Memory allocation and integration in rodents and humans

Consolidation improves the learning of new meanings for known words but not necessarily their integration into semantic memory

Consolidation is essential to the integration of novel words into the mental lexicon; however, its role in learning new meanings for known words remains unclear. This old-form-new-meaning learning is very common, as when one learns that "skate" is also a type of fish in addition to its familiar roller- or ice-skating meaning. To address consolidation effects for new meanings, we compared the behavioral and ERP measures on new and original meanings tested 24 hours after learning with words tested immediately after learning. Semantic judgments of both new and original meanings benefitted from the study-test interval. However, N400 amplitudes on studied words-indicators of meaning access from semantic memory-were unaffected by learning or consolidation. These results suggest that while sleep benefits memory for new meanings, the new meanings do not become integrated into the mental lexicon within that period. Instead, episodic retrieval remains functional in accessing new meanings even after 24 hours.

Emergence of a predictive model in the hippocampus

The brain organizes experiences into memories that guide future behavior. Hippocampal CA1 population activity is hypothesized to reflect predictive models that contain information about future events, but little is known about how they develop. We trained mice on a series of problems with or without a common statistical structure to observe how memories are formed and updated. Mice that learned structured problems integrated their experiences into a predictive model that contained the solutions to upcoming novel problems. Retrieving the model during learning improved discrimination accuracy and facilitated learning. Using calcium imaging to track CA1 activity during learning, we found that hippocampal ensemble activity became more stable as mice formed a predictive model. The hippocampal ensemble was reactivated during training and incorporated new activity patterns from each training problem. These results show how hippocampal activity supports building predictive models by organizing new information with respect to existing memories.

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.

Emotional learning retroactively promotes memory integration through rapid neural reactivation and reorganization

Neutral events preceding emotional experiences can be better remembered, likely by assigning them as significant to guide possible use in future. Yet, the neurobiological mechanisms of how emotional learning enhances memory for past mundane events remain unclear. By two behavioral studies and one functional magnetic resonance imaging study with an adapted sensory preconditioning paradigm, we show rapid neural reactivation and connectivity changes underlying emotion-charged retroactive memory enhancement. Behaviorally, emotional learning retroactively enhanced initial memory for neutral associations across the three studies. Neurally, emotional learning potentiated trial-specific reactivation of overlapping neural traces in the hippocampus and stimulus-relevant neocortex. It further induced rapid hippocampal-neocortical functional reorganization supporting such retroactive memory benefit, as characterized by enhanced hippocampal-neocortical coupling modulated by the amygdala during emotional learning, and a shift of hippocampal connectivity from stimulus-relevant neocortex to distributed transmodal prefrontal-parietal areas at post-learning rests. Together, emotional learning retroactively promotes memory integration for past neutral events through stimulating trial-specific reactivation of overlapping representations and reorganization of associated memories into an integrated network to foster its priority for future use.

More Stable Memory Retention of Novel Words Learned from Fast Mapping than from Explicit Encoding

There is a heated debate on a learning paradigm known as "fast mapping" for its early neocortical dependence and retained memory over time for amnesic patients with hippocampal system damage. Whether the fast mapping allows hippocampus independent learning and induces rapid integration is poorly understood. The present study aims to investigate the effect of fast mapping on very long-term retention, which to our knowledge has not been previously explored. We tested memory retention ranging from 10 min to 1.5 years, for novel word-object associations learned from fast mapping or explicit encoding procedures. The three-alternative forced choice recognition task was employed to assess memory performance. Besides the slight adjustment of the testing schedule, other settings remained the same in Experiment 2 to replicate and verify the findings of Experiment 1. Results showed that overall memory retrieval performance was higher after explicit encoding as compared to fast mapping. However, retrieval performance after explicit encoding dropped after 1.5 years, but remained stable in the fast mapping condition. Furthermore, matching the semantic category of the known and the novel items during the fast mapping paradigm might affect long-term retention. These results suggest that fast mapping creates more stable long-term memory representations as compared to the explicit encoding strategy.

Dimensions and mechanisms of memory organization

Memory formation is dynamic in nature, and acquisition of new information is often influenced by previous experiences. Memories sharing certain attributes are known to interact so that retrieval of one increases the likelihood of retrieving the other, raising the possibility that related memories are organized into associative mnemonic structures of interconnected representations. Although the formation and retrieval of single memories have been studied extensively, very little is known about the brain mechanisms that organize and link related memories. Here we review studies that suggest the existence of mnemonic structures in humans and animal models. These studies suggest three main dimensions of experience that can serve to organize related memories: time, space, and perceptual/conceptual similarities. We propose potential molecular, cellular, and systems mechanisms that might support organization of memories according to these dimensions.

