Asynchronous development of memory integration and differentiation influences temporal memory organization.

Adults remember items with shared contexts as occurring closer in time to one another than those associated with different contexts, even when their objective temporal distance is fixed. Such temporal memory biases are thought to reflect within-event integration and between-event differentiation processes that organize events according to their contextual similarities and differences, respectively. Within-event integration and between-event differentiation are hypothesized to differentially rely on binding and control processes, which may develop at different ages. To test this hypothesis, 5- to 12-year-olds and adults (N = 134) studied quartets of image pairs that contained either the same scene (same-context) or different scenes (different-context). Participants remembered same-context items as occurring closer in time by older childhood (7-9 years), whereas different-context items were remembered as occurring farther apart by early adolescence (10-12 years). The differential emergence of these temporal memory biases suggests within-event integration and between-event differentiation emerge at different ages. RESEARCH HIGHLIGHTS: Children are less likely than adults to use contextual information (e.g., location) to organize their continuous experience in memory, as indicated by temporal memory biases. Biases reflecting within-event integration (i.e., remembering elements with a shared context as occurring closer together in time) emerged in late childhood. Biases reflecting between-event differentiation (i.e., remembering elements from different contexts as occurring farther apart in time) emerged in early adolescence. The differential emergence of biases reflecting within-event integration and between-event differentiation suggests they are distinct, yet complementary, processes that support developmental improvements in event memory organization.

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.

Development of human hippocampal subfield microstructure and relation to associative inference.

The hippocampus is a complex brain structure composed of subfields that each have distinct cellular organizations. While the volume of hippocampal subfields displays age-related changes that have been associated with inference and memory functions, the degree to which the cellular organization within each subfield is related to these functions throughout development is not well understood. We employed an explicit model testing approach to characterize the development of tissue microstructure and its relationship to performance on 2 inference tasks, one that required memory (memory-based inference) and one that required only perceptually available information (perception-based inference). We found that each subfield had a unique relationship with age in terms of its cellular organization. While the subiculum (SUB) displayed a linear relationship with age, the dentate gyrus (DG), cornu ammonis field 1 (CA1), and cornu ammonis subfields 2 and 3 (combined; CA2/3) displayed nonlinear trajectories that interacted with sex in CA2/3. We found that the DG was related to memory-based inference performance and that the SUB was related to perception-based inference; neither relationship interacted with age. Results are consistent with the idea that cellular organization within hippocampal subfields might undergo distinct developmental trajectories that support inference and memory performance throughout development.

Generalization of cognitive maps across space and time.

Prominent theories posit that associative memory structures, known as cognitive maps, support flexible generalization of knowledge across cognitive domains. Here, we evince a representational account of cognitive map flexibility by quantifying how spatial knowledge formed one day was used predictively in a temporal sequence task 24 hours later, biasing both behavior and neural response. Participants learned novel object locations in distinct virtual environments. After learning, hippocampus and ventromedial prefrontal cortex (vmPFC) represented a cognitive map, wherein neural patterns became more similar for same-environment objects and more discriminable for different-environment objects. Twenty-four hours later, participants rated their preference for objects from spatial learning; objects were presented in sequential triplets from either the same or different environments. We found that preference response times were slower when participants transitioned between same- and different-environment triplets. Furthermore, hippocampal spatial map coherence tracked behavioral slowing at the implicit sequence transitions. At transitions, predictive reinstatement of virtual environments decreased in anterior parahippocampal cortex. In the absence of such predictive reinstatement after sequence transitions, hippocampus and vmPFC responses increased, accompanied by hippocampal-vmPFC functional decoupling that predicted individuals' behavioral slowing after a transition. Collectively, these findings reveal how expectations derived from spatial experience generalize to support temporal prediction.

Representations of common event structure in medial temporal lobe and frontoparietal cortex support efficient inference.

