Nonmonotonic Plasticity: How Memory Retrieval Drives Learning

Finding the sweet spot of memory modification: An fMRI study on episodic prediction error strength and type

Previous research has highlighted the critical role of prediction errors (PEs) in signaling the need to adapt memory representations in response to unexpected changes in the environment. Yet, the influence of PE type and strength on memory remains underexplored. In this study, participants encoded naturalistic dialogues prior to undergoing fMRI scanning. During the fMRI session, they listened to dialogues that had been modified in their surface or gist, to varying extents. As expected, our findings revealed robust activation in the inferior frontal gyrus for all PEs. Notably, gist modifications elicited additional activations within the episodic memory network, including the hippocampus. A post-fMRI recognition test demonstrated that surface modifications had no significant impact on memory. Conversely, weak gist changes impaired memory for the original content and hindered learning of the modification. These weak gist changes also triggered activation in the parahippocampal cortex. These results underscore the importance of both the type and strength of PEs in shaping brain activations and memory outcomes, highlighting their complex interplay in cognitive processes.

Visual Statistical Learning Alters Low-Dimensional Cortical Architecture

Our brains are in a constant state of generating predictions, implicitly extracting environmental regularities to support later cognition and behavior, a process known as statistical learning (SL). While prior work investigating the neural basis of SL has focused on the activity of single brain regions in isolation, much less is known about how distributed brain areas coordinate their activity to support such learning. Using fMRI and a classic visual SL task, we investigated changes in whole-brain functional architecture as human female and male participants implicitly learned to associate pairs of images, and later, when predictions generated from learning were violated. By projecting individuals' patterns of cortical and subcortical functional connectivity onto a low-dimensional manifold space, we found that SL was associated with changes along a single neural dimension describing covariance across the visual-parietal and perirhinal cortex (PRC). During learning, we found regions within the visual cortex expanded along this dimension, reflecting their decreased communication with other networks, whereas regions within the dorsal attention network (DAN) contracted, reflecting their increased connectivity with higher-order cortex. Notably, when SL was interrupted, we found the PRC and entorhinal cortex, which did not initially show learning-related effects, now contracted along this dimension, reflecting their increased connectivity with the default mode and DAN, and decreased covariance with visual cortex. While prior research has linked SL to either broad cortical or medial temporal lobe changes, our findings suggest an integrative view, whereby cortical regions reorganize during association formation, while medial temporal lobe regions respond to their violation.

Memory updating and the structure of event representations

People form memories of specific events and use those memories to make predictions about similar new experiences. Living in a dynamic environment presents a challenge: How does one represent valid prior events in memory while encoding new experiences when things change? There is evidence for two seemingly contradictory classes of mechanism: One differentiates outdated event features by making them less similar or less accessible than updated event features. The other integrates updated features of new events with outdated memories, and the relationship between them, into a structured representation. Integrative encoding may occur when changed events trigger inaccurate predictions based on remembered prior events. We propose that this promotes subsequent recollection of events and their order, enabling adaptation to environmental changes.

Distortion of overlapping memories relates to arousal and anxiety

Everyday experiences often overlap, challenging our ability to maintain distinct episodic memories. One way to resolve such interference is by exaggerating subtle differences between remembered events, a phenomenon known as memory repulsion. Here, we tested whether repulsion is influenced by emotional arousal, when resolving memory interference is perhaps most needed. We adapted an existing paradigm in which participants repeatedly studied object-face associations. Participants studied two different-colored versions of each object: a to-be-tested "target" and its not-to-be-tested "competitor" pair mate. The level of interference between target and competitor pair mates was manipulated by making the object colors either highly similar or less similar, depending on the participant group. To manipulate arousal, the competitor object-face associations were preceded by either a neutral tone or an aversive and arousing burst of white noise. Memory distortion for the color of the target objects was tested after each study round to examine whether memory distortions emerge after learning. We found that participants with greater sound-induced pupil dilations, an index of physiological arousal, showed greater memory attraction of target colors towards highly similar competitor colors. Greater memory attraction was also correlated with greater memory interference in the last round of learning. Additionally, individuals who self-reported higher trait anxiety showed greater memory attraction when one of the overlapping memories was associated with something aversive. Our findings suggest that memories of similar neutral and arousing events may blur together after repeated exposures, especially in individuals who show higher arousal responses and symptoms of anxiety.

Plasticity of human resilience mechanisms

The hippocampus's vulnerability to trauma-induced stress can lead to pathophysiological disturbances that precipitate the development of posttraumatic stress disorder (PTSD). The mechanisms of resilience that foster remission and mitigate the adverse effects of stress remain unknown. We analyzed the evolution of hippocampal morphology between 2016/2017 and 2018/2019, as well as the memory control mechanisms crucial for trauma resilience. Participants were individuals exposed to the 2015 Paris terrorist attacks (N = 100), including chronic (N = 34) and remitted (N = 19) PTSD, and nonexposed (N = 72). We found that normalization of inhibitory control processes, which regulate the resurgence of intrusive memories in the hippocampus, not only predicted PTSD remission but also preceded a reduction in traumatic memories. Improvement in control mechanisms was associated with the interruption of stress-induced atrophy in a hippocampal region that includes the dentate gyrus. Human resilience to trauma is characterized by the plasticity of memory control circuits, which interacts with hippocampal neuroplasticity.

Emotion Regulation Under Stress: A Social Processing and Memory Perspective

Research on emotion regulation often focuses on cognitively effortful self-regulation strategies, but exposure to stress has been shown to interfere with the underlying mechanisms supporting such processes. Understanding alternative strategies that potentially bolster emotion regulation under stress is an important topic of investigation. Two potential alternatives involve everyday occurrences of social processing and memory recall. Social support and past emotional experiences may help in guiding us toward appropriate neurophysiological responses through overlapping circuitry with stress and reward systems, while also buttressing cognitive regulation strategies by expanding one's perspective and allowing multiple opportunities to regulate retrospectively. In recognition that ongoing social and emotional events are often at the beginning of a cascade of both emotion regulation and memory processes, this chapter focuses on the emerging role of social relationships and autobiographical memory recall in regulating emotions under stress, highlighting opportunities and challenges associated with this process.

Segregation-to-integration transformation model of memory evolution

Memories are thought to use coding schemes that dynamically adjust their representational structure to maximize both persistence and efficiency. However, the nature of these coding scheme adjustments and their impact on the temporal evolution of memory after initial encoding is unclear. Here, we introduce the Segregation-to-Integration Transformation (SIT) model, a network formalization that offers a unified account of how the representational structure of a memory is transformed over time. The SIT model asserts that memories initially adopt a highly modular or segregated network structure, functioning as an optimal storage buffer by balancing protection from disruptions and accommodating substantial information. Over time, a repeated combination of neural network reactivations involving activation spreading and synaptic plasticity transforms the initial modular structure into an integrated memory form, facilitating intercommunity spreading and fostering generalization. The SIT model identifies a nonlinear or inverted U-shaped function in memory evolution where memories are most susceptible to changing their representation. This time window, located early during the transformation, is a consequence of the memory's structural configuration, where the activation diffusion across the network is maximized.