The role of intrinsic excitability in the evolution of memory: Significance in memory allocation, consolidation, and updating

Memory is a dynamic process that is continuously regulated by both synaptic and intrinsic neural mechanisms. While numerous studies have shown that synaptic plasticity is important in various types and phases of learning and memory, neuronal intrinsic excitability has received relatively less attention, especially regarding the dynamic nature of memory. In this review, we present evidence demonstrating the importance of intrinsic excitability in memory allocation, consolidation, and updating. We also consider the intricate interaction between intrinsic excitability and synaptic plasticity in shaping memory, supporting both memory stability and flexibility.

The role of neuronal excitability, allocation to an engram and memory linking in the behavioral generation of a false memory in mice

Memory is a constructive, not reproductive, process that is prone to errors. Errors in memory, though, may originate from normally adaptive memory processes. At the extreme of memory distortion is falsely "remembering" an event that did not occur. False memories are well-studied in cognitive psychology, but have received relatively less attention in neuroscience. Here, we took advantage of mechanistic insights into how neurons are allocated or recruited into an engram (memory trace) to generate a false memory in mice using only behavioral manipulations. At the time of an event, neurons compete for allocation to an engram supporting the memory for this event; neurons with higher excitability win this competition (Han et al., 2007). Even after the event, these allocated "engram neurons" remain temporarily (~6 h) more excitable than neighboring neurons. Should a similar event occur in this 6 h period of heightened engram neuron excitability, an overlapping population of neurons will be co-allocated to this second engram, which serves to functionally link the two memories (Rashid et al., 2016). Here, we applied this principle of co-allocation and found that mice develop a false fear memory to a neutral stimulus if exposed to this stimulus shortly (3 h), but not a longer time (24 h), after cued fear conditioning. Similar to co-allocation, the generation of this false memory depended on the post-training excitability of engram neurons such that these neurons remained more excitable during exposure to the neutral stimulus at 3 h but not 24 h. Optogenetically silencing engram neurons 3 h after cued fear conditioning impaired formation of a false fear memory to the neutral stimulus, while optogenetically activating engram neurons 24 h after cued fear conditioning created a false fear memory. These results suggest that some false memories may originate from normally adaptive mnemonic processes such as neuronal excitability-dependent allocation and memory linking.

Predictability Changes What We Remember in Familiar Temporal Contexts

The human brain constantly anticipates the future based on memories of the past. Encountering a familiar situation reactivates memory of previous encounters, which can trigger a prediction of what comes next to facilitate responsiveness. However, a prediction error can lead to pruning of the offending memory, a process that weakens its representation in the brain and leads to forgetting. Our goal in this study was to evaluate whether memories are spared from such pruning in situations that allow for accurate predictions at the categorical level, despite prediction errors at the item level. Participants viewed a sequence of objects, some of which reappeared multiple times ("cues"), followed always by novel items. Half of the cues were followed by new items from different (unpredictable) categories, while others were followed by new items from a single (predictable) category. Pattern classification of fMRI data was used to identify category-specific predictions after each cue. Pruning was observed only in unpredictable contexts, while encoding of new items was less robust in predictable contexts. These findings demonstrate that how associative memories are updated is influenced by the reliability of abstract-level predictions in familiar contexts.

Interference between overlapping memories is predicted by neural states during learning

One of the primary contributors to forgetting is interference from overlapping memories. Intuitively, this suggests-and prominent theoretical models argue-that memory interference is best avoided by encoding overlapping memories as if they were unrelated. It is therefore surprising that reactivation of older memories during new encoding has been associated with reduced memory interference. Critically, however, prior studies have not directly established why reactivation reduces interference. Here, we first developed a behavioral paradigm that isolates the negative influence that overlapping memories exert during memory retrieval. We then show that reactivating older memories during the encoding of new memories dramatically reduces this interference cost at retrieval. Finally, leveraging multiple fMRI decoding approaches, we show that spontaneous reactivation of older memories during new encoding leads to integration of overlapping memories and, critically, that integration during encoding specifically reduces interference between overlapping, and otherwise competing, memories during retrieval.