Prior work has shown that the brain represents memories within a cognitive map that supports inference about connections between individual related events. Real-world adaptive behavior is also supported by recognizing common structure among numerous distinct contexts; for example, based on prior experience with restaurants, when visiting a new restaurant one can expect to first get a table, then order, eat, and finally pay the bill. We used a neurocomputational approach to examine how the brain extracts and uses abstract representations of common structure to support novel decisions. Participants learned image pairs (AB, BC) drawn from distinct triads (ABC) that shared the same internal structure and were then tested on their ability to infer indirect (AC) associations. We found that hippocampal and frontoparietal regions formed abstract representations that coded cross-triad relationships with a common geometric structure. Critically, such common representational geometries were formed despite the lack of explicit reinforcement to do so. Furthermore, we found that representations in parahippocampal cortex are hierarchical, reflecting both cross-triad relationships and distinctions between triads. We propose that representations with common geometric structure provide a vector space that codes inferred item relationships with a direction vector that is consistent across triads, thus supporting faster inference. Using computational modeling of response time data, we found evidence for dissociable vector-based retrieval and pattern-completion processes that contribute to successful inference. Moreover, we found evidence that these processes are mediated by distinct regions, with pattern completion supported by hippocampus and vector-based retrieval supported by parahippocampal cortex and lateral parietal cortex.

Semantic Knowledge of Famous People and Places Is Represented in Hippocampus and Distinct Cortical Networks.

Studies have found that anterior temporal lobe (ATL) is critical for detailed knowledge of object categories, suggesting that it has an important role in semantic memory. However, in addition to information about entities, such as people and objects, semantic memory also encompasses information about places. We tested predictions stemming from the PMAT model, which proposes there are distinct systems that support different kinds of semantic knowledge: an anterior temporal (AT) network, which represents information about entities; and a posterior medial (PM) network, which represents information about places. We used representational similarity analysis to test for activation of semantic features when human participants viewed pictures of famous people and places, while controlling for visual similarity. We used machine learning techniques to quantify the semantic similarity of items based on encyclopedic knowledge in the Wikipedia page for each item and found that these similarity models accurately predict human similarity judgments. We found that regions within the AT network, including ATL and inferior frontal gyrus, represented detailed semantic knowledge of people. In contrast, semantic knowledge of places was represented within PM network areas, including precuneus, posterior cingulate cortex, angular gyrus, and parahippocampal cortex. Finally, we found that hippocampus, which has been proposed to serve as an interface between the AT and PM networks, represented fine-grained semantic similarity for both individual people and places. Our results provide evidence that semantic knowledge of people and places is represented separately in AT and PM areas, whereas hippocampus represents semantic knowledge of both categories.SIGNIFICANCE STATEMENT Humans acquire detailed semantic knowledge about people (e.g., their occupation and personality) and places (e.g., their cultural or historical significance). While research has demonstrated that brain regions preferentially respond to pictures of people and places, less is known about whether these regions preferentially represent semantic knowledge about specific people and places. We used machine learning techniques to develop a model of semantic similarity based on information available from Wikipedia, validating the model against similarity ratings from human participants. Using our computational model, we found that semantic knowledge about people and places is represented in distinct anterior temporal and posterior medial brain networks, respectively. We further found that hippocampus, an important memory center, represented semantic knowledge for both types of stimuli.

Memory Reactivation during Learning Simultaneously Promotes Dentate Gyrus/CA2,3 Pattern Differentiation and CA1 Memory Integration.

Events that overlap with previous experience may trigger reactivation of existing memories. However, such reactivation may have different representational consequences within the hippocampal circuit. Computational theories of hippocampal function suggest that dentate gyrus and CA2,3 (DG/CA2,3) are biased to differentiate highly similar memories, whereas CA1 may integrate related events by representing them with overlapping neural codes. Here, we tested whether the formation of differentiated or integrated representations in hippocampal subfields depends on the strength of memory reactivation during learning. Human participants of both sexes learned associations (AB pairs, either face-shape or scene-shape), and then underwent fMRI scanning while they encoded overlapping associations (BC shape-object pairs). Both before and after learning, participants were also scanned while viewing indirectly related elements of the overlapping memories (A and C images) in isolation. We used multivariate pattern analyses to measure reactivation of initial pair memories (A items) during overlapping pair (BC) learning, as well as learning-related representational change for indirectly related memory elements in hippocampal subfields. When prior memories were strongly reactivated during overlapping pair encoding, DG/CA2,3 and subiculum representations for indirectly related images (A and C) became less similar, consistent with pattern differentiation. Simultaneously, memory reactivation during new learning promoted integration in CA1, where representations for indirectly related memory elements became more similar after learning. Furthermore, memory reactivation and subiculum representation predicted faster and more accurate inference (AC) decisions. These data show that reactivation of related memories during new learning leads to dissociable coding strategies in hippocampal subfields, in line with computational theories.SIGNIFICANCE STATEMENT The flexibility of episodic memory allows us to remember both the details that differentiate similar events and the commonalities among them. Here, we tested how reactivation of past experience during new learning promotes formation of neural representations that might serve these two memory functions. We found that memory reactivation during learning promoted formation of differentiated representations for overlapping memories in the dentate gyrus/CA2,3 and subiculum subfields of the hippocampus, while simultaneously leading to the formation of integrated representations of related events in subfield CA1 Furthermore, memory reactivation and subiculum representation predicted success when inferring indirect relationships among events. These findings indicate that memory reactivation is an important learning signal that influences how overlapping events are represented within the hippocampal circuit.