The effects of episodic context on memory integration

Information encountered in different events, such as people and objects, can be interlinked in memory. Such memory integration supports novel inferences about the world. This study investigates the role of episodic context on memory integration in two experiments using an associative inference task. Participants encoded events with overlapping (AB and BC) and non-overlapping associations (XY) presented in the same or different episodic contexts. Inference performance across events (AC) was tested in the absence (Experiment 1) and in the presence (Experiment 2) of the encoding context. Our data show that inferences across events encoded in the same context were more accurate, faster, and made with greater confidence compared to those encoded in different contexts. However, this effect was observed only when the context was presented during testing, suggesting that context enhances associative inferences by facilitating retrieval of events associated with that context. These findings demonstrate that revisiting the encoding context promotes memory integration by providing privileged access to contextually associated memory traces and facilitating their flexible recombination to form novel inferences.

Inducing representational change in the hippocampus through real-time neurofeedback

When you perceive or remember something, other related things come to mind, affecting how these competing items are subsequently perceived and remembered. Such behavioural consequences are believed to result from changes in the overlap of neural representations of these items, especially in the hippocampus. According to multiple theories, hippocampal overlap should increase (integration) when there is high coactivation between cortical representations. However, prior studies used indirect proxies for coactivation by manipulating stimulus similarity or task demands. Here, we induce coactivation in visual cortex more directly using closed-loop neurofeedback from real-time functional magnetic resonance imaging (fMRI). While viewing one object, participants were rewarded for activating the representation of another object as strongly as possible. Across multiple real-time fMRI sessions, participants succeeded in using this neurofeedback to increase coactivation. Compared with a baseline of untrained objects, this protocol led to memory integration in behaviour and the brain: the trained objects became harder for participants to discriminate behaviourally in a categorical perception task and harder to discriminate neurally from patterns of fMRI activity in their hippocampus as a result of losing unique features. These findings demonstrate that neurofeedback can be used to alter and combine memories.This article is part of the theme issue 'Neurofeedback: new territories and neurocognitive mechanisms of endogenous neuromodulation'.

Object Feature Memory Is Distorted by Category Structure

Memory systems constantly confront the challenge of capturing both the shared features that connect experiences together and the unique features that distinguish them. Across two experiments, we leveraged a color memory distortion paradigm to investigate how we handle this representational tension when learning new information. Over a thirty-minute period, participants learned shared and unique features of categories of novel objects, where each feature was assigned a particular color. While participants did not differ in how accurately they remembered these features overall, when inaccurate, participants misremembered the color of shared (relative to unique) features as more similar to the category's average color, suggesting more integration of shared features in memory. This same rapid representational warping manifested in a neural network model trained on the same categories. The work reveals how memories for different features are rapidly and differentially warped as a function of their roles in a category.

The role of REM sleep in neural differentiation of memories in the hippocampus

When faced with a familiar situation, we can use memory to make predictions about what will happen next. If such predictions turn out to be erroneous, the brain can adapt by differentiating the representations of the cues that generated the prediction from the mispredicted item itself, reducing the likelihood of future prediction errors. Prior work by Kim et al. (2017) found that violating a sequential association in a statistical learning paradigm triggered differentiation of the neural representations of the associated items in the hippocampus. Here, we used fMRI to test the preregistered hypothesis that this hippocampal differentiation occurs only when violations are followed by rapid eye movement (REM) sleep. In the morning, participants first learned that some items predict others (e.g., A predicts B) then encountered a violation in which a predicted item (B) failed to appear when expected after its associated item (A); the predicted item later appeared on its own after an unrelated item. Participants were then randomly assigned to one of three conditions: remain awake, take a nap containing non-REM sleep only, or take a nap with both non-REM and REM sleep. While the predicted results were not observed in the preregistered left CA2/3/DG ROI, we did observe evidence for our hypothesis in closely related hippocampal ROIs, uncorrected for multiple comparisons: In right CA2/3/DG, differentiation in the group with REM sleep was greater than in the groups without REM sleep (wake and non-REM nap); this differentiation was item-specific and concentrated in right DG. Differentiation effects were also greater in bilateral DG when the predicted item was more strongly reactivated during the violation. Overall, the results presented here provide initial evidence linking REM sleep to changes in the hippocampal representations of memories in humans.

Repulsion of CA3 / dentate gyrus representations is driven by distinct internal beliefs in the face of ambiguous sensory input

Recent human neuroimaging studies of episodic memory have revealed a counterintuitive phenomenon in the hippocampus: when events are highly similar, corresponding hippocampal activity patterns are sometimes less correlated than activity patterns associated with unrelated events. This phenomenon-repulsion-is not accounted for by most theories of the hippocampus, and the conditions that trigger repulsion remain poorly understood. Here, we used a spatial route-learning task and high-resolution fMRI in humans to test whether hippocampal repulsion is fundamentally driven by internal beliefs about the environment. By precisely measuring participants' internal beliefs and actively manipulating them, we show that repulsion selectively occurred in hippocampal subfields CA3 and dentate gyrus when visual input was ambiguous-or even identical-but internal beliefs were distinct. These findings firmly establish conditions that elicit repulsion and have broad relevance to theories of hippocampal function and to the fields of human episodic memory and rodent spatial navigation.

Search flavor labels in beverages: An electrophysiological investigation of color-flavor congruency and association strength in visual search

Individuals are apt to link various characteristics of an object or event through different sensory experiences. We conducted two electrophysiological experiments to investigate the effects of color-flavor congruency and association strength on visual search efficiency and the in-depth cognitive mechanisms underlying multisensory processes. Participants were prompted with a flavor label and asked to identify the primed flavor from four beverage bottle images. Experiment 1 focused on color-flavor congruency and noted faster searches for congruent targets than incongruent ones. EEG data exhibited smaller N2, larger P3 and LPC, and increased parietal-occipital midline (POM) alpha power for incongruent targets than congruent ones. Experiment 2 manipulated color-flavor association strength within each flavor. Behavioral findings showed that searches for targets with weak association strength took longer than those with strong association strength. Moreover, time-frequency analysis displayed that the former evoked greater frontal midline (FM) theta power and higher alpha power than the latter. Altogether, our research indicated that (1) color expectations based on prior experience can automatically guide people's attentional selection, (2) the color-flavor congruency and association strength impact the visual search efficiency via distinct pathways, and (3) theta and alpha activities make a pivotal role in unraveling multisensory information processing. These findings shed some light on the intricate cognitive processes involved in crossmodal visual search and the underlying neurocognitive dynamics.