The ontogeny of memory persistence and specificity

Interest in the ontogeny of memory blossomed in the twentieth century following the initial observations that memories from infancy and early childhood are rapidly forgotten. The intense exploration of infantile amnesia in subsequent years has led to a thorough characterization of its psychological determinants, although the neurobiology of memory persistence has long remained elusive. By contrast, other phenomena in the ontogeny of memory like infantile generalization have received relatively less attention. Despite strong evidence for reduced memory specificity during ontogeny, infantile generalization is poorly understood from psychological and neurobiological perspectives. In this review, we examine the ontogeny of memory persistence and specificity in humans and nonhuman animals at the levels of behavior and the brain. To this end, we first describe the behavioral phenotypes associated with each phenomenon. Looking into the brain, we then discuss neurobiological mechanisms in the hippocampus that contribute to the ontogeny of memory. Hippocampal neurogenesis and critical period mechanisms have recently been discovered to underlie amnesia during early development, and at the same time, we speculate that similar processes may contribute to the early bias towards memory generalization.

Transcending time in the brain: How event memories are constructed from experience

Our daily lives unfold continuously, yet when we reflect on the past, we remember those experiences as distinct and cohesive events. To understand this phenomenon, early investigations focused on how and when individuals perceive natural breakpoints, or boundaries, in ongoing experience. More recent research has examined how these boundaries modulate brain mechanisms that support long-term episodic memory. This work has revealed that a complex interplay between hippocampus and prefrontal cortex promotes the integration and separation of sequential information to help organize our experiences into mnemonic events. Here, we discuss how both temporal stability and change in one's thoughts, goals, and surroundings may provide scaffolding for these neural processes to link and separate memories across time. When learning novel or familiar sequences of information, dynamic hippocampal processes may work both independently from and in concert with other brain regions to bind sequential representations together in memory. The formation and storage of discrete episodic memories may occur both proactively as an experience unfolds. They may also occur retroactively, either during a context shift or when reactivation mechanisms bring the past into the present to allow integration. We also describe conditions and factors that shape the construction and integration of event memories across different timescales. Together these findings shed new light on how the brain transcends time to transform everyday experiences into meaningful memory representations.

Memory Allocation: Mechanisms and Function

Memories for events are thought to be represented in sparse, distributed neuronal ensembles (or engrams). In this article, we review how neurons are chosen to become part of a particular engram, via a process of neuronal allocation. Experiments in rodents indicate that eligible neurons compete for allocation to a given engram, with more excitable neurons winning this competition. Moreover, fluctuations in neuronal excitability determine how engrams interact, promoting either memory integration (via coallocation to overlapping engrams) or separation (via disallocation to nonoverlapping engrams). In parallel with rodent studies, recent findings in humans verify the importance of this memory integration process for linking memories that occur close in time or share related content. A deeper understanding of allocation promises to provide insights into the logic underlying how knowledge is normally organized in the brain and the disorders in which this process has gone awry.

Memory instability as a gateway to generalization

Our present frequently resembles our past. Patterns of actions and events repeat throughout our lives like a motif. Identifying and exploiting these patterns are fundamental to many behaviours, from creating grammar to the application of skill across diverse situations. Such generalization may be dependent upon memory instability. Following their formation, memories are unstable and able to interact with one another, allowing, at least in principle, common features to be extracted. Exploiting these common features creates generalized knowledge that can be applied across varied circumstances. Memory instability explains many of the biological and behavioural conditions necessary for generalization and offers predictions for how generalization is produced.

Sharp-wave ripples as a signature of hippocampal-prefrontal reactivation for memory during sleep and waking states

It is widely believed that memories that are encoded and retrieved during waking behavior are consolidated during sleep. Recent studies on the interactions between the hippocampus and the prefrontal cortex have greatly advanced our understanding of the physiological bases of these memory processes. Although hippocampal-prefrontal network activity differs in many aspects during waking and sleep states, here we review evidence that hippocampal sharp-wave ripples (SWRs) emerge as a common neurophysiological pattern in both states, facilitating communication between these two regions via coordinated reactivation of stored memory information. We further consider whether sleep and awake reactivation mediate similar memory processes or have different mnemonic functions, and the mechanistic role of this cross-regional dialogue in learning and memory. Finally, we provide an integrated view of how these two forms of reactivation might work together to support spatial learning and memory.