Representations of Temporal Community Structure in Hippocampus and Precuneus Predict Inductive Reasoning Decisions.

Our understanding of the world is shaped by inferences about underlying structure. For example, at the gym, you might notice that the same people tend to arrive around the same time and infer that they are friends that work out together. Consistent with this idea, after participants are presented with a temporal sequence of objects that follows an underlying community structure, they are biased to infer that objects from the same community share the same properties. Here, we used fMRI to measure neural representations of objects after temporal community structure learning and examine how these representations support inference about object relationships. We found that community structure learning affected inferred object similarity: When asked to spatially group items based on their experience, participants tended to group together objects from the same community. Neural representations in perirhinal cortex predicted individual differences in object grouping, suggesting that high-level object representations are affected by temporal community learning. Furthermore, participants were biased to infer that objects from the same community would share the same properties. Using computational modeling of temporal learning and inference decisions, we found that inductive reasoning is influenced by both detailed knowledge of temporal statistics and abstract knowledge of the temporal communities. The fidelity of temporal community representations in hippocampus and precuneus predicted the degree to which temporal community membership biased reasoning decisions. Our results suggest that temporal knowledge is represented at multiple levels of abstraction, and that perirhinal cortex, hippocampus, and precuneus may support inference based on this knowledge.

Reinstatement of item-specific contextual details during retrieval supports recombination-related false memories.

Flexible retrieval mechanisms that allow us to infer relationships across events may also lead to memory errors or distortion when details of one event are misattributed to the related event. Here, we tested how making successful inferences alters representation of overlapping events, leading to false memories. Participants encoded overlapping associations ('AB' and 'BC'), each of which was superimposed on different indoor and outdoor scenes that were pre-exposed prior to associative learning. Participants were subsequently tested on both the directly learned pairs ('AB' and 'BC') and inferred relationships across pairs ('AC'). We predicted that when people make a correct inference, features associated with overlapping events may become integrated in memory. To test this hypothesis, participants completed a final detailed retrieval test, in which they had to recall the scene associated with initially learned 'AB' pairs (or 'BC' pairs). We found that the outcome of inference decisions impacted the degree to which neural patterns elicited during detailed 'AB' retrieval reflected reinstatement of the scene associated with the overlapping 'BC' event. After successful inference, neural patterns in the anterior hippocampus, posterior medial prefrontal cortex, and our content-reinstatement region (left inferior temporal gyrus) were more similar to the overlapping, yet incorrect 'BC' context relative to after unsuccessful inference. Further, greater hippocampal activity during inference was associated with greater reinstatement of the incorrect, overlapping context in our content-reinstatement region, which in turn tracked contextual misattributions during detailed retrieval. These results suggest recombining memories during successful inference can lead to misattribution of contextual details across related events, resulting in false memories.

Does memory reactivation during sleep support generalization at the cost of memory specifics?

Sleep is important for memory, but does it favor consolidation of specific details or extraction of generalized information? Both may occur together when memories are reactivated during sleep, or a loss of certain memory details may facilitate generalization. To examine these issues, we tested memory in participants who viewed landscape paintings by six artists. Paintings were cropped to show only a section of the scene. During a learning phase, each painting section was presented with the artist's name and with a nonverbal sound that had been uniquely associated with that artist. In a test of memory for specifics, participants were shown arrays of six painting sections, all by the same artist. Participants attempted to select the one that was seen in the learning phase. Generalization was tested by asking participants to view new paintings and, for each one, decide which of the six artists created it. After this testing, participants had a 90-minute sleep opportunity with polysomnographic monitoring. When slow-wave sleep was detected, three of the sound cues associated with the artists were repeatedly presented without waking the participants. After sleep, participants were again tested for memory specifics and generalization. Memory reactivation during sleep due to the sound cues led to a relative decline in accuracy on the specifics test, which could indicate the transition to a loss of detail that facilitates generalization, particularly details such as the borders. Generalization performance showed very little change after sleep and was unaffected by the sound cues. Although results tentatively implicate sleep in memory transformation, further research is needed to examine memory change across longer time periods.