A complementary learning systems model of how sleep moderates retrieval practice effects

While many theories assume that sleep is critical in stabilizing and strengthening memories, our recent behavioral study (Liu & Ranganath, 2021, Psychonomic Bulletin & Review, 28[6], 2035-2044) suggests that sleep does not simply stabilize memories. Instead, it plays a more complex role, integrating information across two temporally distinct learning episodes. In the current study, we simulated the results of Liu and Ranganath (2021) using our biologically plausible computational model, TEACH, developed based on the complementary learning systems (CLS) framework. Our model suggests that when memories are activated during sleep, the reduced influence of temporal context establishes connections across temporally separated events through mutual training between the hippocampus and neocortex. In addition to providing a compelling mechanistic explanation for the selective effect of sleep, this model offers new examples of the diverse ways in which the cortex and hippocampus can interact during learning.

The upside of cumulative conceptual interference on exemplar-level mnemonic discrimination

Although long-term visual memory (LTVM) has a remarkable capacity, the fidelity of its episodic representations can be influenced by at least two intertwined interference mechanisms during the encoding of objects belonging to the same category: the capacity to hold similar episodic traces (e.g., different birds) and the conceptual similarity of the encoded traces (e.g., a sparrow shares more features with a robin than with a penguin). The precision of episodic traces can be tested by having participants discriminate lures (unseen objects) from targets (seen objects) representing different exemplars of the same concept (e.g., two visually similar penguins), which generates interference at retrieval that can be solved if efficient pattern separation happened during encoding. The present study examines the impact of within-category encoding interference on the fidelity of mnemonic object representations, by manipulating an index of cumulative conceptual interference that represents the concurrent impact of capacity and similarity. The precision of mnemonic discrimination was further assessed by measuring the impact of visual similarity between targets and lures in a recognition task. Our results show a significant decrement in the correct identification of targets for increasing interference. Correct rejections of lures were also negatively impacted by cumulative interference as well as by the visual similarity with the target. Most interestingly though, mnemonic discrimination for targets presented with a visually similar lure was more difficult when objects were encoded under lower, not higher, interference. These findings counter a simply additive impact of interference on the fidelity of object representations providing a finer-grained, multi-factorial, understanding of interference in LTVM.

A neural network model of differentiation and integration of competing memories

What determines when neural representations of memories move together (integrate) or apart (differentiate)? Classic supervised learning models posit that, when two stimuli predict similar outcomes, their representations should integrate. However, these models have recently been challenged by studies showing that pairing two stimuli with a shared associate can sometimes cause differentiation, depending on the parameters of the study and the brain region being examined. Here, we provide a purely unsupervised neural network model that can explain these and other related findings. The model can exhibit integration or differentiation depending on the amount of activity allowed to spread to competitors - inactive memories are not modified, connections to moderately active competitors are weakened (leading to differentiation), and connections to highly active competitors are strengthened (leading to integration). The model also makes several novel predictions - most importantly, that when differentiation occurs as a result of this unsupervised learning mechanism, it will be rapid and asymmetric, and it will give rise to anticorrelated representations in the region of the brain that is the source of the differentiation. Overall, these modeling results provide a computational explanation for a diverse set of seemingly contradictory empirical findings in the memory literature, as well as new insights into the dynamics at play during learning.

Replay-triggered brain-wide activation in humans

The consolidation of discrete experiences into a coherent narrative shapes the cognitive map, providing structured mental representations of our experiences. In this process, past memories are reactivated and replayed in sequence, fostering hippocampal-cortical dialogue. However, brain-wide engagement coinciding with sequential reactivation (or replay) of memories remains largely unexplored. In this study, employing simultaneous EEG-fMRI, we capture both the spatial and temporal dynamics of memory replay. We find that during mental simulation, past memories are replayed in fast sequences as detected via EEG. These transient replay events are associated with heightened fMRI activity in the hippocampus and medial prefrontal cortex. Replay occurrence strengthens functional connectivity between the hippocampus and the default mode network, a set of brain regions key to representing the cognitive map. On the other hand, when subjects are at rest following learning, memory reactivation of task-related items is stronger than that of pre-learning rest, and is also associated with heightened hippocampal activation and augmented hippocampal connectivity to the entorhinal cortex. Together, our findings highlight a distributed, brain-wide engagement associated with transient memory reactivation and its sequential replay.

No evidence that arousal affects reactivated memories

Memory for inherently neutral elements of emotional events is often enhanced on delayed tests - an effect that has been attributed to noradrenergic arousal. Reactivation of a memory is thought to return its corresponding neural ensemble to a state that is similar to when it was originally experienced. Therefore, we hypothesized that neutral elements of memories, too, can be enhanced through reactivation concurrent with heightened arousal. Participants (n = 94) visited the lab for three sessions. During the first session, they encoded 120 neutral memories consisting of an object presented in unique context images. In session two, the 80 objects were reactivated by presenting their corresponding context images, 40 of which were immediately followed by an arousal-inducing shock. Finally, recognition memory for all objects was tested. It was found that memory for reactivated objects was enhanced, but even though the shocks elicited elevations in arousal as indexed by skin conductance, there was no difference between memory of objects reactivated with and without heightened arousal. We thus conclude that arousal, when isolated from other cognitive and affective variables that might impact memory, has no enhancing effect on reactivated memories.

Want to learn? think again!

One of the best ways to improve new learning and increase memory strength is by reprocessing the recently acquired information, for example, by thinking of it again. Synaptic plasticity, the process by which neurons change the strength of their connections with each other, is fundamental for learning and memory formation. Yet, at present, it is unclear how reprocessing information drives synaptic plasticity to support memory improvement. A new study suggests that reprocessing enhances memory formation by recruiting more synapses to represent the new memory, thus increasing its strength.

Differentiation and Integration of Competing Memories: A Neural Network Model

What determines when neural representations of memories move together (integrate) or apart (differentiate)? Classic supervised learning models posit that, when two stimuli predict similar outcomes, their representations should integrate. However, these models have recently been challenged by studies showing that pairing two stimuli with a shared associate can sometimes cause differentiation, depending on the parameters of the study and the brain region being examined. Here, we provide a purely unsupervised neural network model that can explain these and other related findings. The model can exhibit integration or differentiation depending on the amount of activity allowed to spread to competitors - inactive memories are not modified, connections to moderately active competitors are weakened (leading to differentiation), and connections to highly active competitors are strengthened (leading to integration). The model also makes several novel predictions - most importantly, that when differentiation occurs as a result of this unsupervised learning mechanism, it will be rapid and asymmetric, and it will give rise to anticorrelated representations in the region of the brain that is the source of the differentiation. Overall, these modeling results provide a computational explanation for a diverse set of seemingly contradictory empirical findings in the memory literature, as well as new insights into the dynamics at play during learning.

