU group, compared with the TAU group. Given the preliminary nature of our findings, future research should explore the possibly mediating role of reducing negative self-referential memory bias in preventing and treating depressive symptoms in BD through MBCT.

Sensory suppression and increased neuromodulation during actions disrupt memory encoding of unpredictable self-initiated stimuli.

Actions modulate sensory processing by attenuating responses to self- compared to externally generated inputs, which is traditionally attributed to stimulus-specific motor predictions. Yet, suppression has been also found for stimuli merely coinciding with actions, pointing to unspecific processes that may be driven by neuromodulatory systems. Meanwhile, the differential processing for self-generated stimuli raises the possibility of producing effects also on memory for these stimuli; however, evidence remains mixed as to the direction of the effects. Here, we assessed the effects of actions on sensory processing and memory encoding of concomitant, but unpredictable sounds, using a combination of self-generation and memory recognition task concurrently with EEG and pupil recordings. At encoding, subjects performed button presses that half of the time generated a sound (motor-auditory; MA) and listened to passively presented sounds (auditory-only; A). At retrieval, two sounds were presented and participants had to respond which one was present before. We measured memory bias and memory performance by having sequences where either both or only one of the test sounds were presented at encoding, respectively. Results showed worse memory performance - but no differences in memory bias -, attenuated responses, and larger pupil diameter for MA compared to A sounds. Critically, the larger the sensory attenuation and pupil diameter, the worse the memory performance for MA sounds. Nevertheless, sensory attenuation did not correlate with pupil dilation. Collectively, our findings suggest that sensory attenuation and neuromodulatory processes coexist during actions, and both relate to disrupted memory for concurrent, albeit unpredictable sounds.

The positive evidence bias in perceptual confidence is unlikely post-decisional.

Confidence in a perceptual decision is a subjective estimate of the accuracy of one’s choice. As such, confidence is thought to be an important computation for a variety of cognitive and perceptual processes, and it features heavily in theorizing about conscious access to perceptual states. Recent experiments have revealed a “positive evidence bias” (PEB) in the computations underlying confidence reports. A PEB occurs when confidence, unlike objective choice, overweights the evidence for the correct (or chosen) option, relative to evidence against the correct (or chosen) option. Accordingly, in a perceptual task, appropriate stimulus conditions can be arranged that produce selective changes in confidence reports but no changes in accuracy. Although the PEB is generally assumed to reflect the observer’s perceptual and/or decision processes, post-decisional accounts have not been ruled out. We therefore asked whether the PEB persisted under novel conditions that addressed two possible post-decisional accounts: (i) post-decision evidence accumulation that contributes to a confidence report solicited after the perceptual choice and (ii) a memory bias that emerges in the delay between the stimulus offset and the confidence report. We found that even when the stimulus remained on the screen until observers responded, and when observers reported their choice and confidence simultaneously, the PEB still emerged. Signal detection-based modeling showed that the PEB was not associated with changes to metacognitive efficiency, but rather to confidence criteria. The data show that memory biases cannot explain the PEB and provide evidence against a post-decision evidence accumulation account, bolstering the idea that the PEB is perceptual or decisional in nature.

Therapists' experiences of a brief case formulation and alliance focused pre‐treatment training session (CALL)

AbstractObjectiveA general lack of supervision outcome studies and new advancements within therapist training methods inspired us to develop a randomised controlled trial, Case formulation and ALLiance (CALL), testing the efficacy of a brief pre‐treatment training session. CALL combines generic case formulation and alliance principles with the supervision of a specific client. This qualitative study acts as a preliminary to the randomised controlled trial and aims to explore psychologists' experiences of participating in CALL.MethodSemi‐structured interviews were conducted with seven psychologists in private practice, who participated in CALL between January and May 2020. The transcribed interviews were analysed using thematic analysis.ResultsThe psychologists described CALL as a clinically useful and collegial experience but simultaneously conveyed a lack of recollection of the training session and doubts as to its enduring utilisation.ConclusionCALL has the potential to positively influence the process and outcome of therapy through the fostering of case formulation and alliance management skills, as well as a strong supervisory alliance. However, the familiar content or brief format of the session, and participants' memory bias, may have limited the utilisation and recall of the intervention.

When does self-report of pain occur?: A study of older adults.