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.

Developmental differences in temporal schema acquisition impact reasoning decisions.

Schemas capture patterns across multiple experiences, accumulating information about common event structures that guide decision making in new contexts. Schemas are an important principle of leading theories of cognitive development; yet, we know little about how children and adolescents form schemas and use schematic knowledge to guide decisions. Here, we show that the ability to acquire schematic knowledge based on the temporal regularities of events increases during childhood and adolescence. Furthermore, we show that temporally mediated schematic knowledge biases reasoning decisions in an age-dependent manner. Participants with greater temporal schematic knowledge were more likely to infer that temporally related items shared other, non-temporal properties, with adults showing the greatest relationship between schema knowledge and reasoning choices. These data indicate that the mechanisms underlying schema formation and expression are not fully developed until adulthood and may reflect the ongoing maturation of hippocampus and prefrontal cortex through adolescence.

Abstract Representation of Prospective Reward in the Hippocampus.

Motivation enhances memory by increasing hippocampal engagement during encoding. However, whether such increased hippocampal activation reflects encoding of the value of highly rewarding events per se is less understood. Here, using a monetary incentive encoding task with a novel manipulation, we tested in humans whether the hippocampus represents abstract reward value, independent of perceptual content. During functional MRI scanning, men and women studied object pairs, each preceded by a monetary reward cue indicating the amount of money they would receive if they successfully remembered the object pair at test. Reward cues varied on both the level of reward (penny, dime, and dollar) and visual form (picture or word) across trials to dissociate hippocampal responses to reward value from those reflecting the perceptual properties of the cues. Behaviorally, participants remembered pairs associated with the high reward (dollar) more often than pairs associated with lower rewards. Neural pattern-similarity analysis revealed that hippocampal and parahippocampal cortex activation patterns discriminated between cues of different value regardless of their visual form, and that hippocampal discrimination of value was most pronounced in participants who showed the greatest behavioral sensitivity to reward. Strikingly, hippocampal patterns were most distinct for reward cues that differed in value but had similar visual appearance, consistent with theoretical proposals of hippocampal-pattern differentiation of competing representations. Our data illustrate how contextual representations within the hippocampus go beyond space and time to include information about the motivational salience of events, with hippocampal reward coding tracking the motivational impact on later memory.SIGNIFICANCE STATEMENT Motivation, such as the promise of future rewards, enhances hippocampal engagement during encoding and promotes successful retention of events associated with valuable rewards. However, whether the hippocampus explicitly encodes reward value, dissociable from sensory information, is unclear. Here, we show that the hippocampus forms abstract representation of valuable rewards, encoding conceptual rather than perceptual information about the motivational context of individual events. Reward representation within the hippocampus is associated with preferential retention of high-value events in memory. Furthermore, we show that hippocampal-pattern differentiation serves to emphasize differences between visually similar events with distinct motivational salience. Collectively, these findings indicate that hippocampal contextual representations enable individuals to distinguish the motivational value of events, leading to prioritized encoding of significant memories.

Ventromedial Prefrontal Cortex Is Necessary for Normal Associative Inference and Memory Integration.