Memory and belief updating following complete and partial reminders of fake news

Fake news can have enduring effects on memory and beliefs. An ongoing theoretical debate has investigated whether corrections (fact-checks) should include reminders of fake news. The familiarity backfire account proposes that reminders hinder correction (increasing interference), whereas integration-based accounts argue that reminders facilitate correction (promoting memory integration). In three experiments, we examined how different types of corrections influenced memory for and belief in news headlines. In the exposure phase, participants viewed real and fake news headlines. In the correction phase, participants viewed reminders of fake news that either reiterated the false details (complete) or prompted recall of missing false details (partial); reminders were followed by fact-checked headlines correcting the false details. Both reminder types led to proactive interference in memory for corrected details, but complete reminders produced less interference than partial reminders (Experiment 1). However, when participants had fewer initial exposures to fake news and experienced a delay between exposure and correction, this effect was reversed; partial reminders led to proactive facilitation, enhancing correction (Experiment 2). This effect occurred regardless of the delay before correction (Experiment 3), suggesting that the effects of partial reminders depend on the number of prior fake news exposures. In all experiments, memory and perceived accuracy were better when fake news and corrections were recollected, implicating a critical role for integrative encoding. Overall, we show that when memories of fake news are weak or less accessible, partial reminders are more effective for correction; when memories of fake news are stronger or more accessible, complete reminders are preferable.

Motivation and prediction-driven processing of social memoranda

Social semantic memory guides many aspects of behavior. Individuals rely on acquired and inferred knowledge about personal characteristics and group membership to predict the behavior and character of social targets. These predictions then determine the expectations from, the behavior in, and the interpretations of social interactions. According to predictive processing accounts, mnemonic and attentional mechanisms should enhance the processing of prediction-violating events. However, empirical findings suggest that prediction-consistent social events are often better remembered. This mini-review integrates recent evidence from social and non-social memory research to highlight the role of motivation in explaining these discrepancies. A particular emphasis is given to the continuous nature of prediction-(in)consistency, the epistemic tendency of perceivers to maintain or update their knowledge, and the dynamic influences of motivation on multiple steps in prediction-driven social memory. The suggested framework provides a coherent outlook of existing work and offers promising future directions to better understand the ebb and flow of social memoranda.

The reach of reactivation: Effects of consciously triggered versus unconsciously triggered reactivation of associative memory

Consolidating memories for long-term storage depends on reactivation. Reactivation occurs both consciously, during wakefulness, and unconsciously, during wakefulness and sleep. While considerable work has examined conscious awake and unconscious sleep reactivation, in this study, we directly compare the consequences of conscious and unconscious reactivation during wakefulness. Forty-one participants learned associations consisting of adjective-object-position triads. Objects were clustered into distinct semantic groups (e.g., fruits, vehicles) such that we could examine consequences of reactivation on semantically related memories. After an intensive learning protocol, we systematically reactivated some of the triads by presenting the adjective as a cue. Reactivation was done so that it was consciously experienced for some triads, and only unconsciously processed for others. Memory for spatial positions, the most distal part of the association, was affected by reactivation in a consciousness-dependent and memory-strength-dependent manner. Conscious reactivation resulted in weakening of semantically related memories that were strong initially, resonating with prior findings of retrieval-induced forgetting. Unconscious reactivation, on the other hand, selectively benefited weak reactivated memories, as previously shown for reactivation during sleep. Semantically linked memories were not impaired, but rather were integrated with the reactivated memory. These results taken together demonstrate that conscious and unconscious reactivation have qualitatively different consequences. Results support a consciousness-dependent inhibition account, whereby unconscious reactivation entails less inhibition than conscious reactivation, thus allowing more liberal spread of activation. Findings set the stage for additional exploration into the role of conscious experience in memory storage and structuring.

INDUCING REPRESENTATIONAL CHANGE IN THE HIPPOCAMPUS THROUGH REAL-TIME NEUROFEEDBACK

When you perceive or remember one thing, other related things come to mind. This competition has consequences for how these items are later perceived, attended, or remembered. Such behavioral consequences result from changes in how much the neural representations of the items overlap, especially in the hippocampus. These changes can reflect increased (integration) or decreased (differentiation) overlap; previous studies have posited that the amount of coactivation between competing representations in cortex determines which will occur: high coactivation leads to hippocampal integration, medium coactivation leads to differentiation, and low coactivation is inert. However, those studies used indirect proxies for coactivation, by manipulating stimulus similarity or task demands. Here we induce coactivation of competing memories in visual cortex more directly using closed-loop neurofeedback from real-time fMRI. While viewing one object, participants were rewarded for implicitly activating the representation of another object as strongly as possible. Across multiple real-time fMRI training sessions, they succeeded in using the neurofeedback to induce coactivation. Compared with untrained objects, this coactivation led to behavioral and neural integration: The trained objects became harder for participants to discriminate in a categorical perception task and harder to decode from patterns of fMRI activity in the hippocampus.

Behavioral representational similarity analysis reveals how episodic learning is influenced by and reshapes semantic memory

While semantic and episodic memory have been shown to influence each other, uncertainty remains as to how this interplay occurs. We introduce a behavioral representational similarity analysis approach to assess whether semantic space can be subtly re-sculpted by episodic learning. Eighty participants learned word pairs that varied in semantic relatedness, and learning was bolstered via either testing or restudying. Next-day recall is superior for semantically related pairs, but there is a larger benefit of testing for unrelated pairs. Analyses of representational change reveal that successful recall is accompanied by a pulling together of paired associates, with cue words in semantically related (but not unrelated) pairs changing more across learning than target words. Our findings show that episodic learning is associated with systematic and asymmetrical distortions of semantic space which improve later recall by making cues more predictive of targets, reducing interference from potential lures, and establishing novel connections within pairs.

Hippocampal mechanisms resolve competition in memory and perception

Behaving adaptively requires selection of relevant memories and sensations and suppression of competing ones. We hypothesized that these mechanisms are linked, such that hippocampal computations that resolve competition in memory also shape the precision of sensory representations to guide selective attention. We leveraged f MRI-based pattern similarity, receptive field modeling, and eye tracking to test this hypothesis in humans performing a memory-dependent visual search task. In the hippocampus, differentiation of competing memories predicted the precision of memory-guided eye movements. In visual cortex, preparatory coding of remembered target locations predicted search successes, whereas preparatory coding of competing locations predicted search failures due to interference. These effects were linked: stronger hippocampal memory differentiation was associated with lower competitor activation in visual cortex, yielding more precise preparatory representations. These results demonstrate a role for memory differentiation in shaping the precision of sensory representations, highlighting links between mechanisms that overcome competition in memory and perception.