Technologies for self-care can drive participatory health and promote independence of older adults. One self-care activity is regularly measuring and registering personal health indicators (self-reporting). Older adults may benefit from this practice, as they are more likely to have chronic health issues and have specific self-monitoring needs. However, self-reporting technologies are usually not designed specifically for them. Pain is usually measured using patient reports compiled during medical appointments, although this process may be affected by memory bias and under reporting of fluctuating pain. To address these issues, we introduced a simple tangible interface to self-report pain levels and conducted a three-hour evaluation with 24 older adults. The goal of this study was to identify whether specific activities, activity levels or pain levels trigger older adults to self-report their pain level, besides to understand how older adults would use such a device. Within the limited time frame of the experiment, the majority of our participants chose to report pain when they felt it most, not reporting lower levels of pain. No evidence was found to suggest a relationship between the reporting of pain and the activity (or activity level). Several design insights intended to improve the design of technologies are provided.

Coherence of attention and memory biases in currently and previously depressed women

ABSTRACT Previous research has found that depression is characterised by biased processing of emotional information. Although most studies have examined cognitive biases in isolation, simultaneous examination of multiple biases is required to understand how they may interact and influence one another to produce depression vulnerability. In this study, the attention and memory biases of currently depressed, previously depressed, and never depressed women were examined using the same stimuli and a unified methodology. Participants viewed negative, positive, and neutral words while their eye gaze was tracked and recorded. After a distraction task, participants completed an incidental recognition test that included words from the eye-tracking task and new words. The results supported the hypothesised mediation model for positive words: currently depressed women had a reduced attention bias for positive words and, in turn, had poorer memory for positive words relative to never depressed women. Previously depressed women, however, showed a lack of coherence between attention and memory biases for positive words. The groups did not differ in their attention or memory biases for negative words. The findings provide novel evidence in support of a causal link between the absence of protective attention and memory biases for positive information in clinical depression.

Perceived societal anomie and the implicit trajectory of national decline: Replicating and extending Yamashiro and Roediger (2019) within a French sample

To date, most research has investigated people’s representations of the national past and future separately and the few that examined the relationships between the two overlooked the role of the group’s present. The present study aimed to replicate previous results showing an implicit trajectory of national decline among Americans within a French sample and additionally examined whether perceived societal anomie— that is, perceiving that present society is disintegrated and disregulated—would accentuate this trajectory of decline. Results first showed a positivity bias for the French past and a negativity bias for the French future; thus, replicating previous results showing an implicit trajectory of national decline in another national context. Moreover, the trajectory of decline was steeper for participants who perceived present French society as highly anomic; but only because they projected more negative national futures. Explanations for the conflicting results in the literature regarding valence biases in collective memory are discussed.

How to cope with the threat to moral self? The perspectives of memory bias in moral contexts

How to cope with the threat to moral self? The perspectives of memory bias in moral contexts

Leveraging Machine Learning to Automatically Derive Robust Decision Strategies from Imperfect Knowledge of the Real World

Teaching people clever heuristics is a promising approach to improve decision-making under uncertainty. The theory of resource rationality makes it possible to leverage machine learning to discover optimal heuristics automatically. One bottleneck of this approach is that the resulting decision strategies are only as good as the model of the decision problem that the machine learning methods were applied to. This is problematic because even domain experts cannot give complete and fully accurate descriptions of the decisions they face. To address this problem, we develop strategy discovery methods that are robust to potential inaccuracies in the description of the scenarios in which people will use the discovered decision strategies. The basic idea is to derive the strategy that will perform best in expectation across all possible real-world problems that could have given rise to the likely erroneous description that a domain expert provided. To achieve this, our method uses a probabilistic model of how the description of a decision problem might be corrupted by biases in human judgment and memory. Our method uses this model to perform Bayesian inference on which real-world scenarios might have given rise to the provided descriptions. We applied our Bayesian approach to robust strategy discovery in two domains: planning and risky choice. In both applications, we find that our approach is more robust to errors in the description of the decision problem and that teaching the strategies it discovers significantly improves human decision-making in scenarios where approaches ignoring the risk that the description might be incorrect are ineffective or even harmful. The methods developed in this article are an important step towards leveraging machine learning to improve human decision-making in the real world because they tackle the problem that the real world is fundamentally uncertain.