The ability to flexibly combine existing knowledge in response to novel circumstances is highly adaptive. However, the neural correlates of flexible associative inference are not well characterized. Laboratory tests of associative inference have measured memory for overlapping pairs of studied items (e.g., AB, BC) and for nonstudied pairs with common associates (i.e., AC). Findings from functional neuroimaging and neuropsychology suggest the ventromedial prefrontal cortex (vmPFC) may be necessary for associative inference. Here, we used a neuropsychological approach to test the necessity of vmPFC for successful memory-guided associative inference in humans using an overlapping pairs associative memory task. We predicted that individuals with focal vmPFC damage (n = 5; 3F, 2M) would show impaired inferential memory but intact non-inferential memory. Performance was compared with normal comparison participants (n = 10; 6F, 4M). Participants studied pairs of visually presented objects including overlapping pairs (AB, BC) and nonoverlapping pairs (XY). Participants later completed a three-alternative forced-choice recognition task for studied pairs (AB, BC, XY) and inference pairs (AC). As predicted, the vmPFC group had intact memory for studied pairs but significantly impaired memory for inferential pairs. These results are consistent with the perspective that the vmPFC is necessary for memory-guided associative inference, indicating that the vmPFC is critical for adaptive abilities that require application of existing knowledge to novel circumstances. Additionally, vmPFC damage was associated with unexpectedly reduced memory for AB pairs post-inference, which could potentially reflect retroactive interference. Together, these results reinforce an emerging understanding of a role for the vmPFC in brain networks supporting associative memory processes.SIGNIFICANCE STATEMENT We live in a constantly changing environment, so the ability to adapt our knowledge to support understanding of new circumstances is essential. One important adaptive ability is associative inference which allows us to extract shared features from distinct experiences and relate them. For example, if we see a woman holding a baby, and later see a man holding the same baby, then we might infer that the two adults are a couple. Despite the importance of associative inference, the brain systems necessary for this ability are not known. Here, we report that damage to human ventromedial prefrontal cortex (vmPFC) disproportionately impairs associative inference. Our findings show the necessity of the vmPFC for normal associative inference and memory integration.

Performance of semi-automated hippocampal subfield segmentation methods across ages in a pediatric sample.

Episodic memory function has been shown to depend critically on the hippocampus. This region is made up of a number of subfields, which differ in both cytoarchitectural features and functional roles in the mature brain. Recent neuroimaging work in children and adolescents has suggested that these regions may undergo different developmental trajectories-a fact that has important implications for how we think about learning and memory processes in these populations. Despite the growing research interest in hippocampal structure and function at the subfield level in healthy young adults, comparatively fewer studies have been carried out looking at subfield development. One barrier to studying these questions has been that manual segmentation of hippocampal subfields-considered by many to be the best available approach for defining these regions-is laborious and can be infeasible for large cross-sectional or longitudinal studies of cognitive development. Moreover, manual segmentation requires some subjectivity and is not impervious to bias or error. In a developmental sample of individuals spanning 6-30 years, we assessed the degree to which two semi-automated segmentation approaches-one approach based on Automated Segmentation of Hippocampal Subfields (ASHS) and another utilizing Advanced Normalization Tools (ANTs)-approximated manual subfield delineation on each individual by a single expert rater. Our main question was whether performance varied as a function of age group. Across several quantitative metrics, we found negligible differences in subfield validity across the child, adolescent, and adult age groups, suggesting that these methods can be reliably applied to developmental studies. We conclude that ASHS outperforms ANTs overall and is thus preferable for analyses carried out in individual subject space. However, we underscore that ANTs is also acceptable and may be well-suited for analyses requiring normalization to a single group template (e.g., voxelwise analyses across a wide age range). Previous work has supported the use of such methods in healthy young adults, as well as several special populations such as older adults and those suffering from mild cognitive impairment. Our results extend these previous findings to show that ASHS and ANTs can also be used in pediatric populations as young as six.

Functional connectivity between memory and reward centers across task and rest track memory sensitivity to reward.

External motivation, such as a promise of future monetary reward for remembering an event, can affect which events are remembered. Reward-based memory modulation is thought to result from encoding and post-encoding interactions between dopaminergic midbrain, signaling reward, and hippocampus and parahippocampal cortex, supporting episodic memory. We asked whether hippocampal and parahippocampal interactions with other reward-related regions are related to reward modulation of memory and whether such relationships are stable over time. Individuals' memory sensitivity to reward was measured using a monetary incentive encoding task in which a cue indicated potential monetary reward (penny, dime, or dollar) for remembering an upcoming object pair. Functional connectivity between memory and reward regions was measured before, during, and following the task. Reward-related regions of interest were generated using a meta-analysis of existing studies on reward and included ventral striatum, medial and orbital prefrontal cortices and anterior cingulate cortex, in addition to midbrain. The results showed that connectivity between memory and reward regions tracked individual differences in reward modulation of memory, irrespective of when connectivity was measured. Connectivity patterns of anterior cingulate, orbitofrontal cortex, and ventral striatum covaried together and tracked behavior most strongly. These findings implicate a broader set of reward regions in reward modulation of memory than considered previously and provide new evidence that stable connectivity patterns between memory and reward centers relate to individual differences in how reward impacts memory.