Proximity to boundaries reveals spatial context representation in human hippocampal CA1

Recollection of real-world events is often accompanied by a sense of being in the place where the event transpired. Convergent evidence suggests the hippocampus plays a key role in supporting episodic memory by associating information with the time and place it was originally encountered. This representation is reinstated during memory retrieval. However, little is known about the roles of different subfields of the human hippocampus in this process. Research in humans and non-human animal models has suggested that spatial environmental boundaries have a powerful influence on spatial and episodic memory, as well as hippocampal representations of contexts and events. Here, we used high-resolution fMRI to investigate how boundaries influence hippocampal activity patterns during the recollection of objects encountered in different spatial contexts. During the encoding phase, participants viewed objects once in a naturalistic virtual reality task in which they passively explored two rooms in one of two houses. Following the encoding phase, participants were scanned while they recollected items in the absence of any spatial contextual information. Our behavioral results demonstrated that spatial context memory was enhanced for objects encountered near a boundary. Activity patterns in CA1 carried information about the spatial context associated with each of these boundary items. Exploratory analyses revealed that recollection performance was correlated with the fidelity of retrieved spatial context representations in anterior parahippocampal cortex and subiculum. Our results highlight the privileged role of boundaries in CA1 and suggest more generally a close relationship between memory for spatial contexts and representations in the hippocampus and parahippocampal region.

Predictions transform memories: How expected versus unexpected events are integrated or separated in memory

Our brains constantly generate predictions about the environment based on prior knowledge. Many of the events we experience are consistent with these predictions, while others might be inconsistent with prior knowledge and thus violate our predictions. To guide future behavior, the memory system must be able to strengthen, transform, or add to existing knowledge based on the accuracy of our predictions. We synthesize recent evidence suggesting that when an event is consistent with our predictions, it leads to neural integration between related memories, which is associated with enhanced associative memory, as well as memory biases. Prediction errors, in turn, can promote both neural integration and separation, and lead to multiple mnemonic outcomes. We review these findings and how they interact with factors such as memory reactivation, prediction error strength, and task goals, to offer insight into what determines memory for events that violate our predictions. In doing so, this review brings together recent neural and behavioral research to advance our understanding of how predictions shape memory, and why.

The testing effect for visual materials depends on preexisting knowledge

Remembering facilitates future remembering. This benefit of practicing by active retrieval, as compared to more passive relearning, is known as the testing effect and is one of the most robust findings in the memory literature. It has typically been assessed using verbal materials such as word pairs, sentences, or educational texts. We here investigate if memory for visual materials equally benefits from retrieval-mediated learning. Based on cognitive and neuroscientific theories, we hypothesize that testing effects will be limited to meaningful visual images that can be related to preexisting knowledge. In a series of four experiments, we systematically varied the type of material (meaningless "squiggle" shapes vs. meaningful object images) and the format of the test used to probe memory (a visually driven alternative forced-choice test vs. a remember/know recognition test). Within each experiment, we assessed the effects of practice type (retrieval or restudy) and the delay of the final test (immediate vs. 1 week) on the resulting practice benefits. Abstract shapes never showed a significant testing benefit, irrespective of test format. Meaningful object images did benefit from testing, particularly at long delays, and with a test format probing the recollective component of recognition memory. Together, our results indicate that retrieval can facilitate the recollection of visual images when they represent meaningful semantic units. This pattern of results is predicted by cognitive and neurobiologically motivated theories proposing that retrieval's benefits emerge through spreading activation in semantic networks, producing more easily accessible and longer-lasting memory traces. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Integration of event experiences to build relational knowledge in the human brain

We investigated how the human brain integrates experiences of specific events to build general knowledge about typical event structure. We examined an episodic memory area important for temporal relations, anterior-lateral entorhinal cortex, and a semantic memory area important for action concepts, middle temporal gyrus, to understand how and when these areas contribute to these processes. Participants underwent functional magnetic resonance imaging while learning and recalling temporal relations among novel events over two sessions 1 week apart. Across distinct contexts, individual temporal relations among events could either be consistent or inconsistent with each other. Within each context, during the recall phase, we measured associative coding as the difference of multivoxel correlations among related vs unrelated pairs of events. Neural regions that form integrative representations should exhibit stronger associative coding in the consistent than the inconsistent contexts. We found evidence of integrative representations that emerged quickly in anterior-lateral entorhinal cortex (at session 1), and only subsequently in middle temporal gyrus, which showed a significant change across sessions. A complementary pattern of findings was seen with signatures during learning. This suggests that integrative representations are established early in anterior-lateral entorhinal cortex and may be a pathway to the later emergence of semantic knowledge in middle temporal gyrus.

The reach of reactivation: Effects of consciously-triggered versus unconsciously-triggered reactivation of associative memory

Newly formed memories are not passively stored for future retrieval; rather, they are reactivated offline and thereby strengthened and transformed. However, reactivation is not a uniform process: it occurs throughout different states of consciousness, including conscious rehearsal during wakefulness and unconscious processing during both wakefulness and sleep. In this study, we explore the consequences of reactivation during conscious and unconscious awake states. Forty-one participants learned associations consisting of adjective-object-position triads. Objects were clustered into distinct semantic groups (e.g., multiple fruits, vehicles, musical instruments) which allowed us to examine the consequences of reactivation on semantically-related memories. After an extensive learning phase, some triads were reactivated consciously, through cued retrieval, or unconsciously, through subliminal priming. In both conditions, the adjective was used as the cue. Reactivation impacted memory for the most distal association (i.e., the spatial position of associated objects) in a consciousness-dependent and memory-strength-dependent manner. First, conscious reactivation of a triad resulted in a weakening of other semantically related memories, but only those that were initially more accurate (i.e., memories with lower pre-reactivation spatial errors). This is similar to what has been previously demonstrated in studies employing retrieval-induced forgetting designs. Unconscious reactivation, on the other hand, benefited memory selectively for weak cued items. Semantically linked associations were not impaired, but rather integrated with the reactivated memory. Taken together, our results demonstrate that conscious and unconscious reactivation of memories during wakefulness have qualitatively different consequences on memory for distal associations. Effects are memory-strength-dependent, as has been shown for reactivation during sleep. Results support a consciousness-dependent inhibition account, according to which unconscious reactivation involves less inhibitory dynamics than conscious reactivation, thus allowing more liberal spread of activation. Our findings set the stage for additional exploration into the role of consciousness in memory structuring.

Memory reactivation and suppression modulate integration of the semantic features of related memories in hippocampus

Encoding an event that overlaps with a previous experience may involve reactivating an existing memory and integrating it with new information or suppressing the existing memory to promote formation of a distinct, new representation. We used fMRI during overlapping event encoding to track reactivation and suppression of individual, related memories. We further used a model of semantic knowledge based on Wikipedia to quantify both reactivation of semantic knowledge related to a previous event and formation of integrated memories containing semantic features of both events. Representational similarity analysis revealed that reactivation of semantic knowledge related to a prior event in posterior medial prefrontal cortex (pmPFC) supported memory integration during new learning. Moreover, anterior hippocampus (aHPC) formed integrated representations combining the semantic features of overlapping events. We further found evidence that aHPC integration may be modulated on a trial-by-trial basis by interactions between ventrolateral PFC and anterior mPFC, with suppression of item-specific memory representations in anterior mPFC inhibiting hippocampal integration. These results suggest that PFC-mediated control processes determine the availability of specific relevant memories during new learning, thus impacting hippocampal memory integration.

Twisted memories: Addiction-related engrams are strengthened by desire thinking

Associative learning plays a central role in addiction by reinforcing associations between environmental cues and addiction-related information. Unsupervised learning models posit that memories are adjusted based on how strongly these representations are coactivated during the retrieval process. From a different perspective, clinical models of addiction posit that the escalation and persistence of craving may depend on desire thinking, a thinking style orienting to prefigure information about positive addiction-related experiences. In the present work, we tested the main hypothesis that desire thinking is a key factor in the strengthening of addiction-related associations. A group of adult smoking volunteers (N = 26) engaged in a period of desire thinking before performing an associative learning task in which neutral words (cues) were shown along with images (smoking-related vs. neutral context) at different frequencies. Two retrieval tests were administered, one immediately after encoding and the other after 24 h, to test how the recall of associations changed as a function of retention interval. Two control groups, smokers (N = 21) and non-smokers (N = 22), performed a similar procedure, with a neutral imagination task replacing desire thinking. Participants who engaged in desire thinking increased their performance from the first to the second retrieval test only for the most frequent smoking-related associations. Crucially, this selective effect was not observed in the two control groups. These results provide behavioral evidence in support of the idea that desire thinking plays a role in strengthening addiction-related associations. Thus, this thinking process may be considered a target for reconsolidation-based conceptualizations of, and treatments for, addiction.

Reactivation-induced memory integration prevents proactive interference in perceptual learning

We acquire perceptual skills through experience to adapt ourselves to the changing environment. Accomplishing an effective skill acquisition is a main purpose of perceptual learning research. Given the often observed learning effect specificity, multiple perceptual learnings with shared parameters could serve to improve the generalization of the learning effect. However, the interference between the overlapping memory traces of different learnings may impede this effort. Here, we trained human participants on an orientation discrimination task. We observed a proactive interference effect that the first training blocked the second training at its untrained location. This was a more pronounced effect than the well-known location specificity in perceptual learning. We introduced a short reactivation of the first training before the second training and successfully eliminated the proactive interference when the second training was inside the reconsolidation time window of the reactivated first training. Interestingly, we found that practicing an irrelevant task at the location of the second training immediately after the reactivation of the first training could also restore the effect of the second training but in a smaller magnitude, even if the second training was conducted outside of the reconsolidation window. We proposed a two-level mechanism of reactivation-induced memory integration to account for these results. The reactivation-based procedure could integrate either the previously trained and untrained locations or the two trainings at these locations, depending on the activated representations during the reconsolidation process. The findings provide us with new insight into the roles of long-term memory mechanisms in perceptual learning.

Cross-Modal Facilitation of Episodic Memory by Sequential Action Execution

Throughout our lives, the actions we produce are often highly familiar and repetitive (e.g., commuting to work). However, layered upon these routine actions are novel, episodic experiences. Substantial research has shown that prior knowledge can facilitate learning of conceptually related new information. But despite the central role our behavior plays in real-world experience, it remains unclear how engagement in a familiar sequence of actions influences memory for unrelated, nonmotor information coincident with those actions. To investigate this, we had healthy young adults encode novel items while simultaneously following a sequence of actions (key presses) that was either predictable and well-learned or random. Across three experiments (N = 80 each), we found that temporal order memory, but not item memory, was significantly enhanced for novel items encoded while participants executed predictable compared with random action sequences. These results suggest that engaging in familiar behaviors during novel learning scaffolds within-event temporal memory, an essential feature of episodic experiences.

Contextual incongruency triggers memory reinstatement and the disruption of neural stability

Schemas, or internal representation models of the environment, are thought to be central in organising our everyday life behaviour by giving stability and predictiveness to the structure of the world. However, when an element from an unfolding event mismatches the schema-derived expectations, the coherent narrative is interrupted and an update to the current event model representation is required. Here, we asked whether the perceived incongruence of an item from an unfolding event and its impact on memory relied on the disruption of neural stability patterns preceded by the neural reactivation of the memory representations of the just-encoded event. Our study includes data from two different experiments whereby human participants (N = 33, 26 females and N = 18, 16 females, respectively) encoded images of objects preceded by trial-unique sequences of events depicting daily routine. We found that neural stability patterns gradually increased throughout the ongoing exposure to a schema-consistent episode, which was corroborated by the re-analysis of data from two other experiments, and that the brain stability pattern was interrupted when the encoding of an object of the event was incongruent with the ongoing schema. We found that the decrease in neural stability for low-congruence items was seen at ∼1000 ms from object encoding onset and that it was preceded by an enhanced N400 ERP and an increased degree of neural reactivation of the just-encoded episode. Current results offer new insights into the neural mechanisms and their temporal orchestration that are engaged during online encoding of schema-consistent episodic narratives and the detection of incongruencies.

Representational integration and differentiation in the human hippocampus following goal-directed navigation

As we learn, dynamic memory processes build structured knowledge across our experiences. Such knowledge enables the formation of internal models of the world that we use to plan, make decisions, and act. Recent theorizing posits that mnemonic mechanisms of differentiation and integration - which at one level may seem to be at odds - both contribute to the emergence of structured knowledge. We tested this possibility using fMRI as human participants learned to navigate within local and global virtual environments over the course of 3 days. Pattern similarity analyses on entorhinal cortical and hippocampal patterns revealed evidence that differentiation and integration work concurrently to build local and global environmental representations, and that variability in integration relates to differences in navigation efficiency. These results offer new insights into the neural machinery and the underlying mechanisms that translate experiences into structured knowledge that allows us to navigate to achieve goals.