Dynamic updating of hippocampal object representations reflects new conceptual knowledge.

Concepts organize the relationship among individual stimuli or events by highlighting shared features. Often, new goals require updating conceptual knowledge to reflect relationships based on different goal-relevant features. Here, our aim is to determine how hippocampal (HPC) object representations are organized and updated to reflect changing conceptual knowledge. Participants learned two classification tasks in which successful learning required attention to different stimulus features, thus providing a means to index how representations of individual stimuli are reorganized according to changing task goals. We used a computational learning model to capture how people attended to goal-relevant features and organized object representations based on those features during learning. Using representational similarity analyses of functional magnetic resonance imaging data, we demonstrate that neural representations in left anterior HPC correspond with model predictions of concept organization. Moreover, we show that during early learning, when concept updating is most consequential, HPC is functionally coupled with prefrontal regions. Based on these findings, we propose that when task goals change, object representations in HPC can be organized in new ways, resulting in updated concepts that highlight the features most critical to the new goal.

Temporal Proximity Promotes Integration of Overlapping Events.

Events with overlapping elements can be encoded as two separate representations or linked into an integrated representation, yet we know little about the conditions that promote one form of representation over the other. Here, we tested the hypothesis that the proximity of overlapping events would increase the probability of integration. Participants first established memories for house-object and face-object pairs; half of the pairs were learned 24 hr before an fMRI session, and the other half 30 min before the session. During scanning, participants encoded object-object pairs that overlapped with the initial pairs acquired on the same or prior day. Participants were also scanned as they made inference judgments about the relationships among overlapping pairs learned on the same or different day. Participants were more accurate and faster when inferring relationships among memories learned on the same day relative to those acquired across days, suggesting that temporal proximity promotes integration. Evidence for reactivation of existing memories-as measured by a visual content classifier-was equivalent during encoding of overlapping pairs from the two temporal conditions. In contrast, evidence for integration-as measured by a mnemonic strategy classifier from an independent study [Richter, F. R., Chanales, A. J. H., & Kuhl, B. A. Predicting the integration of overlapping memories by decoding mnemonic processing states during learning. Neuroimage, 124, 323-335, 2016]-was greater for same-day overlapping events, paralleling the behavioral results. During inference itself, activation patterns further differentiated when participants were making inferences about events acquired on the same day versus across days. These findings indicate that temporal proximity of events promotes integration and further influences the neural mechanisms engaged during inference.

Hippocampal Structure Predicts Statistical Learning and Associative Inference Abilities during Development.

Despite the importance of learning and remembering across the lifespan, little is known about how the episodic memory system develops to support the extraction of associative structure from the environment. Here, we relate individual differences in volumes along the hippocampal long axis to performance on statistical learning and associative inference tasks-both of which require encoding associations that span multiple episodes-in a developmental sample ranging from ages 6 to 30 years. Relating age to volume, we found dissociable patterns across the hippocampal long axis, with opposite nonlinear volume changes in the head and body. These structural differences were paralleled by performance gains across the age range on both tasks, suggesting improvements in the cross-episode binding ability from childhood to adulthood. Controlling for age, we also found that smaller hippocampal heads were associated with superior behavioral performance on both tasks, consistent with this region's hypothesized role in forming generalized codes spanning events. Collectively, these results highlight the importance of examining hippocampal development as a function of position along the hippocampal axis and suggest that the hippocampal head is particularly important in encoding associative structure across development.

Memory reactivation during rest supports upcoming learning of related content.

Although a number of studies have highlighted the importance of offline processes for memory, how these mechanisms influence future learning remains unknown. Participants with established memories for a set of initial face-object associations were scanned during passive rest and during encoding of new related and unrelated pairs of objects. Spontaneous reactivation of established memories and enhanced hippocampal-neocortical functional connectivity during rest was related to better subsequent learning, specifically of related content. Moreover, the degree of functional coupling during rest was predictive of neural engagement during the new learning experience itself. These results suggest that through rest-phase reactivation and hippocampal-neocortical interactions, existing memories may come to facilitate encoding during subsequent related episodes.