Continuously changing memories: a framework for proactive and non-linear consolidation

The traditional view of long-term memory is that memory traces mature in a predetermined 'linear' process: their neural substrate shifts from rapidly plastic medial temporal regions towards stable neocortical networks. We propose that memories remain malleable, not by repeated reinstantiations of this linear process but instead via dynamic routes of proactive and non-linear consolidation: memories change, their trajectory is flexible and reversible, and their physical basis develops continuously according to anticipated demands. Studies demonstrating memory updating, increasing hippocampal dependence to support adaptive use, and rapid neocortical plasticity provide evidence for continued non-linear consolidation. Although anticipated demand can affect all stages of memory formation, the extent to which it shapes the physical memory trace repeatedly and proactively will require further dedicated research.

Representations of Complex Contexts: A Role for Hippocampus

The hippocampus plays a critical role in supporting episodic memory, in large part by binding together experiences and items with surrounding contextual information. At present, however, little is known about the roles of different hippocampal subfields in supporting this item-context binding. To address this question, we constructed a task in which items were affiliated with differing types of context-cognitive associations that vary at the local, item level and membership in temporally organized lists that linked items together at a global level. Participants made item recognition judgments while undergoing high-resolution fMRI. We performed voxel pattern similarity analyses to answer the question of how human hippocampal subfields represent retrieved information about cognitive states and the time at which a past event took place. As participants recollected previously presented items, activity patterns in the CA23DG subregion carried information about prior cognitive states associated with these items. We found no evidence to suggest reinstatement of information about temporal context at the level of list membership, but exploratory analyses revealed representations of temporal context at a coarse level in conjunction with representations of cognitive contexts. Results are consistent with characterizations of CA23DG as a critical site for binding together items and contexts in the service of memory retrieval.

Attentional capture mediates the emergence and suppression of intrusive memories

Intrusive memories hijack consciousness and their control may lead to forgetting. However, the contribution of reflexive attention to qualifying a memory signal as interfering is unknown. We used machine learning to decode the brain's electrical activity and pinpoint the otherwise hidden emergence of intrusive memories reported during a memory suppression task. Importantly, the algorithm was trained on an independent attentional model of visual activity, mimicking either the abrupt and interfering appearance of visual scenes into conscious awareness or their deliberate exploration. Intrusion of memories into conscious awareness were decoded above chance. The decoding accuracy increased when the algorithm was trained using a model of reflexive attention. Conscious detection of intrusive activity decoded from the brain signal was central to the future silencing of suppressed memories and later forgetting. Unwanted memories require the reflexive orienting of attention and access to consciousness to be suppressed effectively by inhibitory control.

A smartphone intervention that enhances real-world memory and promotes differentiation of hippocampal activity in older adults

The act of remembering an everyday experience influences how we interpret the world, how we think about the future, and how we perceive ourselves. It also enhances long-term retention of the recalled content, increasing the likelihood that it will be recalled again. Unfortunately, the ability to recollect event-specific details and reexperience the past tends to decline with age. This decline in recollection may reflect a corresponding decrease in the distinctiveness of hippocampal memory representations. Despite these well-established changes, there are few effective cognitive behavioral interventions that target real-world episodic memory. We addressed this gap by developing a smartphone-based application called HippoCamera that allows participants to record labeled videos of everyday events and subsequently replay, high-fidelity autobiographical memory cues. In two experiments, we found that older adults were able to easily integrate this noninvasive intervention into their daily lives. Using HippoCamera to repeatedly reactivate memories for real-world events improved episodic recollection and it evoked more positive autobiographical sentiment at the time of retrieval. In both experiments, these benefits were observed shortly after the intervention and again after a 3-mo delay. Moreover, more detailed recollection was associated with more differentiated memory signals in the hippocampus. Thus, using this smartphone application to systematically reactivate memories for recent real-world experiences can help to maintain a bridge between the present and past in older adults.

Neural representations of naturalistic events are updated as our understanding of the past changes

The brain actively reshapes our understanding of past events in light of new incoming information. In the current study, we ask how the brain supports this updating process during the encoding and recall of naturalistic stimuli. One group of participants watched a movie ('The Sixth Sense') with a cinematic 'twist' at the end that dramatically changed the interpretation of previous events. Next, participants were asked to verbally recall the movie events, taking into account the new 'twist' information. Most participants updated their recall to incorporate the twist. Two additional groups recalled the movie without having to update their memories during recall: one group never saw the twist; another group was exposed to the twist prior to the beginning of the movie, and thus the twist information was incorporated both during encoding and recall. We found that providing participants with information about the twist beforehand altered neural response patterns during movie-viewing in the default mode network (DMN). Moreover, presenting participants with the twist at the end of the movie changed the neural representation of the previously-encoded information during recall in a subset of DMN regions. Further evidence for this transformation was obtained by comparing the neural activation patterns during encoding and recall and correlating them with behavioral signatures of memory updating. Our results demonstrate that neural representations of past events encoded in the DMN are dynamically integrated with new information that reshapes our understanding in natural contexts.

Removal of reinforcement improves instrumental performance in humans by decreasing a general action bias rather than unmasking learnt associations

Performance during instrumental learning is commonly believed to reflect the knowledge that has been acquired up to that point. However, recent work in rodents found that instrumental performance was enhanced during periods when reinforcement was withheld, relative to periods when reinforcement was provided. This suggests that reinforcement may mask acquired knowledge and lead to impaired performance. In the present study, we investigated whether such a beneficial effect of removing reinforcement translates to humans. Specifically, we tested whether performance during learning was improved during non-reinforced relative to reinforced task periods using signal detection theory and a computational modelling approach. To this end, 60 healthy volunteers performed a novel visual go/no-go learning task with deterministic reinforcement. To probe acquired knowledge in the absence of reinforcement, we interspersed blocks without feedback. In these non-reinforced task blocks, we found an increased d', indicative of enhanced instrumental performance. However, computational modelling showed that this improvement in performance was not due to an increased sensitivity of decision making to learnt values, but to a more cautious mode of responding, as evidenced by a reduction of a general response bias. Together with an initial tendency to act, this is sufficient to drive differential changes in hit and false alarm rates that jointly lead to an increased d'. To conclude, the improved instrumental performance in the absence of reinforcement observed in studies using asymmetrically reinforced go/no-go tasks may reflect a change in response bias rather than unmasking latent knowledge.

Phase separation of competing memories along the human hippocampal theta rhythm

Competition between overlapping memories is considered one of the major causes of forgetting, and it is still unknown how the human brain resolves such mnemonic conflict. In the present magnetoencephalography (MEG) study, we empirically tested a computational model that leverages an oscillating inhibition algorithm to minimise overlap between memories. We used a proactive interference task, where a reminder word could be associated with either a single image (non-competitive condition) or two competing images, and participants were asked to always recall the most recently learned word-image association. Time-resolved pattern classifiers were trained to detect the reactivated content of target and competitor memories from MEG sensor patterns, and the timing of these neural reactivations was analysed relative to the phase of the dominant hippocampal 3 Hz theta oscillation. In line with our pre-registered hypotheses, target and competitor reactivations locked to different phases of the hippocampal theta rhythm after several repeated recalls. Participants who behaviourally experienced lower levels of interference also showed larger phase separation between the two overlapping memories. The findings provide evidence that the temporal segregation of memories, orchestrated by slow oscillations, plays a functional role in resolving mnemonic competition by separating and prioritising relevant memories under conditions of high interference.

Correcting the hebbian mistake: Toward a fully error-driven hippocampus

The hippocampus plays a critical role in the rapid learning of new episodic memories. Many computational models propose that the hippocampus is an autoassociator that relies on Hebbian learning (i.e., "cells that fire together, wire together"). However, Hebbian learning is computationally suboptimal as it does not learn in a way that is driven toward, and limited by, the objective of achieving effective retrieval. Thus, Hebbian learning results in more interference and a lower overall capacity. Our previous computational models have utilized a powerful, biologically plausible form of error-driven learning in hippocampal CA1 and entorhinal cortex (EC) (functioning as a sparse autoencoder) by contrasting local activity states at different phases in the theta cycle. Based on specific neural data and a recent abstract computational model, we propose a new model called Theremin (Total Hippocampal ERror MINimization) that extends error-driven learning to area CA3-the mnemonic heart of the hippocampal system. In the model, CA3 responds to the EC monosynaptic input prior to the EC disynaptic input through dentate gyrus (DG), giving rise to a temporal difference between these two activation states, which drives error-driven learning in the EC→CA3 and CA3↔CA3 projections. In effect, DG serves as a teacher to CA3, correcting its patterns into more pattern-separated ones, thereby reducing interference. Results showed that Theremin, compared with our original Hebbian-based model, has significantly increased capacity and learning speed. The model makes several novel predictions that can be tested in future studies.

From remembering to reconstruction: The transformative neural representation of episodic memory

Although memory has long been recognized as a generative process, neural research of memory in recent decades has been predominantly influenced by Tulving's "mental time traveling" perspective and focused on the reactivation and consolidation of encoded memory representations. With the development of multiple powerful analytical approaches to characterize the contents and formats of neural representations, recent studies are able to provide detailed examinations of the representations at various processing stages and have provided exciting new insights into the transformative nature of episodic memory. These studies have revealed the rapid, substantial, and continuous transformation of memory representation during the encoding, maintenance, consolidation, and retrieval of both single and multiple events, as well as event sequences. These transformations are characterized by the abstraction, integration, differentiation, and reorganization of memory representations, enabling the long-term retention and generalization of memory. These studies mark a significant shift in perspective from remembering to reconstruction, which might better reveal the nature of memory and its roles in supporting more effective learning, adaptive decision-making, and creative problem solving.

Retrieval context determines whether event boundaries impair or enhance temporal order memory

Meaningful changes in context create "event boundaries", segmenting continuous experience into distinct episodes in memory. A foundational finding in this literature is that event boundaries impair memory for the temporal order of stimuli spanning a boundary compared to equally spaced stimuli within an event. This seems surprising in light of intuitions about memory in everyday life, where the order of within-event experiences (did I have coffee before the first bite of bagel?) often seems more difficult to recall than the order of events per se (did I have breakfast or do the dishes first?). Here, we aimed to resolve this discrepancy by manipulating whether stimuli carried information about their encoding context during retrieval, as they often do in everyday life (e.g., bagel-breakfast). In Experiments 1 and 2, we show that stimuli inherently associated with a unique encoding context produce a "flipped" order memory effect, whereby temporal memory was superior for cross-boundary than within-event item pairs. In Experiments 3 and 4, we added context information at retrieval to a standard laboratory event memory protocol where stimuli were encoded in the presence of arbitrary context cues (colored frames). We found that whether temporal order memory for cross-boundary stimuli was enhanced or impaired relative to within-event items depended on whether the context was present or absent during the memory test. Taken together, we demonstrate that the effect of event boundaries on temporal memory is malleable, and determined by the availability of context information at retrieval.

Retrieval suppression induced forgetting on 1-week-old consolidated episodic memories

Retrieval suppression has been established to cause forgetting on a wide range of memory types, but mostly in newly formed memories. Over time, the consolidation process stabilizes memory and changes the memory locus in the brain, which may affect the effectiveness of retrieval suppression. In two experiments, we examined whether retrieval suppression can induce forgetting on consolidated episodic memories and explored its potential reliance on explicit memory reactivation or spontaneous memory intrusions to destabilize the consolidated memory. We found that, compared with associative interference, another well-established forgetting approach, retrieval suppression consistently induced forgetting on 1-week-old memories. This suppression-induced forgetting was uncovered stably via an independent retrieval cue, suggesting its effect being on the target memory itself. However, we did not find evidence of modulation on the suppression-induced forgetting by either explicit reactivation or spontaneous intrusions. Together, our results extend the suppression-induced forgetting to episodic memories that have been consolidated for 1 week and suggest that retrieval suppression could destabilize consolidated memories.

Suppression weakens unwanted memories via a sustained reduction of neural reactivation

Aversive events sometimes turn into intrusive memories. However, prior evidence indicates that such memories can be controlled via a mechanism of retrieval suppression. Here, we test the hypothesis that suppression exerts a sustained influence on memories by deteriorating their neural representations. This deterioration, in turn, would hinder their subsequent reactivation and thus impoverish the vividness with which they can be recalled. In an fMRI study, participants repeatedly suppressed memories of aversive scenes. As predicted, this process rendered the memories less vivid. Using a pattern classifier, we observed that suppression diminished the neural reactivation of scene information both globally across the brain and locally in the parahippocampal cortices. Moreover, the decline in vividness was associated with reduced reinstatement of unique memory representations in right parahippocampal cortex. These results support the hypothesis that suppression weakens memories by causing a sustained reduction in the potential to reactivate their neural representations.

A neural network model of when to retrieve and encode episodic memories

Recent human behavioral and neuroimaging results suggest that people are selective in when they encode and retrieve episodic memories. To explain these findings, we trained a memory-augmented neural network to use its episodic memory to support prediction of upcoming states in an environment where past situations sometimes reoccur. We found that the network learned to retrieve selectively as a function of several factors, including its uncertainty about the upcoming state. Additionally, we found that selectively encoding episodic memories at the end of an event (but not mid-event) led to better subsequent prediction performance. In all of these cases, the benefits of selective retrieval and encoding can be explained in terms of reducing the risk of retrieving irrelevant memories. Overall, these modeling results provide a resource-rational account of why episodic retrieval and encoding should be selective and lead to several testable predictions.